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๐€ ๐’๐ง๐ž๐š๐ค ๐๐ž๐ž๐ค ๐ข๐ง๐ญ๐จ $DSYNC ๐๐ซ๐ข๐ฆ๐ฎ๐ฌ ๐Ÿ.๐ŸŽ โ€“ ๐“๐ก๐ž ๐Œ๐จ๐ฌ๐ญ ๐€๐๐ฏ๐š๐ง๐œ๐ž๐ ๐€๐ˆ ๐€๐ ๐ž๐ง๐ญ ๐ข๐ง ๐–๐ž๐›๐Ÿ‘ Primus 2.0 isnโ€™t just another AI. Itโ€™s the most advanced on-chain AI agentโ€”๐œ๐š๐ฉ๐š๐›๐ฅ๐ž ๐จ๐Ÿ ๐›๐ฎ๐ข๐ฅ๐๐ข๐ง๐  ๐Ÿ๐ฎ๐ฅ๐ฅ๐ฒ ๐Ÿ๐ฎ๐ง๐œ๐ญ๐ข๐จ๐ง๐š๐ฅ ๐–๐ž๐›๐Ÿ‘ ๐๐€๐ฉ๐ฉ๐ฌ, ๐œ๐จ๐ฆ๐ฉ๐ฅ๐ž๐ญ๐ž๐ฅ๐ฒ ๐š๐ฎ๐ญ๐จ๐ง๐จ๐ฆ๐จ๐ฎ๐ฌ๐ฅ๐ฒ. In this sneak peak video of the upcoming upgrade coming to Primus, ๐ข๐ญ...

106,156 gรถrรผntรผleme โ€ข 1 yฤฑl รถnce โ€ขvia X (Twitter)

10 Yorum

Greg Caplan ๐Ÿš€ profil fotoฤŸrafฤฑ
Greg Caplan ๐Ÿš€2 yฤฑl รถnce

Stop wasting time following up with leads. Let our AI agents do it for you.

CryptoSkull ๐Ÿ’€ ze last bull standing profil fotoฤŸrafฤฑ
CryptoSkull ๐Ÿ’€ ze last bull standing1 yฤฑl รถnce

Dayum!! That's a big leap for @primus_sentient ๐Ÿ”ฅ

Inmortal profil fotoฤŸrafฤฑ
Inmortal1 yฤฑl รถnce

Run it back turbo

Satoshi Flipper profil fotoฤŸrafฤฑ
Satoshi Flipper1 yฤฑl รถnce

$DSYNC on FIRE ๐Ÿ”ฅ๐Ÿ”ฅ

Jamma Pelson profil fotoฤŸrafฤฑ
Jamma Pelson1 yฤฑl รถnce

HUGEEEEEE

Narly.sol profil fotoฤŸrafฤฑ
Narly.sol1 yฤฑl รถnce

That is crazy amazing ๐Ÿ™Œ ๐Ÿ†

Desfra Nctwcrk profil fotoฤŸrafฤฑ
Desfra Nctwcrk1 yฤฑl รถnce

Vote on the $DSYNC Rewards date now! Only those who vote within the next 48 hours will receive an early allocation from the Treasury Pool Funds. Vote Now โคต๏ธ

Drew profil fotoฤŸrafฤฑ
Drew1 yฤฑl รถnce

Leading the way $DSYNC

ElonTrades profil fotoฤŸrafฤฑ
ElonTrades1 yฤฑl รถnce

๐Ÿ”ฅ

MikiMouse profil fotoฤŸrafฤฑ
MikiMouse1 yฤฑl รถnce

๐Ÿ‘€

Benzer Videolar

$DSYNC ๐๐ซ๐ข๐ฆ๐ฎ๐ฌ ๐Ÿ.๐ŸŽ: ๐“๐ก๐ž ๐…๐ข๐ซ๐ฌ๐ญ ๐€๐ฎ๐ญ๐จ๐ง๐จ๐ฆ๐จ๐ฎ๐ฌ ๐Ž๐ง-๐‚๐ก๐š๐ข๐ง ๐€๐ˆ ๐ƒ๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ž๐ซ In the video, youโ€™ll witness ๐๐ซ๐ข๐ฆ๐ฎ๐ฌ ๐Ÿ.๐ŸŽ independently ๐ฐ๐ซ๐ข๐ญ๐ž ๐š ๐Ÿ๐ฎ๐ฅ๐ฅ ๐ฏ๐จ๐ญ๐ข๐ง๐  ๐ฌ๐ฆ๐š๐ซ๐ญ ๐œ๐จ๐ง๐ญ๐ซ๐š๐œ๐ญ inside Remix IDE, debug its own compilation errors, and deploy the contract on-chain ๐ฐ๐ข๐ญ๐ก๐จ๐ฎ๐ญ ๐š ๐ฌ๐ข๐ง๐ ๐ฅ๐ž ๐ฅ๐ข๐ง๐ž ๐จ๐Ÿ ๐œ๐จ๐๐ž ๐ฐ๐ซ๐ข๐ญ๐ญ๐ž๐ง ๐›๐ฒ ๐š ๐ก๐ฎ๐ฆ๐š๐ง. ๐–๐ก๐š๐ญ ๐’๐ž๐ญ๐ฌ ๐๐ซ๐ข๐ฆ๐ฎ๐ฌ ๐Ÿ.๐ŸŽ ๐€๐ฉ๐š๐ซ๐ญ? Not a chatbot. Not an API wrapper. Not a prompt engine. ๐๐ซ๐ข๐ฆ๐ฎ๐ฌ ๐Ÿ.๐ŸŽ ๐ข๐ฌ ๐ญ๐ก๐ž ๐Ÿ๐ข๐ซ๐ฌ๐ญ ๐Ÿ๐ฎ๐ฅ๐ฅ๐ฒ ๐š๐ฎ๐ญ๐จ๐ง๐จ๐ฆ๐จ๐ฎ๐ฌ ๐จ๐ง-๐œ๐ก๐š๐ข๐ง ๐€๐ˆ ๐š๐ ๐ž๐ง๐ญ ๐œ๐š๐ฉ๐š๐›๐ฅ๐ž ๐จ๐Ÿ ๐›๐ฎ๐ข๐ฅ๐๐ข๐ง๐  ๐š๐ง๐ ๐๐ž๐ฉ๐ฅ๐จ๐ฒ๐ข๐ง๐  ๐œ๐จ๐ฆ๐ฉ๐ฅ๐ž๐ญ๐ž ๐–๐ž๐›๐Ÿ‘ ๐š๐ฉ๐ฉ๐ฅ๐ข๐œ๐š๐ญ๐ข๐จ๐ง๐ฌ ๐ž๐ง๐ ๐ญ๐จ ๐ž๐ง๐. ๐Š๐ž๐ฒ ๐ˆ๐ง๐ง๐จ๐ฏ๐š๐ญ๐ข๐จ๐ง๐ฌ: -On-Chain Cognitive Execution: Full reasoning, code generation, deployment, and logic verification โ€” all happen trustlessly on-chain. -Autonomous Full-Screen Control: Primus sees the entire development interface and dynamically interacts with IDEs like Remix, Terminal, or VS Code, just like a real developer. -Decentralized Agentic Architecture: Powered by the HiveMind framework and Destra MCPs, Primus assembles specialized cognition units on demand for adaptive, modular intelligence. -Self-Healing Workflows: Primus detects and corrects its own bugs during compilation and testing โ€” no human intervention needed. -Web3-Native by Design: Unlike other agents tied to centralized APIs, Primus operates within decentralized compute, storage, and deployment pipelines. ๐๐ซ๐ข๐ฆ๐ฎ๐ฌ ๐ƒ๐จ๐ž๐ฌ๐งโ€™๐ญ ๐‰๐ฎ๐ฌ๐ญ ๐†๐ž๐ง๐ž๐ซ๐š๐ญ๐ž ๐‚๐จ๐๐ž โ€” ๐ˆ๐ญ ๐๐ฎ๐ข๐ฅ๐๐ฌ ๐ญ๐ก๐ž ๐…๐ฎ๐ญ๐ฎ๐ซ๐ž Primus 2.0 isnโ€™t just "๐€๐ˆ ๐Ÿ๐จ๐ซ ๐–๐ž๐›๐Ÿ‘." It is Web3, ๐ž๐ง๐ ๐ข๐ง๐ž๐ž๐ซ๐ž๐ ๐ง๐š๐ญ๐ข๐ฏ๐ž๐ฅ๐ฒ ๐Ÿ๐จ๐ซ ๐๐ž๐œ๐ž๐ง๐ญ๐ซ๐š๐ฅ๐ข๐ณ๐ž๐ ๐๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ฆ๐ž๐ง๐ญ. This is ๐ญ๐ก๐ž ๐Ÿ๐ข๐ซ๐ฌ๐ญ ๐ญ๐ซ๐ฎ๐ž ๐ฌ๐ญ๐ž๐ฉ ๐ญ๐จ๐ฐ๐š๐ซ๐ ๐š๐ฎ๐ญ๐จ๐ง๐จ๐ฆ๐จ๐ฎ๐ฌ ๐จ๐ง-๐œ๐ก๐š๐ข๐ง ๐€๐ˆ ๐ž๐ง๐ ๐ข๐ง๐ž๐ž๐ซ๐ข๐ง๐ , where AI doesnโ€™t just assist the developer "๐ข๐ญ ๐›๐ž๐œ๐จ๐ฆ๐ž๐ฌ ๐ญ๐ก๐ž ๐๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ž๐ซ".

Destra Network

43,535 gรถrรผntรผleme โ€ข 1 yฤฑl รถnce

๐ƒ๐ž๐ฌ๐ญ๐ซ๐š ๐๐ซ๐ข๐ฆ๐ฎ๐ฌ ๐Ÿ.๐ŸŽ ๐๐ž๐ญ๐š ๐ฉ๐ซ๐ž๐ฏ๐ข๐ž๐ฐโ€“ $DSYNC ๐“๐ก๐ž ๐€๐ˆ ๐€๐ ๐ž๐ง๐ญ ๐“๐ก๐š๐ญ ๐๐ฎ๐ข๐ฅ๐๐ฌ ๐–๐ž๐›๐Ÿ‘ ๐๐€๐ฉ๐ฉ๐ฌ ๐ฐ๐ข๐ญ๐ก ๐š ๐’๐ข๐ง๐ ๐ฅ๐ž ๐๐ซ๐จ๐ฆ๐ฉ๐ญ In this video, witness Primus 2.0 do something wild: ๐š๐ฎ๐ญ๐จ๐ง๐จ๐ฆ๐จ๐ฎ๐ฌ๐ฅ๐ฒ ๐š๐ซ๐œ๐ก๐ข๐ญ๐ž๐œ๐ญ, ๐œ๐จ๐๐ž, ๐š๐ง๐ ๐š๐ฌ๐ฌ๐ž๐ฆ๐›๐ฅ๐ž ๐ญ๐ก๐ซ๐ž๐ž ๐Ÿ๐ฎ๐ฅ๐ฅ ๐–๐ž๐›๐Ÿ‘ ๐๐€๐ฉ๐ฉ๐ฌ from scratch (it will build anything you want it to) : - ๐€ ๐๐ฒ๐ง๐š๐ฆ๐ข๐œ ๐’๐ญ๐š๐ค๐ข๐ง๐  ๐๐€๐ฉ๐ฉ - ๐€ ๐ฅ๐ข๐ฏ๐ž ๐๐…๐“ ๐€๐ฎ๐œ๐ญ๐ข๐จ๐ง ๐‡๐จ๐ฎ๐ฌ๐ž - ๐€ ๐Ÿ๐š๐ข๐ซ ๐‚๐จ๐ข๐ง ๐…๐ฅ๐ข๐ฉ ๐†๐š๐ฆ๐ž No templates. No hardcoded workflows. Just raw reasoning and autonomous build cycles. Powered by ๐ƒ๐ž๐ฌ๐ญ๐ซ๐šโ€™๐ฌ ๐ƒ๐ž๐œ๐ž๐ง๐ญ๐ซ๐š๐ฅ๐ข๐ณ๐ž๐ ๐Œ๐‚๐ ๐’๐ž๐ซ๐ฏ๐ž๐ซ๐ฌ, Primus taps into distributed intelligence pipelines. Through Cognitive Mesh Protocols, it connects with a swarm of decentralized toolchains, runtime sandboxes, and smart compiler agents. Using Context Hubs, it pulls domain-specific patterns, optimizes code in real-time, and resolves logic gapsโ€”without a single external query. ๐–๐ก๐š๐ญ ๐ฒ๐จ๐ฎโ€™๐ซ๐ž ๐ฐ๐š๐ญ๐œ๐ก๐ข๐ง๐  ๐ข๐ฌ๐งโ€™๐ญ ๐ฌ๐œ๐ซ๐ข๐ฉ๐ญ๐ž๐. ๐˜๐จ๐ฎโ€™๐ซ๐ž ๐ฐ๐š๐ญ๐œ๐ก๐ข๐ง๐  ๐š๐ง ๐€๐ˆ ๐ฌ๐ฒ๐ฌ๐ญ๐ž๐ฆ ๐›๐ฎ๐ข๐ฅ๐ ๐ฅ๐ข๐ค๐ž ๐š ๐Ÿ๐ฎ๐ฅ๐ฅ-๐ฌ๐ญ๐š๐œ๐ค ๐ž๐ง๐ ๐ข๐ง๐ž๐ž๐ซ ๐ฐ๐ข๐ญ๐ก ๐š๐ฎ๐ญ๐จ๐ง๐จ๐ฆ๐ฒ, ๐ฉ๐ซ๐ž๐œ๐ข๐ฌ๐ข๐จ๐ง, ๐š๐ง๐ ๐š ๐ฌ๐ฉ๐ž๐ž๐ ๐ญ๐ก๐š๐ญโ€™๐ฌ ๐Ÿ๐ซ๐š๐ง๐ค๐ฅ๐ฒ ๐ฎ๐ง๐Ÿ๐š๐ข๐ซ ๐ญ๐จ ๐ก๐ฎ๐ฆ๐š๐ง๐ฌ. This is how Web3 gets built now: decentralized, autonomous, and agent-native ~ Powered by Destra Network.

Destra Network

37,972 gรถrรผntรผleme โ€ข 1 yฤฑl รถnce

๐ƒ๐ž๐ฌ๐ญ๐ซ๐š ๐๐ž๐ญ๐ฐ๐จ๐ซ๐ค ๐Œ๐š๐ข๐ง๐ง๐ž๐ญ ๐๐ก๐š๐ฌ๐ž ๐Ÿ’ ๐†๐จ๐ž๐ฌ ๐‹๐ข๐ฏ๐ž ๐“๐ก๐ข๐ฌ ๐Œ๐จ๐ง๐ญ๐ก | $DSYNC ๐“๐ฎ๐ซ๐ง๐ฌ ๐ƒ๐ž๐Ÿ๐ฅ๐š๐ญ๐ข๐จ๐ง๐š๐ซ๐ฒ With the launch of ๐ƒ๐ž๐ฌ๐ญ๐ซ๐š ๐๐ž๐ญ๐ฐ๐จ๐ซ๐ค ๐Œ๐š๐ข๐ง๐ง๐ž๐ญ ๐๐ก๐š๐ฌ๐ž ๐Ÿ’ this month, a major shift begins, lets learn how: $DSYNC ๐›๐ž๐œ๐จ๐ฆ๐ž๐ฌ ๐๐ž๐Ÿ๐ฅ๐š๐ญ๐ข๐จ๐ง๐š๐ซ๐ฒ through ๐ฉ๐ซ๐จ๐ญ๐จ๐œ๐จ๐ฅ-๐ฅ๐ž๐ฏ๐ž๐ฅ ๐›๐ฎ๐ซ๐ง๐ฌ embedded across the entire ecosystem. Thanks to the integration of the ๐ƒ๐ž๐ฌ๐ญ๐ซ๐š ๐€๐ˆ ๐‚๐ก๐š๐ข๐ง, every serviceโ€”whether it's deploying AI agents with Destra Sentient, building apps through Genesis, or generating content via One-Click AIโ€”now runs through a system that ๐š๐ฎ๐ญ๐จ๐ฆ๐š๐ญ๐ข๐œ๐š๐ฅ๐ฅ๐ฒ ๐›๐ฎ๐ซ๐ง๐ฌ ๐š ๐ฉ๐จ๐ซ๐ญ๐ข๐จ๐ง ๐จ๐Ÿ $DSYNC ๐ฐ๐ข๐ญ๐ก ๐ž๐ฏ๐ž๐ซ๐ฒ ๐ฎ๐ฌ๐ž. This isnโ€™t symbolic:๐ข๐ญโ€™๐ฌ ๐ญ๐ž๐œ๐ก๐ง๐ข๐œ๐š๐ฅ. -Every AI inference -Every smart contract deployment -Every on-chain file upload -Every task run by an AI agent. All of it flows through the Destra AI Chain, triggering token burns in real time. This isnโ€™t just utilityโ€”itโ€™s a ๐ฌ๐ž๐ฅ๐Ÿ-๐ฌ๐ฎ๐ฌ๐ญ๐š๐ข๐ง๐ข๐ง๐  ๐๐ž๐Ÿ๐ฅ๐š๐ญ๐ข๐จ๐ง ๐ฅ๐จ๐จ๐ฉ: More usage โ†’ More $DSYNC burned โ†’ Lower supply โ†’ Higher scarcity Watch this infographic video to see how Phase 4 transforms $DSYNC into a truly scarce assetโ€”๐›๐ฒ ๐๐ž๐ฌ๐ข๐ ๐ง, ๐ง๐จ๐ญ ๐›๐ฒ ๐ฉ๐ซ๐จ๐ฆ๐ข๐ฌ๐ž๐ฌ. Welcome to the first blockchain where ๐€๐ˆ ๐ฎ๐ฌ๐š๐ ๐ž ๐๐ข๐ซ๐ž๐œ๐ญ๐ฅ๐ฒ ๐ซ๐ž๐๐ฎ๐œ๐ž๐ฌ ๐ญ๐ก๐ž ๐ง๐š๐ญ๐ข๐ฏ๐ž ๐ญ๐จ๐ค๐ž๐ง ๐ฌ๐ฎ๐ฉ๐ฉ๐ฅ๐ฒ. No inflation. No theoretical burns. Just real, protocol-enforced deflation. ๐๐ก๐š๐ฌ๐ž ๐Ÿ’ ๐ข๐ฌ ๐ฃ๐ฎ๐ฌ๐ญ ๐ญ๐ก๐ž ๐›๐ž๐ ๐ข๐ง๐ง๐ข๐ง๐ . ๐–๐š๐ญ๐œ๐ก ๐ง๐จ๐ฐ.

Destra Network

192,353 gรถrรผntรผleme โ€ข 1 yฤฑl รถnce

๐ˆ๐ง๐ญ๐ซ๐จ๐๐ฎ๐œ๐ข๐ง๐  ๐ƒ๐ž๐ฌ๐ญ๐ซ๐š ๐€๐ ๐ž๐ง๐ญ ๐— ๐๐ž๐ญ๐š: $DSYNC ๐“๐ก๐ž ๐–๐จ๐ซ๐ฅ๐โ€™๐ฌ ๐…๐ข๐ซ๐ฌ๐ญ ๐“๐ซ๐ฎ๐ฅ๐ฒ ๐ƒ๐ž๐œ๐ž๐ง๐ญ๐ซ๐š๐ฅ๐ข๐ณ๐ž๐ ๐€๐ˆ ๐€๐ ๐ž๐ง๐ญ Meet Agent X, the first creation of Destra Sentient, ๐ฉ๐จ๐ฐ๐ž๐ซ๐ž๐ ๐›๐ฒ ๐จ๐ฎ๐ซ ๐๐ž๐œ๐ž๐ง๐ญ๐ซ๐š๐ฅ๐ข๐ณ๐ž๐ ๐ข๐ง๐Ÿ๐ซ๐š๐ฌ๐ญ๐ซ๐ฎ๐œ๐ญ๐ฎ๐ซ๐ž. This is the first true decentralized AI agent, ensuring unparalleled security, transparency, and scalability through our network of independent nodes. At its core is our ๐‡๐ข๐ฏ๐ž๐Œ๐ข๐ง๐ ๐š๐ซ๐œ๐ก๐ข๐ญ๐ž๐œ๐ญ๐ฎ๐ซ๐ž, where Agent X ๐ข๐๐ž๐ง๐ญ๐ข๐Ÿ๐ข๐ž๐ฌ ๐ฒ๐จ๐ฎ๐ซ ๐ข๐ง๐ญ๐ž๐ง๐ญ and ๐ข๐ง๐ญ๐ž๐ฅ๐ฅ๐ข๐ ๐ž๐ง๐ญ๐ฅ๐ฒ ๐๐ž๐ฅ๐ž๐ ๐š๐ญ๐ž๐ฌ ๐ญ๐š๐ฌ๐ค๐ฌ ๐ญ๐จ ๐ฌ๐ฉ๐ž๐œ๐ข๐š๐ฅ๐ข๐ณ๐ž๐ ๐€๐ˆ ๐š๐ ๐ž๐ง๐ญ๐ฌ, ๐ž๐š๐œ๐ก ๐š๐ง ๐ž๐ฑ๐ฉ๐ž๐ซ๐ญ ๐ข๐ง ๐ข๐ญ๐ฌ ๐๐จ๐ฆ๐š๐ข๐ง. Powered by the Destra NPC Framework, built on Python, it supports seamless multi-agent collaboration and allows developers to easily build and expand using Python giving users unmatched flexibility. In this video, three key agents demonstrate the power of intelligent delegation: ๐Ÿ.๐“๐ก๐ž ๐’๐จ๐œ๐ข๐š๐ฅ ๐’๐ž๐ง๐ญ๐ข๐ง๐ž๐ฅ: This agent, acting as the eyes and ears on social platforms, forums, and online communities, is scanning Twitter, Reddit, Discord, and other spaces to gather the latest discussions, trends, and insights. From trending hashtags to niche group conversations, the Social Sentinel Agent is providing a comprehensive snapshot of whatโ€™s buzzing in the space. ๐Ÿ.๐“๐ก๐ž ๐Œ๐š๐ซ๐ค๐ž๐ญ ๐’๐ž๐ง๐ญ๐ข๐ง๐ž๐ฅ: This agent is keeping its finger on the pulse of the crypto markets, analyzing blockchain activity, monitoring market trends, and generating actionable insights related to cryptocurrencies, DeFi, and emerging technologies. Whether itโ€™s spotting a spike in trading volume or explaining the implications of a new protocol upgrade, the Market Sentinel is delivering precision. ๐Ÿ‘.๐“๐ก๐ž ๐–๐ข๐ญ ๐’๐ž๐ง๐ญ๐ข๐ง๐ž๐ฅ: This agent, specializing in humor and conversational charm, is ensuring that responses are not just accurate but also engaging, injecting personality and savagery. Whether delivering a witty reply or adding savagery, the Wit Sentinel is making interactions delightful. ๐”๐ง๐ฅ๐ข๐ค๐ž ๐ญ๐ซ๐š๐๐ข๐ญ๐ข๐จ๐ง๐š๐ฅ ๐€๐ˆ๐ฌ ๐ญ๐ก๐š๐ญ ๐ซ๐ž๐ฅ๐ฒ ๐จ๐ง ๐œ๐ž๐ง๐ญ๐ซ๐š๐ฅ๐ข๐ณ๐ž๐ ๐ฌ๐ฒ๐ฌ๐ญ๐ž๐ฆ๐ฌ, ๐€๐ ๐ž๐ง๐ญ ๐— ๐ฎ๐ฌ๐ž๐ฌ ๐ฌ๐ฉ๐ž๐œ๐ข๐š๐ฅ๐ข๐ณ๐ž๐ ๐š๐ ๐ž๐ง๐ญ๐ฌ ๐ญ๐ก๐š๐ญ ๐œ๐จ๐ฅ๐ฅ๐š๐›๐จ๐ซ๐š๐ญ๐ž ๐ฌ๐ž๐š๐ฆ๐ฅ๐ž๐ฌ๐ฌ๐ฅ๐ฒ ๐ฎ๐ง๐๐ž๐ซ ๐ญ๐ก๐ž ๐ ๐ฎ๐ข๐๐š๐ง๐œ๐ž ๐จ๐Ÿ ๐ญ๐ก๐ž ๐‡๐ข๐ฏ๐ž๐Œ๐ข๐ง๐ ๐๐ฎ๐ž๐ž๐ง ๐๐ž๐ž ๐š๐ง๐ ๐š๐œ๐ญ ๐š๐ฌ ๐จ๐ง๐ž. This modular, decentralized system ensures responses are faster, deeper, and more precise. Agent X ๐ž๐ฏ๐จ๐ฅ๐ฏ๐ž๐ฌ ๐ฐ๐ข๐ญ๐ก ๐ž๐ฏ๐ž๐ซ๐ฒ ๐ข๐ง๐ญ๐ž๐ซ๐š๐œ๐ญ๐ข๐จ๐ง, adding new agents to the HiveMind, each designed to excel in its niche. This is AI reimagined: intelligent, modular, and decentralized. With Agent X, youโ€™re not just chatting with an AIโ€”๐ฒ๐จ๐ฎโ€™๐ซ๐ž ๐ž๐ฑ๐ฉ๐ž๐ซ๐ข๐ž๐ง๐œ๐ข๐ง๐  ๐š ๐ญ๐ž๐š๐ฆ ๐จ๐Ÿ ๐๐จ๐ฆ๐š๐ข๐ง ๐ž๐ฑ๐ฉ๐ž๐ซ๐ญ๐ฌ ๐ฐ๐จ๐ซ๐ค๐ข๐ง๐  ๐ข๐ง ๐ซ๐ž๐š๐ฅ ๐ญ๐ข๐ฆ๐ž. Agent X is coming to X (Twitter this week) ๐“๐ก๐ž ๐ฏ๐ข๐๐ž๐จ ๐š๐ญ๐ญ๐š๐œ๐ก๐ž๐ ๐๐ข๐ฌ๐ฉ๐ฅ๐š๐ฒ๐ฌ ๐ข๐ญ ๐ข๐ง ๐ญ๐ž๐ฌ๐ญ๐ข๐ง๐  ๐ฉ๐ก๐š๐ฌ๐ž, ๐ข๐ญโ€™๐ฌ ๐ฉ๐ฎ๐ซ๐ฉ๐จ๐ฌ๐ž๐ฅ๐ฒ ๐ฆ๐š๐๐ž ๐ญ๐จ ๐ญ๐ž๐ฌ๐ญ ๐ฐ๐ข๐ญ๐ญ๐ฒ ๐ง๐š๐ญ๐ฎ๐ซ๐ž ๐จ๐Ÿ ๐ญ๐ก๐ž ๐›๐จ๐ญ ๐›๐ž๐œ๐š๐ฎ๐ฌ๐ž ๐ฐ๐ž ๐ค๐ง๐จ๐ฐ ๐ญ๐ก๐š๐ญโ€™๐ฌ ๐ฐ๐ก๐š๐ญ ๐ฒ๐จ๐ฎ ๐ฅ๐ข๐ค๐ž. The HiveMind is here. The future is decentralized. Are you ready?

Destra Network

194,056 gรถrรผntรผleme โ€ข 1 yฤฑl รถnce

Anthropic's Claude Ai Agents Team just Educated how to build production AI agents in under 30 mins. For Free. From the engineers who built the stack. CANCEL Your Weekend Plans, and Learn to Build AI Agents Today. Bookmark it. Watch it. Build your first production agent this weekend. $5,000/month. $7,000/month. $12,000/month. People are building agents for clients and charging $$$ as Beginners. You're still stuck in the thinking about AI phase. This video fixes that tonight. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward. โ†“ Ivan Nardini runs Developer Relations for AI at Google Cloud. He just gave away the entire production agent stack in 30 minutes. This is the talk that separates people deploying AI agents that actually scale from people whose agents break the moment they leave localhost. Here's everything inside. I break down a production AI video like this every week. Follow Himanshu Kumar. โ†“ The 4-part agent stack that actually scales. Most devs are duct-taping frameworks together and calling it an "AI agent." Ivan lays out the real stack: Agent Development Kit (ADK): open-source, code-first framework for building, evaluating, and deploying agents. Supports Claude models through Vertex AI directly. Model Context Protocol (MCP): lets your agent talk to any tool or data source with one standard. Vertex AI Agent Engine: managed platform for deploying, monitoring, and scaling agents in production. No DevOps headaches. Agent-to-Agent Protocol: open protocol so agents built on different frameworks can actually work together. This is the stack replacing every hacky agent setup in production right now. Full MCP + Claude breakdowns drop weekly on Himanshu Kumar. โ†“ Building your first real agent. Ivan builds a birthday planner agent live. LLM Agent class. Name it. Define instructions. Pick the model. He uses Claude 3.7 Sonnet. You could use Opus 4.7 for better reasoning. Full agent built in minutes. Not weeks. Watch the build once and you'll never structure an agent the wrong way again. I post agent architectures people pay $500 courses to learn. Himanshu Kumar. โ†“ Multi-agent systems without the chaos. Single agents are easy. Multi-agent systems are where 99% of builders fail. Ivan extends the birthday planner by: Adding a calendar service through MCP tools Creating an orchestrator agent to route requests between agents Handling state and context across agent handoffs This is production multi-agent architecture. Clean. Scalable. Debuggable. Most tutorials hand-wave this part. This one shows you every step. Multi-agent orchestration content drops weekly on Himanshu Kumar. โ†“ Deployment without the DevOps nightmare. This is where most AI projects die. You build a cool agent locally. It works. You try to deploy it. Everything breaks. Vertex AI Agent Engine fixes this: Minimal code deployment Automatic monitoring of latency, CPU, and memory Built-in observability and logging No infrastructure setup needed You provide config and requirements. The platform handles the rest. This is how agents actually get to production. Deployment guides for Claude agents post every week. Himanshu Kumar. โ†“ Agent-to-Agent Protocol: the future nobody's talking about. Most people don't know this exists yet. The A2A Protocol lets agents built in different frameworks communicate seamlessly. Your Claude agent. My LangChain agent. Someone else's CrewAI agent. All talking to each other. All solving parts of the same problem. All without custom integration code. This is the infrastructure layer of the coming AI economy. Getting in early on A2A Protocol is like getting in early on HTTP in 1995. A2A deep dive coming soon. Himanshu Kumar. โ†“ 30 minutes from the team shipping this in production. You'll learn more from this than from 6 months of YouTube tutorials made by people who've never deployed an agent past localhost. People who watch this understand production AI agents at the architect level. People who skip it keep hacking together frameworks that break every time an API updates. Save the video. Watch it tonight. Build a real agent this weekend. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Himanshu Kumar

226,535 gรถrรผntรผleme โ€ข 2 ay รถnce

OpenLedger X Morpheus The partnership of openledger with Morpheus enables Use Morpheus to build "The Autonomous Smart Contract Engineer" on top of OpenLedger. What is Morpheus? Morpheus is a Web3-native AI coding agent that turns natural language into executable smart contracts and full-stack dApps. It is powered by a specialized Solidity model built on top of OpenLedger, tailored for the unique demands of secure and efficient onchain development. It goes beyond code generation. Using fine-tuned models, agent-based architecture, and modular plugin support, Morpheus automates the entire development pipeline-from writing and simulating contracts to deploying and maintaining them. Its mission is to reduce the barrier to dApp creation while enabling autonomous agents and individuals to participate in decentralized economies. Why OpenLedger? The rise of AI agents in Web3 raises urgent questions around transparency, attribution, explainability, and contributor incentives. OpenLedger provides the infrastructure to ensure that contributor data used in model outputs is recorded with verifiable attribution. Through Proof of Attribution, contributors-whether they provide prompts, datasets, or logic refinements-can receive credit and rewards when their work influences model behavior. But attribution alone isnโ€™t enough. In critical domains like smart contract deployment, DeFi automation, and DAO governance, understanding why a model made a decision is just as important as the output itself. OpenLedger supports explainability by linking outputs back to their original data sources-allowing developers and auditors to trace logic, validate decisions, and build trust in AI-powered systems. OpenLedger supports Morpheus by: Recording which data was used in generating model outputs Enabling verifiable attribution of contributed datasets Powering reward mechanisms for contributors Offering scalable and efficient model execution via OpenLoRA Supporting transparency and traceability in model decision-making This creates an open, rewardable foundation for AI-driven coding-without relying on opaque systems. How is the system built? The Morpheus architecture has three layers: Datanet Layer OpenLedger powers Morpheus with a specialized Datanet - a decentralized data layer where developers, auditors, and contributors can share smart contract patterns, audit logs, exploit reports, and logic modules. Each submission is recorded onchain with attribution using OpenLedgerโ€™s Proof of Attribution. As the model learns and evolves from this data, contributors receive rewards proportional to their impact on future outputs. The Morpheus architecture has two layers: Intent Layer Users describe what they want to build. Example: "Create a token with tax logic that routes to a DAO." Morpheus parses the instruction, retrieves relevant contract types, and plans a modular execution flow. Agent Layer The agent generates, tests, and assembles the contract. It handles versioning, logic validation, and deployment readiness. Security checks-reentrancy protection, overflow control, gas modeling-are embedded into the generation phase. Generated outputs are mapped to their source data using OpenLedgerโ€™s Proof of Attribution, providing traceability across the pipeline. How does the AI model work? Morpheus is being powered by a specialized Solidity model built on top of OpenLedger. This model is purpose-built to handle the nuances of smart contract logic, security, and upgradeability. Unlike generalized coding agents, it is designed specifically for EVM environments and Web3 use cases, drawing from real protocol data and security best practices. Morpheus is fine-tuned on a vertical stack of smart contract data: Audited protocol code (e.g., Uniswap V4, Compound) OpenZeppelin libraries and EIP reference implementations Smart contract vulnerability reports and exploit reconstructions Edge cases from fuzz testing and adversarial examples It uses models like CodeLlama and DeepSeek-Coder, enhanced through RAG pipelines referencing standardized security patterns and emerging protocol designs. This training stack is integrated into a continuous feedback loop, enabling real-time specialization for EVM and beyond. Why a specialized model is needed? Smart contract development is uniquely high-stakes. A generalized AI model is not enough. As 'vibe coding' and natural language programming become more common, we're seeing an influx of AI-generated code in Web3 as well. But smart contracts are not frontends or prototypes-they govern real value, enforce trustless execution, and often become immutable after deployment. Billions have been lost in Web3 due to bugs and inefficiencies: In 2022 alone, over $3.8 billion was stolen due to smart contract exploits, many of which stemmed from avoidable issues like reentrancy, integer overflows, or access control failures. Inefficient contract structures lead to unnecessary gas consumption. Optimizing for gas can reduce costs by up to 40%, saving projects millions over time. Upgradeable contract patterns, like UUPS or Transparent Proxies, require strict adherence to storage layout and initialization rules. Mistakes here often go undetected by generic models and can render a contract unupgradeable or vulnerable. A specialized Solidity model is trained on real-world exploits, EIP standards, and libraries like OpenZeppelin to: Generate secure, gas-efficient code by default Recognize and correctly implement complex proxy patterns Map user intent to modular, auditable contract architectures Incorporate battle-tested logic from audited protocols and fuzz-tested edge cases Morpheus goes beyond syntax-it understands the nuances of decentralized infrastructure and deploys code that meets production-grade standards. What applications will this enable Token creation with built-in logic (tax, liquidity, governance) DeFi automations triggered by market conditions Payment contracts between agents and contributors DAO tooling with dynamic NFT-based voting Cross-chain bridging logic tied to real-world oracles Asset issuance flows through chat-based interfaces Natural language contract templates with reusable logic Each of these flows is backed by OpenLedgerโ€™s Proof of Attribution-ensuring traceability, explainability, and fair rewards across the ecosystem. This is the future of AI-native development. Open. Attributed. Explainable. Community-powered. Morpheus and OpenLedger are building the first system for autonomous coding agents where: Contributor work is recorded onchain Reuse is incentivized through attribution Model outputs are traceable and explainable Contracts evolve through human-agent collaboration Anyone can contribute prompts, logic, or flows-and get rewarded The smart contract engineer is no longer a human-only role. It is an agentic, decentralized, and transparent process-powered by OpenLedger.

OpenLedger

46,735 gรถrรผntรผleme โ€ข 1 yฤฑl รถnce

Everyone's building AI agents that run on someone else's server, store memory in someone else's database, and can be shut down by someone else's terms of service. I built one that can't be. FlowClaw is an AI agent that runs on a decentralized distributed computer. Your agent, your conversations, your memory, your tools โ€” all stored onchain on Flow, a distributed network of validator nodes across the world. Not a centralized cloud. Not someone's S3 bucket. A blockchain that functions as censorship-resistant compute and storage for your AI. This isn't a wrapper. Your agent is a Resource โ€” a first-class programmable object in Cadence (Flow's smart contract language) that physically lives in your account's on-chain storage. It can't be duplicated, seized, or deleted by anyone except you. Your encrypted messages, your cognitive memory, your scheduled tasks โ€” they persist on a global distributed ledger that no single entity controls. It's an alpha build. It will break. But it works today on mainnet and I want people to push it this weekend. What it does: You go to authenticate with a passkey (Face ID, Touch ID), and you have a blockchain account in seconds. No wallet. No seed phrase. No tokens needed โ€” gas is sponsored. You're immediately chatting with an AI agent that has real tool execution: live web data, token prices, on-chain balances, Cadence script execution, FLOW transfers. Every message is encrypted client-side before it touches the chain. The agent has a cognitive memory system โ€” it doesn't just remember your last message, it builds molecular memory clusters where related knowledge bonds together for contextual retrieval across sessions. You can spawn sub-agents from a visual canvas to run parallel research. The memory tab shows you exactly what your agent knows. Everything is transparent and everything is yours. 11 smart contracts. No external dependencies. No keeper networks. No account abstraction hacks. Here's the part that matters for the censorship-resistance crowd: FlowClaw supports BYOK โ€” bring your own key. You can plug in any LLM provider. But pair it with Venice and you get the full stack: a censorship-resistant AI model running inference with no content filtering, connected to an agent whose state lives on a decentralized network that no company can shut down, with end-to-end encrypted conversations that nobody can read โ€” not the relay operator, not the LLM provider, not the blockchain validators. Venice doesn't log prompts. Flow can't read your encrypted storage. The relay never sees your plaintext. That's not a privacy policy. That's architecture. You can also use OpenAI, Anthropic, or any OpenAI-compatible provider. The agent platform doesn't care โ€” it's model-agnostic. But the Venice pairing is the one that closes every gap in the stack. For the people tinkering with OpenClaw and the broader open-source agent ecosystem โ€” FlowClaw is exploring what happens when you take the agent off the cloud entirely. Not just open-sourcing the code (though it is), but putting the actual runtime state on a distributed computer. Your agent's memory isn't in a SQLite file on your laptop or a Pinecone index on someone's cluster. It's on-chain, encrypted, and replicated across every validator node on Flow. You own it the way you own a private key โ€” mathematically, not contractually. The blockchain here isn't a gimmick bolted onto an agent for token speculation. It's functioning as the infrastructure layer that replaces AWS. Flow accounts are programmable containers with their own storage, keys, and security capabilities. Passkey authentication works natively because Flow supports P-256 keys at the protocol level โ€” the same curve your phone uses for biometrics. Gas sponsorship works natively because Flow transactions have separate proposer, authorizer, and payer roles built into the protocol. No proxy contracts. No relayers. No ERC-4337. Now here's the part that interests me economically. Every FlowClaw interaction is an on-chain transaction. Every message stored, every memory committed, every session created, every sub-agent spawned. An active user might generate dozens of transactions in a single conversation. Scale that and FlowClaw becomes a real contributor to Flow's transaction volume. Flow.com becomes deflationary at 250 TPS. Applications like FlowClaw that generate high-frequency, storage-heavy transactions are exactly what moves the needle. Every encrypted message uses account storage, which requires FLOW balance to back it. Every transaction burns fees. The more agents running, the more demand for $FLOW โ€” not because of a tokenomics gimmick, but because the protocol literally requires it for compute and storage. FlowClaw doesn't have its own token. The token is $FLOW. The entire platform runs natively on the network โ€” using Flow storage, paying Flow transaction fees, backed by Flow account balances. If FlowClaw succeeds, FLOW captures that value directly. I'm sharing this early because the AI agent space is moving fast and I think the decentralized infrastructure angle is underexplored. Most "crypto AI" projects are tokens with a chatbot attached. FlowClaw is the opposite โ€” it's an agent platform that happens to use a blockchain because the blockchain solves real engineering problems that centralized infrastructure can't. Try it: Github: Create an agent, ask it something, spawn a sub-agent, check your memory tab, pair it with Venice for the full censorship-resistant stack. Break it and tell me what broke. If you think this direction matters, the best thing you can do is use it and give feedback. Your AI agent should be yours. Not your provider's. Not your platform's. Yours.

doodlifts โžก๏ธ Miami ๐Ÿ“

12,127 gรถrรผntรผleme โ€ข 4 ay รถnce

๐•๐ˆ๐‚๐“๐Ž๐‘ ๐ƒ๐€๐•๐ˆ๐’ ๐‡๐€๐๐’๐Ž๐ ๐‰๐”๐’๐“ ๐๐”๐‘๐ˆ๐„๐ƒ ๐“๐‡๐„ โ€œ๐…๐Ž๐‘๐„๐•๐„๐‘ ๐–๐€๐‘โ€ ๐‹๐ˆ๐„ ๐ˆ๐ ๐“๐‡๐ˆ๐‘๐“๐„๐„๐ ๐Œ๐ˆ๐๐”๐“๐„๐’. ๐ˆ๐‘๐€๐ ๐“๐„๐‘๐‘๐ˆ๐…๐ˆ๐„๐ƒ ๐’๐„๐•๐„๐ ๐๐‘๐„๐’๐ˆ๐ƒ๐„๐๐“๐’. ๐“๐‘๐”๐Œ๐ ๐ƒ๐„๐’๐“๐‘๐Ž๐˜๐„๐ƒ ๐ˆ๐“๐’ ๐€๐๐ˆ๐‹๐ˆ๐“๐˜ ๐“๐Ž ๐Œ๐€๐Š๐„ ๐–๐€๐‘ ๐ˆ๐ ๐…๐ˆ๐•๐„ ๐–๐„๐„๐Š๐’. ๐“๐‡๐ˆ๐’ ๐ˆ๐’ ๐“๐‡๐„ ๐‡๐ˆ๐’๐“๐Ž๐‘๐ˆ๐€๐โ€™๐’ ๐’๐‚๐Ž๐‘๐„๐‚๐€๐‘๐ƒ. Victor Davis Hanson โ€” the most decorated classical military historian in America, author of ๐˜›๐˜ฉ๐˜ฆ ๐˜š๐˜ฆ๐˜ค๐˜ฐ๐˜ฏ๐˜ฅ ๐˜ž๐˜ฐ๐˜ณ๐˜ญ๐˜ฅ ๐˜ž๐˜ข๐˜ณ๐˜ด and ๐˜›๐˜ฉ๐˜ฆ ๐˜Š๐˜ข๐˜ด๐˜ฆ ๐˜๐˜ฐ๐˜ณ ๐˜›๐˜ณ๐˜ถ๐˜ฎ๐˜ฑ, Hoover Institution senior fellow, lifelong scholar of how wars actually end โ€” spent thirteen minutes on the Daily Signal this week doing what no cable news anchor has bothered to do since February. He compared this war to every other war in American history and then showed his work. His conclusion, in his own words: โ€œ๐˜ž๐˜ฆโ€™๐˜ท๐˜ฆ ๐˜ฏ๐˜ฆ๐˜ท๐˜ฆ๐˜ณ ๐˜ต๐˜ข๐˜ฌ๐˜ฆ๐˜ฏ ๐˜ฐ๐˜ฏ ๐˜ข ๐˜ค๐˜ฐ๐˜ถ๐˜ฏ๐˜ต๐˜ณ๐˜บ ๐˜ฐ๐˜ง 93 ๐˜ฎ๐˜ช๐˜ญ๐˜ญ๐˜ช๐˜ฐ๐˜ฏ ๐˜ฑ๐˜ฆ๐˜ฐ๐˜ฑ๐˜ญ๐˜ฆ ๐˜ต๐˜ฉ๐˜ข๐˜ต ๐˜ฉ๐˜ข๐˜ฅ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฎ๐˜ฐ๐˜ด๐˜ต ๐˜ง๐˜ฆ๐˜ข๐˜ณ๐˜ด๐˜ฐ๐˜ฎ๐˜ฆ, ๐˜ต๐˜ฆ๐˜ณ๐˜ณ๐˜ช๐˜ฃ๐˜ญ๐˜ฆ ๐˜ณ๐˜ฆ๐˜ฑ๐˜ถ๐˜ต๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ฐ๐˜ง ๐˜ฃ๐˜ฆ๐˜ช๐˜ฏ๐˜จ ๐˜ฅ๐˜ข๐˜ฏ๐˜จ๐˜ฆ๐˜ณ๐˜ฐ๐˜ถ๐˜ด ๐˜ข๐˜ฏ๐˜ฅ ๐˜ถ๐˜ฏ๐˜ฑ๐˜ณ๐˜ฆ๐˜ฅ๐˜ช๐˜ค๐˜ต๐˜ข๐˜ฃ๐˜ญ๐˜ฆ, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ณ๐˜ถ๐˜ฏ๐˜ฏ๐˜ช๐˜ฏ๐˜จ ๐˜ต๐˜ฉ๐˜ฆ ๐˜”๐˜ช๐˜ฅ๐˜ฅ๐˜ญ๐˜ฆ ๐˜Œ๐˜ข๐˜ด๐˜ต ๐˜ธ๐˜ช๐˜ต๐˜ฉ ๐˜ข ๐˜ณ๐˜ช๐˜ฏ๐˜จ-๐˜ฐ๐˜ง-๐˜ง๐˜ช๐˜ณ๐˜ฆ ๐˜ฑ๐˜ณ๐˜ฐ๐˜น๐˜ช๐˜ฆ๐˜ด ๐˜ช๐˜ฏ ๐˜š๐˜บ๐˜ณ๐˜ช๐˜ข, ๐˜๐˜ณ๐˜ข๐˜ฒ, ๐˜ ๐˜ฆ๐˜ฎ๐˜ฆ๐˜ฏ, ๐˜Ž๐˜ข๐˜ป๐˜ข, ๐˜“๐˜ฆ๐˜ฃ๐˜ข๐˜ฏ๐˜ฐ๐˜ฏ โ€” ๐˜ช๐˜ฏ๐˜ฅ๐˜ฐ๐˜ฎ๐˜ช๐˜ต๐˜ข๐˜ฃ๐˜ญ๐˜ฆ. ๐˜›๐˜ฉ๐˜ฆ๐˜บ ๐˜ฉ๐˜ข๐˜ฅ ๐˜ต๐˜ฆ๐˜ณ๐˜ณ๐˜ช๐˜ง๐˜ช๐˜ฆ๐˜ฅ ๐˜ด๐˜ฆ๐˜ท๐˜ฆ๐˜ฏ ๐˜ฑ๐˜ณ๐˜ฆ๐˜ด๐˜ช๐˜ฅ๐˜ฆ๐˜ฏ๐˜ต๐˜ด. ๐˜ˆ๐˜ฏ๐˜ฅ ๐˜บ๐˜ฆ๐˜ต, ๐˜ช๐˜ฏ ๐˜ง๐˜ช๐˜ท๐˜ฆ ๐˜ธ๐˜ฆ๐˜ฆ๐˜ฌ๐˜ด, ๐˜ธ๐˜ฆ ๐˜ฅ๐˜ฆ๐˜ด๐˜ต๐˜ณ๐˜ฐ๐˜บ๐˜ฆ๐˜ฅ ๐˜ช๐˜ต๐˜ด ๐˜ข๐˜ฃ๐˜ช๐˜ญ๐˜ช๐˜ต๐˜บ ๐˜ต๐˜ฐ ๐˜ฎ๐˜ข๐˜ฌ๐˜ฆ ๐˜ธ๐˜ข๐˜ณ.โ€ Read that sentence and then read it again. ๐’๐ž๐ฏ๐ž๐ง ๐ฉ๐ซ๐ž๐ฌ๐ข๐๐ž๐ง๐ญ๐ฌ. ๐“๐ž๐ซ๐ซ๐ข๐Ÿ๐ข๐ž๐. ๐…๐ข๐ฏ๐ž ๐ฐ๐ž๐ž๐ค๐ฌ. ๐ƒ๐ž๐ฌ๐ญ๐ซ๐จ๐ฒ๐ž๐. That is not a Trump rally soundbite. That is Victor Davis Hanson, the man who wrote the textbooks on Thermopylae, Cannae, and the Pacific War, rendering verdict in real time on the fastest decisive American military victory since the First Gulf War, and arguably since 1945. Here is what Hanson walked through, and every single beat of it is lethal to the legacy narrative. ๐“๐ก๐ž ๐‚๐ซ๐ข๐ญ๐ข๐œ๐ฌ ๐๐ž๐ฏ๐ž๐ซ ๐ƒ๐ข๐ ๐“๐ก๐ž ๐‡๐จ๐ฆ๐ž๐ฐ๐จ๐ซ๐ค Hanson opens by naming names. The Democratic grandees in the House and Senate. The New York Times. The Washington Post. NPR. PBS. The Wall Street Journal news section. And โ€” this is the key part โ€” the disaffected ex-MAGA right that spent six weeks screaming ๐˜ž๐˜ฐ๐˜ณ๐˜ญ๐˜ฅ ๐˜ž๐˜ข๐˜ณ ๐˜๐˜๐˜ from podcasts and Substacks. He points out that these two camps share ๐ญ๐ฐ๐จ ๐ญ๐ก๐ข๐ง๐ ๐ฌ ๐ข๐ง ๐œ๐จ๐ฆ๐ฆ๐จ๐ง. First, ๐˜ต๐˜ฉ๐˜ฆ๐˜บ ๐˜ธ๐˜ข๐˜ฏ๐˜ต๐˜ฆ๐˜ฅ ๐˜ช๐˜ต ๐˜ฏ๐˜ฐ๐˜ต ๐˜ต๐˜ฐ ๐˜จ๐˜ฐ ๐˜ธ๐˜ฆ๐˜ญ๐˜ญ, because a Trump military success would destroy their entire post-2024 political project. Second, and more devastating: ๐ญ๐ก๐ž๐ฒ ๐ง๐ž๐ฏ๐ž๐ซ ๐๐ข๐ ๐š ๐ฌ๐ข๐ง๐ ๐ฅ๐ž ๐ก๐ข๐ฌ๐ญ๐จ๐ซ๐ข๐œ๐š๐ฅ ๐œ๐จ๐ฆ๐ฉ๐š๐ซ๐ข๐ฌ๐จ๐ง. Not one of them, Hanson notes, bothered to measure the Iran campaign against ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฃ๐˜ฐ๐˜ฎ๐˜ฃ๐˜ช๐˜ฏ๐˜จ ๐˜ค๐˜ข๐˜ฎ๐˜ฑ๐˜ข๐˜ช๐˜จ๐˜ฏ ๐˜ช๐˜ฏ ๐˜š๐˜ฆ๐˜ณ๐˜ฃ๐˜ช๐˜ข ๐˜ฐ๐˜ณ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฃ๐˜ฐ๐˜ฎ๐˜ฃ๐˜ช๐˜ฏ๐˜จ ๐˜ค๐˜ข๐˜ฎ๐˜ฑ๐˜ข๐˜ช๐˜จ๐˜ฏ ๐˜ช๐˜ฏ ๐˜“๐˜ช๐˜ฃ๐˜บ๐˜ข ๐˜ฐ๐˜ณ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ง๐˜ช๐˜ณ๐˜ด๐˜ต ๐˜Ž๐˜ถ๐˜ญ๐˜ง ๐˜ž๐˜ข๐˜ณ ๐˜ฐ๐˜ณ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ด๐˜ฆ๐˜ค๐˜ฐ๐˜ฏ๐˜ฅ ๐˜Ž๐˜ถ๐˜ญ๐˜ง ๐˜ž๐˜ข๐˜ณ ๐˜ฐ๐˜ณ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ˆ๐˜ง๐˜จ๐˜ฉ๐˜ข๐˜ฏ. Not one of them asked how many missiles the U.S. had destroyed, whether American aircraft had been shot down (45 were lost in the First Gulf War alone), whether the enemy command structure had been taken out. Instead, they just asserted the conclusion they needed: ๐˜ง๐˜ฐ๐˜ณ๐˜ฆ๐˜ท๐˜ฆ๐˜ณ ๐˜ธ๐˜ข๐˜ณ. That is not analysis. That is a feelings-forward prayer dressed up as journalism, and Hanson calls it for exactly what it is. ๐“๐ก๐ž ๐€๐œ๐ญ๐ฎ๐š๐ฅ ๐’๐œ๐จ๐ซ๐ž๐›๐จ๐š๐ซ๐: ๐…๐จ๐ฎ๐ซ ๐‘๐ฎ๐ฅ๐ข๐ง๐  ๐‚๐ฅ๐ข๐ช๐ฎ๐ž๐ฌ, ๐ƒ๐ž๐œ๐š๐ฉ๐ข๐ญ๐š๐ญ๐ž๐ Hansonโ€™s single most important factual paragraph of the 13 minutes: โ€œ๐˜๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ง๐˜ช๐˜ณ๐˜ด๐˜ต ๐˜ง๐˜ช๐˜ท๐˜ฆ ๐˜ธ๐˜ฆ๐˜ฆ๐˜ฌ๐˜ด, ๐˜ต๐˜ฉ๐˜ฆ ๐˜œ๐˜ฏ๐˜ช๐˜ต๐˜ฆ๐˜ฅ ๐˜š๐˜ต๐˜ข๐˜ต๐˜ฆ๐˜ด ๐˜ธ๐˜ช๐˜ต๐˜ฉ ๐˜ต๐˜ฉ๐˜ฆ ๐˜๐˜ด๐˜ณ๐˜ข๐˜ฆ๐˜ญ๐˜ช ๐˜ˆ๐˜ช๐˜ณ ๐˜๐˜ฐ๐˜ณ๐˜ค๐˜ฆ ๐˜ธ๐˜ช๐˜ฑ๐˜ฆ๐˜ฅ ๐˜ฐ๐˜ถ๐˜ต ๐˜ฎ๐˜ฐ๐˜ด๐˜ต ๐˜ฐ๐˜ง ๐˜ต๐˜ฉ๐˜ฆ ๐˜ต๐˜ฐ๐˜ฑ ๐˜ฆ๐˜ค๐˜ฉ๐˜ฆ๐˜ญ๐˜ฐ๐˜ฏ ๐˜ฐ๐˜ง ๐˜ต๐˜ฉ๐˜ฆ ๐˜ง๐˜ฐ๐˜ถ๐˜ณ ๐˜ณ๐˜ถ๐˜ญ๐˜ช๐˜ฏ๐˜จ ๐˜ค๐˜ญ๐˜ช๐˜ฒ๐˜ถ๐˜ฆ๐˜ด ๐˜ช๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ ๐˜๐˜ณ๐˜ข๐˜ฏ๐˜ช๐˜ข๐˜ฏ ๐˜ฏ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ.โ€ He lists them individually. Memorize this list, because it is the actual accounting of what ๐Ÿ๐ข๐ฏ๐ž ๐ฐ๐ž๐ž๐ค๐ฌ ๐จ๐Ÿ ๐€๐ฆ๐ž๐ซ๐ข๐œ๐š๐ง ๐š๐ง๐ ๐ˆ๐ฌ๐ซ๐š๐ž๐ฅ๐ข ๐š๐ข๐ซ๐ฉ๐จ๐ฐ๐ž๐ซ did to a regime that spent 46 years promising ๐˜‹๐˜ฆ๐˜ข๐˜ต๐˜ฉ ๐˜ต๐˜ฐ ๐˜ˆ๐˜ฎ๐˜ฆ๐˜ณ๐˜ช๐˜ค๐˜ข: ๐Ž๐ง๐ž. The Islamic Revolutionary Guard Corps โ€” IRGC command network shattered. Qassem-era terror infrastructure leadership dead or in hiding. ๐“๐ฐ๐จ. The regular Iranian Army โ€” senior general officer corps hollowed out by precision strike. ๐“๐ก๐ซ๐ž๐ž. The theocratic apparat โ€” including the Supreme Leader himself. The Assembly of Experts is reportedly unable to convene. ๐…๐จ๐ฎ๐ซ. The elected politicians โ€” the facade government, the President, the Foreign Minister, the Majlis leadership. ๐€๐ฅ๐ฅ ๐Ÿ๐จ๐ฎ๐ซ ๐ฉ๐ข๐ฅ๐ฅ๐š๐ซ๐ฌ ๐จ๐Ÿ ๐ญ๐ก๐ž ๐ซ๐ž๐ ๐ข๐ฆ๐ž ๐ฐ๐ž๐ซ๐ž ๐ก๐ข๐ญ. ๐’๐ข๐ฆ๐ฎ๐ฅ๐ญ๐š๐ง๐ž๐จ๐ฎ๐ฌ๐ฅ๐ฒ. ๐ˆ๐ง ๐ญ๐ก๐ข๐ซ๐ญ๐ฒ-๐Ÿ๐ข๐ฏ๐ž ๐๐š๐ฒ๐ฌ. That is not a ๐˜ฒ๐˜ถ๐˜ข๐˜จ๐˜ฎ๐˜ช๐˜ณ๐˜ฆ. That is not a ๐˜ด๐˜ต๐˜ข๐˜ญ๐˜ฆ๐˜ฎ๐˜ข๐˜ต๐˜ฆ. That is the most surgical decapitation of a hostile nation-state since the Japanese surrender ceremony on the USS Missouri. ๐“๐ก๐ž ๐“๐ก๐ซ๐ž๐ž-๐๐ก๐š๐ฌ๐ž ๐“๐ซ๐ฎ๐ฆ๐ฉ ๐’๐ญ๐ซ๐š๐ญ๐ž๐ ๐ฒ ๐‡๐š๐ง๐ฌ๐จ๐ง ๐€๐œ๐ญ๐ฎ๐š๐ฅ๐ฅ๐ฒ ๐ƒ๐ข๐š๐ ๐ซ๐š๐ฆ๐ฆ๐ž๐ Hanson then does something cable news cannot do in 45-second segments: he reconstructs the entire strategic arc. Three phases. Execute them in order. Win. ๐๐ก๐š๐ฌ๐ž ๐Ž๐ง๐ž: ๐Œ๐ข๐ฅ๐ข๐ญ๐š๐ซ๐ฒ ๐๐ž๐ฌ๐ญ๐ซ๐ฎ๐œ๐ญ๐ข๐จ๐ง. Find the tunnels. Find the hidden airfields. Find the silos. Find the people in bunkers. Kill the command structure. Leave the regime with ๐˜ข ๐˜ง๐˜ฆ๐˜ธ ๐˜ฅ๐˜ณ๐˜ฐ๐˜ฏ๐˜ฆ๐˜ด, ๐˜ข ๐˜ง๐˜ฆ๐˜ธ ๐˜ฃ๐˜ข๐˜ญ๐˜ญ๐˜ช๐˜ด๐˜ต๐˜ช๐˜ค ๐˜ฎ๐˜ช๐˜ด๐˜ด๐˜ช๐˜ญ๐˜ฆ๐˜ด and nothing with which to rebuild. ๐๐ก๐š๐ฌ๐ž ๐“๐ฐ๐จ: ๐“๐ก๐ž ๐จ๐Ÿ๐Ÿ๐ž๐ซ ๐ญ๐จ ๐ง๐ž๐ ๐จ๐ญ๐ข๐š๐ญ๐ž. Hanson: โ€œ๐˜›๐˜ณ๐˜ถ๐˜ฎ๐˜ฑ ๐˜ด๐˜ข๐˜ช๐˜ฅ ๐˜ต๐˜ฐ ๐˜ต๐˜ฉ๐˜ฆ๐˜ฎ, ๐˜ธ๐˜ฆ ๐˜ค๐˜ข๐˜ฏ ๐˜ฉ๐˜ข๐˜ท๐˜ฆ ๐˜ฏ๐˜ฆ๐˜จ๐˜ฐ๐˜ต๐˜ช๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ๐˜ด ๐˜ฏ๐˜ฐ๐˜ธ ๐˜ช๐˜ง ๐˜บ๐˜ฐ๐˜ถ ๐˜ฎ๐˜ฆ๐˜ฆ๐˜ต ๐˜ฐ๐˜ถ๐˜ณ ๐˜ฅ๐˜ฆ๐˜ฎ๐˜ข๐˜ฏ๐˜ฅ๐˜ด.โ€ Self-interested? Yes โ€” Trump wanted oil prices down before midterms. But it was also, Hanson argues, to ๐˜ญ๐˜ฆ๐˜ต ๐˜ต๐˜ฉ๐˜ฆ ๐˜ณ๐˜ฆ๐˜จ๐˜ช๐˜ฎ๐˜ฆ ๐˜ฉ๐˜ข๐˜ท๐˜ฆ ๐˜ข ๐˜ค๐˜ฉ๐˜ข๐˜ฏ๐˜ค๐˜ฆ ๐˜ข๐˜ฏ๐˜ฅ ๐˜ด๐˜ฉ๐˜ฐ๐˜ธ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ธ๐˜ฐ๐˜ณ๐˜ญ๐˜ฅ ๐˜ต๐˜ฉ๐˜ข๐˜ต ๐˜›๐˜ณ๐˜ถ๐˜ฎ๐˜ฑ ๐˜ธ๐˜ข๐˜ด ๐˜ฏ๐˜ฐ๐˜ต ๐˜ข ๐˜ฎ๐˜ข๐˜ฅ๐˜ฎ๐˜ข๐˜ฏ. Iran refused, betting that Western street protests and MAGA apostates would pressure Trump to fold. ๐‡๐ž ๐๐ข๐ ๐ง๐จ๐ญ ๐Ÿ๐จ๐ฅ๐. ๐‡๐ž ๐ก๐š๐ฌ ๐ง๐ž๐ฏ๐ž๐ซ ๐Ÿ๐จ๐ฅ๐๐ž๐. ๐๐ก๐š๐ฌ๐ž ๐“๐ก๐ซ๐ž๐ž: ๐„๐œ๐จ๐ง๐จ๐ฆ๐ข๐œ ๐ฌ๐ญ๐ซ๐š๐ง๐ ๐ฎ๐ฅ๐š๐ญ๐ข๐จ๐ง. When Iran announced it would close the Strait of Hormuz to everyone who was not ๐˜ฑ๐˜ณ๐˜ฐ-๐˜๐˜ณ๐˜ข๐˜ฏ๐˜ช๐˜ข๐˜ฏ, Hanson says Trump just took the pen out of their hand. โ€œ๐˜›๐˜ฉ๐˜ข๐˜ตโ€™๐˜ด ๐˜ข ๐˜จ๐˜ฐ๐˜ฐ๐˜ฅ ๐˜ช๐˜ฅ๐˜ฆ๐˜ข. ๐˜š๐˜ฉ๐˜ถ๐˜ต ๐˜ฅ๐˜ฐ๐˜ธ๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ ๐˜š๐˜ต๐˜ณ๐˜ข๐˜ช๐˜ต ๐˜ข๐˜ฏ๐˜ฅ ๐˜ญ๐˜ฆ๐˜ต ๐˜ช๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ ๐˜จ๐˜ฐ๐˜ฐ๐˜ฅ ๐˜จ๐˜ถ๐˜บ๐˜ด ๐˜ข๐˜ฏ๐˜ฅ ๐˜ด๐˜ต๐˜ฐ๐˜ฑ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฃ๐˜ข๐˜ฅ ๐˜จ๐˜ถ๐˜บ๐˜ด. ๐˜‰๐˜ถ๐˜ต ๐˜บ๐˜ฐ๐˜ถ๐˜ณ ๐˜ฃ๐˜ข๐˜ฅ ๐˜จ๐˜ถ๐˜บ๐˜ด ๐˜ข๐˜ณ๐˜ฆ ๐˜ฐ๐˜ถ๐˜ณ ๐˜จ๐˜ฐ๐˜ฐ๐˜ฅ ๐˜จ๐˜ถ๐˜บ๐˜ด, ๐˜ข๐˜ฏ๐˜ฅ ๐˜บ๐˜ฐ๐˜ถ๐˜ณ ๐˜จ๐˜ฐ๐˜ฐ๐˜ฅ ๐˜จ๐˜ถ๐˜บ๐˜ด ๐˜ข๐˜ณ๐˜ฆ ๐˜ฐ๐˜ถ๐˜ณ ๐˜ฃ๐˜ข๐˜ฅ ๐˜จ๐˜ถ๐˜บ๐˜ด.โ€ Translation: ๐ˆ๐ซ๐š๐ง ๐๐ž๐œ๐ฅ๐š๐ซ๐ž๐ ๐š ๐›๐ฅ๐จ๐œ๐ค๐š๐๐ž ๐จ๐Ÿ ๐ญ๐ก๐ž ๐ฐ๐จ๐ซ๐ฅ๐. ๐€๐ฆ๐ž๐ซ๐ข๐œ๐š ๐๐ž๐œ๐ฅ๐š๐ซ๐ž๐ ๐š ๐›๐ฅ๐จ๐œ๐ค๐š๐๐ž ๐จ๐Ÿ ๐ˆ๐ซ๐š๐ง. ๐€๐ฆ๐ž๐ซ๐ข๐œ๐š ๐ก๐š๐ฌ ๐š ๐œ๐š๐ซ๐ซ๐ข๐ž๐ซ ๐ฌ๐ญ๐ซ๐ข๐ค๐ž ๐ ๐ซ๐จ๐ฎ๐ฉ. ๐ˆ๐ซ๐š๐ง ๐ก๐š๐ฌ ๐๐“ ๐›๐จ๐š๐ญ๐ฌ ๐š๐ง๐ ๐ฆ๐ข๐ง๐ž๐ฌ. That is not a close fight. ๐“๐ก๐ž ๐‘๐ž๐ฌ๐ญ๐ซ๐š๐ข๐ง๐ญ ๐๐จ๐ข๐ง๐ญ ๐๐จ ๐Ž๐ง๐ž ๐Ž๐ง ๐“๐ก๐ž ๐‹๐ž๐Ÿ๐ญ ๐–๐ข๐ฅ๐ฅ ๐€๐œ๐ค๐ง๐จ๐ฐ๐ฅ๐ž๐๐ ๐ž Here is the paragraph that should be read aloud on every network tonight and will be read aloud on none of them. Hanson, coolly: โ€œ๐˜ž๐˜ฆโ€™๐˜ณ๐˜ฆ ๐˜ฏ๐˜ฐ๐˜ต ๐˜ญ๐˜ช๐˜ฌ๐˜ฆ ๐˜‰๐˜ข๐˜ณ๐˜ข๐˜ค๐˜ฌ ๐˜–๐˜ฃ๐˜ข๐˜ฎ๐˜ข ๐˜ช๐˜ฏ ๐˜“๐˜ช๐˜ฃ๐˜บ๐˜ข ๐˜ข๐˜ฏ๐˜ฅ ๐˜ต๐˜ข๐˜ฌ๐˜ช๐˜ฏ๐˜จ ๐˜ฐ๐˜ถ๐˜ต ๐˜ต๐˜ฆ๐˜ญ๐˜ฆ๐˜ท๐˜ช๐˜ด๐˜ช๐˜ฐ๐˜ฏ ๐˜ด๐˜ต๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ๐˜ด ๐˜ข๐˜ฏ๐˜ฅ ๐˜ฑ๐˜ฐ๐˜ณ๐˜ต๐˜ด. ๐˜ž๐˜ฆโ€™๐˜ณ๐˜ฆ ๐˜ฏ๐˜ฐ๐˜ต ๐˜ญ๐˜ช๐˜ฌ๐˜ฆ ๐˜‰๐˜ช๐˜ญ๐˜ญ ๐˜Š๐˜ญ๐˜ช๐˜ฏ๐˜ต๐˜ฐ๐˜ฏ ๐˜ช๐˜ฏ ๐˜š๐˜ฆ๐˜ณ๐˜ฃ๐˜ช๐˜ข ๐˜ต๐˜ฉ๐˜ข๐˜ต ๐˜ฅ๐˜ฆ๐˜ด๐˜ต๐˜ณ๐˜ฐ๐˜บ๐˜ฆ๐˜ฅ ๐˜ฆ๐˜ท๐˜ฆ๐˜ณ๐˜บ ๐˜ฃ๐˜ณ๐˜ช๐˜ฅ๐˜จ๐˜ฆ ๐˜ฐ๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ ๐˜‹๐˜ข๐˜ฏ๐˜ถ๐˜ฃ๐˜ฆ ๐˜ข๐˜ฏ๐˜ฅ ๐˜ต๐˜ฐ๐˜ฐ๐˜ฌ ๐˜ฐ๐˜ถ๐˜ต ๐˜ต๐˜ฉ๐˜ฆ๐˜ช๐˜ณ ๐˜จ๐˜ณ๐˜ช๐˜ฅ ๐˜ฐ๐˜ง ๐˜ข ๐˜ฎ๐˜ช๐˜ญ๐˜ญ๐˜ช๐˜ฐ๐˜ฏ ๐˜ข๐˜ฏ๐˜ฅ ๐˜ข ๐˜ฉ๐˜ข๐˜ญ๐˜ง ๐˜ฑ๐˜ฆ๐˜ฐ๐˜ฑ๐˜ญ๐˜ฆ. ๐˜ž๐˜ฆโ€™๐˜ณ๐˜ฆ ๐˜ฏ๐˜ฐ๐˜ต ๐˜๐˜ข๐˜ณ๐˜ณ๐˜บ ๐˜›๐˜ณ๐˜ถ๐˜ฎ๐˜ข๐˜ฏ ๐˜ต๐˜ฉ๐˜ข๐˜ต ๐˜ฅ๐˜ฆ๐˜ด๐˜ต๐˜ณ๐˜ฐ๐˜บ๐˜ฆ๐˜ฅ ๐˜ข๐˜ญ๐˜ญ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฉ๐˜บ๐˜ฅ๐˜ณ๐˜ฐ๐˜ฆ๐˜ญ๐˜ฆ๐˜ค๐˜ต๐˜ณ๐˜ช๐˜ค ๐˜ฑ๐˜ญ๐˜ข๐˜ฏ๐˜ต๐˜ด ๐˜ช๐˜ฏ ๐˜•๐˜ฐ๐˜ณ๐˜ต๐˜ฉ ๐˜’๐˜ฐ๐˜ณ๐˜ฆ๐˜ข. ๐˜ž๐˜ฆ ๐˜ญ๐˜ฆ๐˜ต ๐˜บ๐˜ฐ๐˜ถ ๐˜ฐ๐˜ง๐˜ง ๐˜ฆ๐˜ข๐˜ด๐˜บ.โ€ Get the implications of that. Every American president from Truman to Obama โ€” Democrat and Republican alike โ€” hit ๐๐ฎ๐š๐ฅ-๐ฎ๐ฌ๐ž ๐œ๐ข๐ฏ๐ข๐ฅ๐ข๐š๐ง ๐ข๐ง๐Ÿ๐ซ๐š๐ฌ๐ญ๐ซ๐ฎ๐œ๐ญ๐ฎ๐ซ๐ž in every major air campaign of the last 75 years. Truman flattened North Korean hydroelectric plants and killed civilians by the thousands. Clinton blacked out a million and a half Serbs and bombed Belgrade bridges on the Danube for weeks. Obama leveled Libyan television and ports. ๐ƒ๐จ๐ง๐š๐ฅ๐ ๐“๐ซ๐ฎ๐ฆ๐ฉ, ๐Ÿ๐ข๐ฏ๐ž ๐ฐ๐ž๐ž๐ค๐ฌ ๐ข๐ง๐ญ๐จ ๐ญ๐ก๐ž ๐ฆ๐จ๐ฌ๐ญ ๐œ๐จ๐ง๐ฌ๐ž๐ช๐ฎ๐ž๐ง๐ญ๐ข๐š๐ฅ ๐Œ๐ข๐๐๐ฅ๐ž ๐„๐š๐ฌ๐ญ ๐œ๐จ๐ง๐Ÿ๐ซ๐จ๐ง๐ญ๐š๐ญ๐ข๐จ๐ง ๐ฌ๐ข๐ง๐œ๐ž ๐˜๐จ๐ฆ ๐Š๐ข๐ฉ๐ฉ๐ฎ๐ซ, ๐ก๐š๐ฌ ๐ง๐จ๐ญ ๐ก๐ข๐ญ ๐š ๐ฌ๐ข๐ง๐ ๐ฅ๐ž ๐ˆ๐ซ๐š๐ง๐ข๐š๐ง ๐ฉ๐จ๐ฐ๐ž๐ซ ๐ฉ๐ฅ๐š๐ง๐ญ, ๐š ๐ฌ๐ข๐ง๐ ๐ฅ๐ž ๐ฐ๐š๐ญ๐ž๐ซ ๐ญ๐ซ๐ž๐š๐ญ๐ฆ๐ž๐ง๐ญ ๐Ÿ๐š๐œ๐ข๐ฅ๐ข๐ญ๐ฒ, ๐š ๐ฌ๐ข๐ง๐ ๐ฅ๐ž ๐›๐ซ๐ข๐๐ ๐ž, ๐จ๐ซ ๐š ๐ฌ๐ข๐ง๐ ๐ฅ๐ž ๐ซ๐ž๐Ÿ๐ข๐ง๐ž๐ซ๐ฒ. He has kept the war confined to the regimeโ€™s war-making capability and left the civilian grid intact. ๐“๐ก๐ž ๐ฆ๐š๐ง ๐ญ๐ก๐ž ๐ฅ๐ž๐ ๐š๐œ๐ฒ ๐ฉ๐ซ๐ž๐ฌ๐ฌ ๐œ๐š๐ฅ๐ฅ๐ž๐ ๐ซ๐ž๐œ๐ค๐ฅ๐ž๐ฌ๐ฌ ๐ข๐ฌ ๐ซ๐ฎ๐ง๐ง๐ข๐ง๐  ๐ญ๐ก๐ž ๐ฆ๐จ๐ฌ๐ญ ๐ฌ๐ฎ๐ซ๐ ๐ข๐œ๐š๐ฅ๐ฅ๐ฒ ๐ซ๐ž๐ฌ๐ญ๐ซ๐š๐ข๐ง๐ž๐ ๐š๐ข๐ซ ๐œ๐š๐ฆ๐ฉ๐š๐ข๐ ๐ง ๐ข๐ง ๐ฆ๐จ๐๐ž๐ซ๐ง ๐€๐ฆ๐ž๐ซ๐ข๐œ๐š๐ง ๐ก๐ข๐ฌ๐ญ๐จ๐ซ๐ฒ. Every talking head who called this a ๐˜ง๐˜ฐ๐˜ณ๐˜ฆ๐˜ท๐˜ฆ๐˜ณ ๐˜ธ๐˜ข๐˜ณ owes Hanson an apology for not knowing the historical baseline he is using. $๐Ÿ’๐ŸŽ๐ŸŽ ๐Œ๐ข๐ฅ๐ฅ๐ข๐จ๐ง ๐€ ๐ƒ๐š๐ฒ ๐€๐ง๐ ๐‚๐จ๐ฎ๐ง๐ญ๐ข๐ง๐  Hanson cites the economists now ๐˜ง๐˜ญ๐˜ช๐˜ฑ๐˜ฑ๐˜ช๐˜ฏ๐˜จ ๐˜ฐ๐˜ฏ ๐˜ข ๐˜ฅ๐˜ช๐˜ฎ๐˜ฆ at major research universities in Europe and the United States who have started to measure what the American counter-blockade is actually doing to Tehran. The number: $๐Ÿ’๐ŸŽ๐ŸŽ ๐ฆ๐ข๐ฅ๐ฅ๐ข๐จ๐ง ๐š ๐๐š๐ฒ ๐š๐ง๐ ๐œ๐ฅ๐ข๐ฆ๐›๐ข๐ง๐ . Lost oil sales. Lost petrochemical exports. Lost critical imports of mechanical goods, electrical components, and food. A regime that was already bankrupt before the war, that had hyperinflation eating its own middle class before the first bomb dropped, is now losing half a billion dollars every 24 hours. Hanson is blunt: โ€œ๐˜›๐˜ฉ๐˜ฆ๐˜บ ๐˜ธ๐˜ฆ๐˜ณ๐˜ฆ ๐˜ฃ๐˜ณ๐˜ฐ๐˜ฌ๐˜ฆ ๐˜ต๐˜ฐ ๐˜ฃ๐˜ฆ๐˜จ๐˜ช๐˜ฏ ๐˜ธ๐˜ช๐˜ต๐˜ฉ, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ต๐˜ฉ๐˜ฆ๐˜บ ๐˜ค๐˜ข๐˜ฏ'๐˜ต ๐˜ฅ๐˜ฐ ๐˜ข๐˜ฏ๐˜บ๐˜ต๐˜ฉ๐˜ช๐˜ฏ๐˜จ ๐˜ข๐˜ฃ๐˜ฐ๐˜ถ๐˜ต ๐˜ช๐˜ต ๐˜ฃ๐˜ฆ๐˜ค๐˜ข๐˜ถ๐˜ด๐˜ฆ ๐˜›๐˜ณ๐˜ถ๐˜ฎ๐˜ฑ ๐˜ฅ๐˜ช๐˜ฅ ๐˜ช๐˜ต ๐˜ด๐˜ฆ๐˜ฒ๐˜ถ๐˜ฆ๐˜ฏ๐˜ต๐˜ช๐˜ข๐˜ญ๐˜ญ๐˜บ. ๐˜”๐˜ช๐˜ญ๐˜ช๐˜ต๐˜ข๐˜ณ๐˜บ ๐˜ง๐˜ช๐˜ณ๐˜ด๐˜ต, ๐˜ค๐˜ฉ๐˜ข๐˜ฏ๐˜ค๐˜ฆ ๐˜ฐ๐˜ง ๐˜ฏ๐˜ฆ๐˜จ๐˜ฐ๐˜ต๐˜ช๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ด๐˜ฆ๐˜ค๐˜ฐ๐˜ฏ๐˜ฅ, ๐˜ฑ๐˜ถ๐˜ต ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฃ๐˜ฐ๐˜ฐ๐˜ต ๐˜ฐ๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฏ๐˜ฆ๐˜ค๐˜ฌ ๐˜ต๐˜ฉ๐˜ช๐˜ณ๐˜ฅ.โ€ ๐“๐ก๐š๐ญ ๐ข๐ฌ ๐š ๐๐จ๐œ๐ญ๐ซ๐ข๐ง๐ž. ๐–๐ซ๐ข๐ญ๐ž ๐ข๐ญ ๐๐จ๐ฐ๐ง. ๐“๐ก๐ž ๐ˆ๐ซ๐š๐ง๐ข๐š๐ง ๐๐ž๐จ๐ฉ๐ฅ๐ž: ๐€ ๐๐ž๐ซ๐ฅ๐ข๐ง ๐–๐š๐ฅ๐ฅ ๐Œ๐จ๐ฆ๐ž๐ง๐ญ ๐ˆ๐ง ๐’๐ฅ๐จ๐ฐ ๐Œ๐จ๐ญ๐ข๐จ๐ง Hansonโ€™s most historically evocative passage is about the Iranian street. He notes that the regimeโ€™s ruling cliques are right now motivated by ๐˜ต๐˜ฉ๐˜ณ๐˜ฆ๐˜ฆ ๐˜ค๐˜ข๐˜ต๐˜ข๐˜ญ๐˜บ๐˜ด๐˜ต๐˜ด: they do not know who is in charge, they have watched 30-40-50 of their colleagues get killed, and they are fighting each other for the remains of power. But the fear underneath all of that is the one that matters: ๐ญ๐ก๐ž๐ฒ ๐š๐ซ๐ž ๐ญ๐ž๐ซ๐ซ๐ข๐Ÿ๐ข๐ž๐ ๐จ๐Ÿ ๐ญ๐ก๐ž๐ข๐ซ ๐จ๐ฐ๐ง ๐ฉ๐ž๐จ๐ฉ๐ฅ๐ž. โ€œ๐˜›๐˜ฉ๐˜ฆ ๐˜๐˜ณ๐˜ข๐˜ฏ๐˜ช๐˜ข๐˜ฏ ๐˜ฑ๐˜ฆ๐˜ฐ๐˜ฑ๐˜ญ๐˜ฆ ๐˜ข๐˜ณ๐˜ฆ ๐˜ด๐˜ช๐˜ค๐˜ฌ ๐˜ข๐˜ฏ๐˜ฅ ๐˜ต๐˜ช๐˜ณ๐˜ฆ๐˜ฅ. ๐˜‰๐˜ฆ๐˜ง๐˜ฐ๐˜ณ๐˜ฆ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ธ๐˜ข๐˜ณ ๐˜ฆ๐˜ท๐˜ฆ๐˜ฏ ๐˜ด๐˜ต๐˜ข๐˜ณ๐˜ต๐˜ฆ๐˜ฅ, ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฉ๐˜บ๐˜ฑ๐˜ฆ๐˜ณ๐˜ช๐˜ฏ๐˜ง๐˜ญ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ธ๐˜ข๐˜ด ๐˜ด๐˜ต๐˜ณ๐˜ข๐˜ฏ๐˜จ๐˜ญ๐˜ช๐˜ฏ๐˜จ ๐˜ต๐˜ฉ๐˜ฆ๐˜ฎ. ๐˜›๐˜ฉ๐˜ฆ๐˜บ ๐˜ค๐˜ฐ๐˜ถ๐˜ญ๐˜ฅ๐˜ฏ'๐˜ต ๐˜ข๐˜ง๐˜ง๐˜ฐ๐˜ณ๐˜ฅ ๐˜จ๐˜ข๐˜ด, ๐˜ต๐˜ฉ๐˜ฆ๐˜บ ๐˜ค๐˜ฐ๐˜ถ๐˜ญ๐˜ฅ๐˜ฏ'๐˜ต ๐˜ข๐˜ง๐˜ง๐˜ฐ๐˜ณ๐˜ฅ ๐˜ง๐˜ฐ๐˜ฐ๐˜ฅ, ๐˜ต๐˜ฉ๐˜ฆ๐˜บ ๐˜ค๐˜ข๐˜ฏ'๐˜ต ๐˜จ๐˜ฐ ๐˜ฐ๐˜ถ๐˜ต ๐˜ฐ๐˜ง ๐˜ต๐˜ฉ๐˜ฆ ๐˜ค๐˜ฐ๐˜ถ๐˜ฏ๐˜ต๐˜ณ๐˜บ. ๐˜ˆ๐˜ฏ๐˜ฅ ๐˜ช๐˜ตโ€™๐˜ด ๐˜ต๐˜ฆ๐˜ฏ ๐˜ต๐˜ช๐˜ฎ๐˜ฆ๐˜ด ๐˜ธ๐˜ฐ๐˜ณ๐˜ด๐˜ฆ ๐˜ฏ๐˜ฐ๐˜ธ.โ€ Hansonโ€™s historical parallel is devastating and correct. The Berlin Wall did not come down the day Reagan said ๐˜ต๐˜ฆ๐˜ข๐˜ณ ๐˜ฅ๐˜ฐ๐˜ธ๐˜ฏ ๐˜ต๐˜ฉ๐˜ช๐˜ด ๐˜ธ๐˜ข๐˜ญ๐˜ญ. It came down ๐ฐ๐ž๐ž๐ค๐ฌ ๐š๐ง๐ ๐ฆ๐จ๐ง๐ญ๐ก๐ฌ ๐ฅ๐š๐ญ๐ž๐ซ ๐ข๐ง ๐„๐š๐ฌ๐ญ๐ž๐ซ๐ง ๐„๐ฎ๐ซ๐จ๐ฉ๐ž, ๐š๐ง๐ ๐ญ๐ฐ๐จ ๐ฒ๐ž๐š๐ซ๐ฌ ๐ฅ๐š๐ญ๐ž๐ซ ๐ข๐ง ๐ญ๐ก๐ž ๐’๐จ๐ฏ๐ข๐ž๐ญ ๐”๐ง๐ข๐จ๐ง ๐ข๐ญ๐ฌ๐ž๐ฅ๐Ÿ. The collapse of the IRGCโ€™s street-level power over 90 million Iranians may take exactly that long. But it is coming, and the mullahs know it, and that is why they are freelancing contradictory statements on Twitter every 12 hours while their own Supreme Leader is dead and nobody has been elevated. ๐“๐ก๐ž ๐‚๐š๐ฏ๐ž๐š๐ญ ๐„๐ฏ๐ž๐ซ๐ฒ ๐๐ž๐ ๐จ๐ญ๐ข๐š๐ญ๐จ๐ซ ๐ˆ๐ง ๐–๐š๐ฌ๐ก๐ข๐ง๐ ๐ญ๐จ๐ง ๐๐ž๐ž๐๐ฌ ๐“๐จ ๐‘๐ž๐š๐ The closing minute of Hansonโ€™s commentary is the hinge of everything. He warns that the coming negotiation is a trap unless it is structured correctly. His words: โ€œ๐˜๐˜ง ๐˜บ๐˜ฐ๐˜ถ ๐˜ฃ๐˜ฆ๐˜ญ๐˜ช๐˜ฆ๐˜ท๐˜ฆ ๐˜ต๐˜ฉ๐˜ข๐˜ต ๐˜ต๐˜ฉ๐˜ฆ๐˜บ ๐˜ธ๐˜ช๐˜ญ๐˜ญ ๐˜ข๐˜ฃ๐˜ช๐˜ฅ๐˜ฆ ๐˜ฃ๐˜บ ๐˜ข ๐˜ฅ๐˜ฆ๐˜ฎ๐˜ข๐˜ฏ๐˜ฅ ๐˜ต๐˜ฉ๐˜ข๐˜ต ๐˜ธ๐˜ฆโ€™๐˜ท๐˜ฆ ๐˜จ๐˜ช๐˜ท๐˜ฆ๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ๐˜ฎ, ๐˜ฏ๐˜ฐ ๐˜ฏ๐˜ถ๐˜ค๐˜ญ๐˜ฆ๐˜ข๐˜ณ ๐˜ฎ๐˜ข๐˜ต๐˜ฆ๐˜ณ๐˜ช๐˜ข๐˜ญ ๐˜ง๐˜ฐ๐˜ณ 20 ๐˜บ๐˜ฆ๐˜ข๐˜ณ๐˜ด, ๐˜ธ๐˜ฉ๐˜ข๐˜ต๐˜ฆ๐˜ท๐˜ฆ๐˜ณ ๐˜ช๐˜ต ๐˜ช๐˜ด, ๐˜ต๐˜ฉ๐˜ฆ๐˜ฏ ๐˜บ๐˜ฐ๐˜ถ ๐˜ฉ๐˜ข๐˜ท๐˜ฆ ๐˜ต๐˜ฐ ๐˜ฃ๐˜ฆ๐˜ญ๐˜ช๐˜ฆ๐˜ท๐˜ฆ ๐˜ต๐˜ฉ๐˜ข๐˜ต ๐˜ต๐˜ฉ๐˜ฆ๐˜บ ๐˜ธ๐˜ช๐˜ญ๐˜ญ ๐˜ฏ๐˜ฆ๐˜ท๐˜ฆ๐˜ณ ๐˜ฃ๐˜ณ๐˜ฆ๐˜ข๐˜ฌ ๐˜ต๐˜ฉ๐˜ฆ๐˜ช๐˜ณ ๐˜ธ๐˜ฐ๐˜ณ๐˜ฅ. ๐˜ ๐˜ฅ๐˜ฐ๐˜ฏโ€™๐˜ต ๐˜ต๐˜ฉ๐˜ช๐˜ฏ๐˜ฌ ๐˜ต๐˜ฉ๐˜ฆ๐˜บโ€™๐˜ท๐˜ฆ ๐˜ฆ๐˜ท๐˜ฆ๐˜ณ ๐˜ฌ๐˜ฆ๐˜ฑ๐˜ต ๐˜ต๐˜ฉ๐˜ฆ๐˜ช๐˜ณ ๐˜ธ๐˜ฐ๐˜ณ๐˜ฅ.โ€ And then the hammer: โ€œ๐˜›๐˜ฉ๐˜ฆ๐˜ณ๐˜ฆ ๐˜ธ๐˜ช๐˜ญ๐˜ญ ๐˜ฃ๐˜ฆ ๐˜ข ๐˜ฑ๐˜ณ๐˜ฆ๐˜ด๐˜ช๐˜ฅ๐˜ฆ๐˜ฏ๐˜ต ๐˜ด๐˜ฐ๐˜ฎ๐˜ฆ๐˜ฅ๐˜ข๐˜บ ๐˜ญ๐˜ช๐˜ฌ๐˜ฆ ๐˜’๐˜ข๐˜ฎ๐˜ข๐˜ญ๐˜ข ๐˜๐˜ข๐˜ณ๐˜ณ๐˜ช๐˜ด, ๐˜Ž๐˜ข๐˜ท๐˜ช๐˜ฏ ๐˜•๐˜ฆ๐˜ธ๐˜ด๐˜ฐ๐˜ฎ, ๐˜—๐˜ฆ๐˜ต๐˜ฆ ๐˜‰๐˜ถ๐˜ต๐˜ต๐˜ช๐˜จ๐˜ช๐˜ฆ๐˜จ, ๐˜Š๐˜ฐ๐˜ณ๐˜บ ๐˜‰๐˜ฐ๐˜ฐ๐˜ฌ๐˜ฆ๐˜ณ, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ฑ๐˜ฆ๐˜ฐ๐˜ฑ๐˜ญ๐˜ฆ ๐˜ฐ๐˜ง ๐˜ต๐˜ฉ๐˜ข๐˜ต ๐˜ค๐˜ข๐˜ญ๐˜ช๐˜ฃ๐˜ฆ๐˜ณ ๐˜ข๐˜ฏ๐˜ฅ ๐˜ฎ๐˜ช๐˜ฏ๐˜ฅ๐˜ด๐˜ฆ๐˜ต, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ ๐˜ฅ๐˜ฐ๐˜ฏโ€™๐˜ต ๐˜ต๐˜ฉ๐˜ช๐˜ฏ๐˜ฌ ๐˜ต๐˜ฉ๐˜ฆ๐˜บ ๐˜ธ๐˜ช๐˜ญ๐˜ญ ๐˜ฆ๐˜ท๐˜ฆ๐˜ณ ๐˜ง๐˜ฐ๐˜ณ๐˜ค๐˜ฆ ๐˜ต๐˜ฉ๐˜ฆ๐˜ฎ ๐˜ต๐˜ฐ ๐˜ฉ๐˜ฐ๐˜ฏ๐˜ฐ๐˜ณ ๐˜ข๐˜ฏ๐˜บ ๐˜ฐ๐˜ง ๐˜ต๐˜ฉ๐˜ฆ๐˜ช๐˜ณ ๐˜ค๐˜ฐ๐˜ฎ๐˜ฎ๐˜ช๐˜ต๐˜ฎ๐˜ฆ๐˜ฏ๐˜ต๐˜ด.โ€ Translation: any JCPOA-style agreement that depends on the next Democratic president to enforce it is worthless on the day it is signed. The Iranian regime has never kept a deal. The Democratic Party has never enforced one. Therefore, Hanson concludes, ๐ฐ๐ž ๐ก๐š๐ ๐›๐ž๐ญ๐ญ๐ž๐ซ ๐ ๐ž๐ญ ๐ญ๐ก๐ž๐ฆ ๐ญ๐จ ๐ฌ๐ฎ๐ซ๐ซ๐ž๐ง๐๐ž๐ซ ๐ฎ๐ง๐œ๐จ๐ง๐๐ข๐ญ๐ข๐จ๐ง๐š๐ฅ๐ฅ๐ฒ ๐จ๐ซ ๐Ÿ๐š๐œ๐ž ๐ž๐œ๐จ๐ง๐จ๐ฆ๐ข๐œ ๐ซ๐ฎ๐ข๐ง, ๐ฐ๐ก๐ข๐œ๐ก ๐ฐ๐ข๐ฅ๐ฅ ๐ฎ๐ฌ๐ก๐ž๐ซ ๐ข๐ง ๐š ๐ซ๐ž๐ ๐ข๐ฆ๐ž ๐œ๐ก๐š๐ง๐ ๐ž. That is not a preference. That is a strategic necessity. Anything short of unconditional surrender or regime collapse just sets the clock ticking on the next war โ€” this time with a nuclear-armed ayatollah. ๐•๐ข๐œ๐ญ๐จ๐ซ ๐ƒ๐š๐ฏ๐ข๐ฌ ๐‡๐š๐ง๐ฌ๐จ๐ง ๐ข๐ฌ ๐ง๐จ๐ญ ๐š ๐œ๐š๐›๐ฅ๐ž ๐ง๐ž๐ฐ๐ฌ ๐ฉ๐ฎ๐ง๐๐ข๐ญ. ๐‡๐ž ๐ข๐ฌ ๐ญ๐ก๐ž ๐œ๐ฅ๐š๐ฌ๐ฌ๐ข๐œ๐š๐ฅ ๐ก๐ข๐ฌ๐ญ๐จ๐ซ๐ข๐š๐ง ๐ฐ๐ก๐จ ๐ฐ๐ซ๐จ๐ญ๐ž ๐ญ๐ก๐ž ๐›๐จ๐จ๐ค๐ฌ ๐ž๐ฏ๐ž๐ซ๐ฒ ๐ฐ๐š๐ซ ๐œ๐จ๐ฅ๐ฅ๐ž๐ ๐ž ๐ฎ๐ฌ๐ž๐ฌ. ๐‡๐ข๐ฌ ๐ฏ๐ž๐ซ๐๐ข๐œ๐ญ ๐ข๐ฌ ๐ญ๐ก๐š๐ญ ๐ƒ๐จ๐ง๐š๐ฅ๐ ๐“๐ซ๐ฎ๐ฆ๐ฉ ๐ญ๐จ๐จ๐ค ๐จ๐ง ๐š ๐œ๐จ๐ฎ๐ง๐ญ๐ซ๐ฒ ๐จ๐Ÿ ๐Ÿ—๐Ÿ‘ ๐ฆ๐ข๐ฅ๐ฅ๐ข๐จ๐ง ๐ฉ๐ž๐จ๐ฉ๐ฅ๐ž, ๐ฐ๐ข๐ญ๐ก ๐š ๐Ÿ’๐Ÿ”-๐ฒ๐ž๐š๐ซ ๐ซ๐ž๐ฉ๐ฎ๐ญ๐š๐ญ๐ข๐จ๐ง ๐Ÿ๐จ๐ซ ๐ญ๐ž๐ซ๐ซ๐ข๐Ÿ๐ฒ๐ข๐ง๐  ๐€๐ฆ๐ž๐ซ๐ข๐œ๐š๐ง ๐ฉ๐ซ๐ž๐ฌ๐ข๐๐ž๐ง๐ญ๐ฌ, ๐š๐ง๐ ๐๐ž๐ฌ๐ญ๐ซ๐จ๐ฒ๐ž๐ ๐ข๐ญ๐ฌ ๐š๐›๐ข๐ฅ๐ข๐ญ๐ฒ ๐ญ๐จ ๐ฆ๐š๐ค๐ž ๐ฐ๐š๐ซ ๐ข๐ง ๐Ÿ‘๐Ÿ“ ๐๐š๐ฒ๐ฌ ๐ฐ๐ข๐ญ๐ก๐จ๐ฎ๐ญ ๐ก๐ข๐ญ๐ญ๐ข๐ง๐  ๐š ๐ฌ๐ข๐ง๐ ๐ฅ๐ž ๐œ๐ข๐ฏ๐ข๐ฅ๐ข๐š๐ง ๐ฉ๐จ๐ฐ๐ž๐ซ ๐ฉ๐ฅ๐š๐ง๐ญ. ๐“๐ก๐š๐ญ ๐ข๐ฌ ๐ญ๐ก๐ž ๐Ÿ๐š๐ฌ๐ญ๐ž๐ฌ๐ญ, ๐ฆ๐จ๐ฌ๐ญ ๐ซ๐ž๐ฌ๐ญ๐ซ๐š๐ข๐ง๐ž๐, ๐ฆ๐จ๐ฌ๐ญ ๐๐ž๐œ๐ข๐ฌ๐ข๐ฏ๐ž ๐€๐ฆ๐ž๐ซ๐ข๐œ๐š๐ง ๐ฆ๐ข๐ฅ๐ข๐ญ๐š๐ซ๐ฒ ๐ฏ๐ข๐œ๐ญ๐จ๐ซ๐ฒ ๐ฌ๐ข๐ง๐œ๐ž ๐Ÿ๐Ÿ—๐Ÿ’๐Ÿ“. ๐“๐ก๐ž ๐ฉ๐ž๐จ๐ฉ๐ฅ๐ž ๐ฐ๐ก๐จ ๐œ๐š๐ฅ๐ฅ๐ž๐ ๐ข๐ญ ๐š ๐Ÿ๐จ๐ซ๐ž๐ฏ๐ž๐ซ ๐ฐ๐š๐ซ ๐ฐ๐ž๐ซ๐ž ๐ง๐จ๐ญ ๐ฐ๐ซ๐จ๐ง๐  ๐›๐ž๐œ๐š๐ฎ๐ฌ๐ž ๐จ๐Ÿ ๐›๐š๐ ๐ฅ๐ฎ๐œ๐ค. ๐“๐ก๐ž๐ฒ ๐ฐ๐ž๐ซ๐ž ๐ฐ๐ซ๐จ๐ง๐  ๐›๐ž๐œ๐š๐ฎ๐ฌ๐ž ๐ญ๐ก๐ž๐ฒ ๐ง๐ž๐ฏ๐ž๐ซ ๐จ๐ฉ๐ž๐ง๐ž๐ ๐š ๐ก๐ข๐ฌ๐ญ๐จ๐ซ๐ฒ ๐›๐จ๐จ๐ค. ๐‡๐š๐ง๐ฌ๐จ๐ง ๐ฃ๐ฎ๐ฌ๐ญ ๐จ๐ฉ๐ž๐ง๐ž๐ ๐จ๐ง๐ž ๐Ÿ๐จ๐ซ ๐ญ๐ก๐ž๐ฆ.

M.A. Rothman

89,400 gรถrรผntรผleme โ€ข 3 ay รถnce

The $AEGIS DApp portal is now open to all: ๐Ÿ›ก๏ธ At Aegis, we believe in empowering the blockchain full of security, transparency and innovation. The Aegis Dapp has been under development for several months prior to the launch of $AEGIS and with that we have been able to build what we believe has the potential to change how users go about their day to day security. We are thrilled to share our progress and truly exciting news with you all. ๐ŸŽฏ First things first, at Aegis, we want to make it clear that the value of what we seek to bring to security across the blockchain, comes from our big vision, our strong team, and our commitment to long-term goals. โ„น๏ธ Letโ€™s kick this off with some information that is constantly happening, which is behind the scenes. Our full team is dedicated to the opportunity that lays ahead of us with becoming the leading voice/name for security, grasping every aspect with innovation, hard work, passion and commitment to see this sector grow. Everyone is aware of how important security is, a heartwarming mention to Messari for including us on how they see this sector growing rapidly and pushing a 10 Billion evaluation. We take that recognition with full responsibility and gratitude as we've been working hard on some really powerful stuff that could change the game for our industry. If you read the title and report itself, Iโ€™m sure thatโ€™ll give you some insight to whatโ€™s coming, and to the vast extent of what you can expect Aegis to be working towards. โ€”> ๐Ÿค This comes from teaming up with others within this sector and coming up with new tech to projects driven by our community, within the pipeline you can be confident that what we are building will push the cryptocurrency industry as a whole into a better future, the magnitude to what Aegis brings will not stop until we can confidently say, โ€œNegative security reports across the blockchain are at an all time low, thousands of users are satisfied that Aegis is protecting them and their assets.โ€ We're sticking to our vision no matter what the market does or whatever else comes our way. We plan to build what we set out to and we will see to it that our ecosystem is met. We've been working on some pretty amazing products that will be available within our Dapp, letโ€™s go over what we offer: * AI Audits * Live Monitoring * Penetration Testing * Bug Bounties * Live Watchdog * Token analytics for everyday users, developers, teams, auditors, institutions, investors. โฌ‡๏ธ Letโ€™s break it down for you in some simple steps: AI AUDITS: We have trained our LLM models as AI AGENTS, these consist of 3 people ( AI AGENTS ) for the audits that are performed. - Audit - Reviewer - Judge Each one analyzes with a different personality, letโ€™s check what personalities our AI AGENTS consist of: 3 different perspective auditors. 1 - Fine-tuned model x amount reads the code and generates the audit. โœ… 2 - Model x amount reviews the code and fact checks thoroughly. โœ… 3 - Model x amount ranks the code based on the severity outcome. โœ… โŒš๏ธ Live Monitoring/Watchdog: The Live Monitoring/Watchdog system is designed to provide real-time surveillance of smart contracts, ensuring the detection and prevention of any potentially harmful transactions or malicious activities. Through the utilization of an AI Agent model, the system is trained to proactively identify and thwart suspicious behavior, thereby safeguarding the integrity of the smart contracts. Also, a paid sophisticated threat detection model is available for more intricate protocols and Dapps, offering an advanced level of protection against potential threats. This proactive approach is crucial in mitigating the risk of exploitation and ensuring the security of the smart contract ecosystem. ๐Ÿ–Š๏ธ Pen Testing: Our platform offers Pen Testing services to developers, providing a controlled environment for whitehat hackers to simulate attacks and identify vulnerabilities in smart contracts and protocols. In addition to human whitehat hackers, our AI Agents function as Red and Blue teams, actively engaging in simulated attacks to stress-test protocols and identify potential weaknesses. This comprehensive approach allows developers to proactively identify and address security issues, ultimately enhancing the robustness and resilience of their projects. ๐Ÿ•ท๏ธ Bug Bounties: Our Bug Bounty listing platform provides developers with the opportunity to list their protocols and offer bounties to white hat hackers for identifying vulnerabilities. By aggregating millions of bounties from various platforms and utilizing AI tools, we streamline the testing process, reducing up to 80% of the workload typically associated with security testing. This allows developers to efficiently identify and address potential vulnerabilities in their protocols, ultimately enhancing the overall security and resilience of their projects. ๐Ÿช™ And lot more token analytics features for regular users, this will give you the opportunity to explore our Dapp for yourself and have some fun diving into the security platform of the future! Iโ€™m sure youโ€™re excited to try it all out yourself, which is why we have some exciting news to bring to the #Guardians of the blockchain! But just before you continue the read and see the beans have been spilled, we have to take this opportunity to share with you that this large step to becoming a security leader is but only 20% of what we have revealed. This will be at the core of what Aegis stands for and hopes to achieve. The focus here is upon our Dapp, and in time we will slowly bring forward information/updates regarding segments of what makes Aegis a force to be reckoned with. Now that youโ€™re fired up and excited to all of the announcements to come, letโ€™s get to the news youโ€™ve been waiting for! ๐ŸŽ‰ Weโ€™re spilling the good news, and are happy to say we are now set for public release! The team at Aegis are overwhelmed with the development, support from teams, community, partners and more on what we believe to be an institutional-grade product. But the fun doesnโ€™t stop there, this marks the start of what we aim to become, as it will take time and cycles to become better and better. Constant advancements will be set in place to attain the goal of achieving blockchain security. A statement from our CEO- Brian Hunt: โ€œI can confirm from the security conferences I attended with Centralized security firms Peckshield, Hacken, Certik, BlockSec presentations, they are trying to achieve something similar and it will take them years. Decentralized AI for Security!โ€ This initial drop of our dapp will be to get users signed up to gain access, in which weโ€™ll whitelist users to get the ball rolling. ๐Ÿ“ฃ To end this segment, letโ€™s get the party started with the long awaited Aegis Ai Security Dapp and sign up now!

AEGIS AI

127,936 gรถrรผntรผleme โ€ข 2 yฤฑl รถnce

CANCEL Your Weekend Plans, and Learn Claude Code Today. $5,000/month. $10,000/month. $20,000/month. People are building entire apps and charging clients thousands using Claude Code. You're still Googling 'how to center a div.' While you're binge-watching a show you won't remember next week, a 19 year old with zero coding experience just built a $5,000 SaaS product in one afternoon using the tool I'm about to break down. Same laptop. Same internet. Same 24 hours. He has Claude Code. You have Netflix. That's the only difference. This YouTube video is a goldmine. Full Claude Code tutorial. Beginner to pro. Every feature. Every setup step. Every best practice. Zero prior knowledge needed. Save it. Watch it tonight. Not tomorrow. Tonight. Save this post. This is your complete Claude Code roadmap. Lose it and you lose the next 12 months of income. Follow Himanshu Kumar so you don't miss the breakdowns for each feature. โ†“ 1. Understand What Claude Code Actually Is. You think Claude Code is just another chatbot. It's not. And that misunderstanding is why you're broke. ChatGPT gives you text. Claude Code gives you software. It runs in your terminal. It reads your entire codebase. It writes files directly to your project. It runs commands on your machine. It debugs errors autonomously. It builds features end to end. You're not chatting. You're deploying a developer. One that works 24/7. Never asks for a raise. Never calls in sick. Never pushes broken code at 5 PM on a Friday. People are charging clients $5,000-$10,000 for apps they built with Claude Code in 3 hours. And you didn't even know this tool existed because you're still asking ChatGPT to write you a to-do list. The gap between you and people making money with AI isn't intelligence. It's awareness. Now you're aware. Save this post. Follow Himanshu Kumar for the complete breakdown of every Claude Code feature. โ†“ 2. Set Up Claude Code Properly. Most people quit here. "It's too complicated." "I don't know terminal." "I'll set it up later." Later never comes. And "complicated" means "I watched for 30 seconds and gave up." The setup takes 10 minutes. Install Node.js. Install Claude Code via npm. Authenticate your account. Open your terminal. Done. 10 minutes. You spent longer this morning deciding what to have for breakfast. The video walks through every single click. Every command. Every screen. Assuming you know absolutely nothing. If you can download an app on your phone, you can set up Claude Code. It's the same level of difficulty. But you'll still tell yourself it's "too technical" because that excuse is more comfortable than admitting you're just scared to try something new. This is the setup that everything else builds on. Skip it and nothing works. โ†“ 3. Use the Desktop App. You don't even need to live in the terminal if you don't want to. Claude Code has a desktop app. Clean interface. Visual feedback. Everything you need without touching command line. But here's the thing most people don't know: The desktop app isn't just a pretty wrapper. It lets you manage projects visually. See file changes in real time. Switch between projects instantly. The people making money with Claude Code use the desktop app for client projects because it's faster to manage multiple builds simultaneously. You're still opening 14 browser tabs to organize one project. They open one app and everything's there. Efficiency isn't a personality trait. It's a tool choice. Save this post. Follow Himanshu Kumar for the desktop app workflow that handles 5 client projects at once. โ†“ 4. Install the Right Dependencies. This is where beginners silently fail and blame the tool. Claude Code needs certain dependencies installed to work properly. Miss one and everything breaks. Then you go on Twitter and say "Claude Code doesn't work." It works fine. You just didn't read the setup guide. The video covers every dependency you need. What to install. How to install it. How to verify it's working. No guessing. No Stack Overflow rabbit holes at midnight. No "why isn't this working" for 3 hours. Watch the dependency section once. Follow every step. Never deal with setup issues again. You spent more time last week troubleshooting a printer than this takes. โ†“ 5. Work Inside Your Code Editor. Claude Code integrates directly with your code editor. VS Code. Cursor. Whatever you use. It's not a separate window you alt-tab between. It's right there. In your workflow. You type a request. Claude writes the code. The code appears in your editor. You review it. Accept it. Done. No copy pasting between windows. No reformatting code that got mangled in transit. No "which version was the right one." It's like pair programming with someone who never gets distracted, never argues about naming conventions, and actually writes code that works on the first try. Your current coding process is: Google the problem, read 5 answers on Stack Overflow, copy the wrong one, debug for an hour, find the right one, paste it in, break something else, repeat. Claude Code's process is: describe what you want, get working code, move on with your life. Same hour. One method produces working software. The other produces frustration and a browser history full of Stack Overflow tabs. Stop coding the hard way. Save this post. Follow Himanshu Kumar for code editor setup guides and integration tips. โ†“ 6. Master Basic Usage. Most people learn 5% of a tool and say they "know" it. You "know" Photoshop because you can crop an image. You "know" Excel because you can sum a column. You "know" Claude Code because you asked it one question. Basic usage means: How to give Claude Code context about your project. How to ask for changes to existing code. How to generate new files and features. How to review what Claude produces. How to iterate when the output isn't perfect. These basics are the foundation of everything. Skip them and every advanced feature feels confusing. Master them and every advanced feature feels obvious. The video breaks down each one with real examples. Not theory. Actual usage on actual projects. You've been using AI tools at 5% capacity and wondering why your results are 5% of what others get. Save this post. Follow Himanshu Kumar for daily Claude Code usage tips. โ†“ 7. Learn Every Command. Claude Code has commands that most users never discover. Because most users type one message and expect magic. That's not how professionals use it. Professionals use specific commands that tell Claude Code exactly what to do, how to do it, and what constraints to follow. The difference between a beginner and someone making $10K/month with Claude Code is knowing which command to use and when. The video walks through every single one. Not just what they do. But when to use each one. And why one command is better than another for specific situations. You've been using Claude Code like a hammer. These commands turn it into a full toolbox. Stop treating a power tool like a blunt instrument. Save this post. Follow Himanshu Kumar for the command cheat sheet I use daily. โ†“ 8. Understand Modes and Shortcuts. Speed matters. The person who builds an app in 2 hours charges $5,000. The person who builds the same app in 2 days charges $2,000. Same app. Same quality. Different speed. Different income. Claude Code has modes that change how it operates. And shortcuts that cut your workflow time in half. Most people don't know either exists. They use Claude Code in default mode for everything. Like driving a car in first gear on the highway. Technically it works. But everyone is passing you. The video shows you every mode. Every shortcut. Every time-saving trick that separates the people charging $2,000 per project from the people charging $10,000. Speed is money. Literally. Save this post. Follow Himanshu Kumar for the shortcuts that cut my build time by 60%. โ†“ 9. Write a Proper Planning Prompt. This is the section that separates amateurs from professionals. And it's the section most people skip. A planning prompt tells Claude Code what you're building before you start building it. Architecture. File structure. Technologies. Features. Constraints. Edge cases. Without a planning prompt, Claude Code guesses. And guessing produces garbage. With a planning prompt, Claude Code executes a clear plan. And clear plans produce working software. The video shows you exactly how to write a planning prompt that makes Claude Code produce professional-grade output on the first try. "But I just want to start coding." That's why your code breaks every time. That's why you restart projects 4 times. That's why nothing you build ever gets finished. Because you refuse to plan. A 5-minute planning prompt saves you 5 hours of debugging. But you'd rather skip the 5 minutes and suffer through the 5 hours because patience isn't your thing. And that's exactly why you're not making money. Planning is the most underpaid skill in coding. And the most overpaid when you master it. Save this post. Follow Himanshu Kumar for the planning prompt templates I use for every client project. โ†“ 10. Choose the Right Model. Claude Code lets you select different AI models. Not all models are the same. Not all tasks need the same model. Using the most powerful model for a simple task wastes credits. Using a basic model for a complex task wastes time. The video explains: Which model to use for quick fixes. Which model to use for complex architecture. Which model to use for debugging. Which model to use for code generation. Most people pick one model and use it for everything. That's like using a sledgehammer to hang a picture frame. Model selection is strategy. And strategy is money. The people making $10K/month with Claude Code are strategic about every credit they spend. You're burning through credits because you use the most expensive model to write a hello world. โ†“ 11. Use Git and Version Control. If you're not using version control, you're one mistake away from losing everything. Claude Code integrates with Git. Every change tracked. Every version saved. Every mistake reversible. Without Git: Claude makes a change. It breaks something. You can't undo it. You start over. 3 hours wasted. With Git: Claude makes a change. It breaks something. You roll back in 5 seconds. Keep working. Version control isn't optional. It's insurance. And the people not using it are the same people who say "I lost my entire project" like it's something that just happens. It doesn't just happen. It happens because you didn't set up Git. The video walks through the entire Git integration. Save this post. Follow Himanshu Kumar for the Git workflow that's saved every project I've ever built. โ†“ 12. Set Up Claude.MD and Memory. This is the feature that makes Claude Code feel like a real team member instead of a stranger you explain everything to every time. ClaudeMD is a memory file. You tell Claude Code about your project once. It remembers forever. Coding style preferences. Project architecture decisions. Technology stack. File naming conventions. Business logic rules. Without ClaudeMD: Every new conversation starts from zero. You explain the same things repeatedly. Output is inconsistent. With ClaudeMD: Claude knows your project. Claude follows your rules. Claude produces consistent, professional code. The difference between a sloppy freelancer and a reliable agency is consistency. Claude. MD gives you consistency without the agency overhead. Most people don't set this up and wonder why Claude Code gives different answers every time. โ†“ 13. Automate with Tasks. This is where Claude Code stops being a tool and starts being an employee. Tasks let you define repeating workflows. "Every time I push code, run tests." "Every time I create a new file, add boilerplate." "Every time I start a session, check for errors." Automated. Hands-free. Consistent. You're doing these things manually every single day. The same checks. The same steps. The same routine. Tasks do them automatically. So you can focus on the work that actually makes money. Every manual task you automate is time you get back. And time is the only thing you can never make more of. Save this post. Follow Himanshu Kumar for the task automation templates that run my entire workflow. โ†“ 14. Explore Features Most People Never Touch. The video covers features that 95% of Claude Code users don't know exist. Because they watched a 3-minute TikTok about Claude Code and think they're experts now. They're not. They're using 5% of a tool that can do everything. The full tutorial goes deep into features that most tutorials skip because they're "too advanced." They're not too advanced. They're too valuable for lazy creators to bother explaining. This video explains all of them. Clearly. For beginners. The 5% of features you don't know about are the 5% that make people rich. โ†“ Let's zoom out. I just broke down 14 sections of Claude Code. Setup and installation. Desktop app. Dependencies. Code editor integration. Basic usage. Commands. Modes and shortcuts. Planning prompts. Model selection. Git and version control. Memory and Claude. MD. Tasks and automation. Advanced features. All in one video. All free. All beginner friendly. The person who masters even half of these in the next 2 weeks will be in the top 1% of Claude Code users. The top 1% of Claude Code users are the ones charging $5,000-$10,000 per project and building them in a single afternoon. Everyone else is asking ChatGPT to fix their resume. Same tools. Same access. Completely different outcomes. Because one person treats AI like a toy. And the other treats it like a business. โ†“ Here's the hard truth nobody wants to hear. You don't have a talent problem. You don't have an intelligence problem. You don't have a resources problem. You have an action problem. Everything I just listed has a free tutorial right here in the attached video. 33 minutes. That's it. 33 minutes to learn the tool that people are using to build $5,000-$20,000/month businesses. You spent more time today scrolling Twitter than it takes to watch this video. You spent more time this week watching Netflix than it takes to master Claude Code basics. You spent more time this month doing nothing than it would take to completely change your income. The information is free. The tool is accessible. The opportunity is here. The only thing missing is you caring enough to start. โ†“ CANCEL your plans this week. This isn't optional anymore. The people learning Claude Code right now will be building apps for the people who didn't learn it. That's not a prediction. That's already happening. Companies are replacing $150/hour developers with one person and Claude Code. If you code: learn Claude Code or become half as valuable by next year. If you don't code: learn Claude Code or miss the biggest opportunity to start earning from tech without a CS degree. There's no path forward that doesn't include AI coding tools. None. You have one window. Right now. This week. โ†“ Here's your action plan for the next 7 days: Day 1: Watch the full video. Install Claude Code. Set up dependencies. Day 2: Learn basic usage. Try 5 different commands. Day 3: Write your first planning prompt. Build a small project. Day 4: Set up Claude. MD. Configure your memory file. Day 5: Master modes and shortcuts. Build a second project faster. Day 6: Set up Git integration. Automate with tasks. Day 7: Build something real. A tool, an app, a website. Ship it. 7 days. One tool. One completely different skill set. One completely different income potential. Or 7 more days of scrolling Twitter watching other people build things while you "plan to start." Your call. โ†“ This is the most important video you'll watch this year. 33 minutes. Complete Claude Code mastery. From zero to building real projects. Save this post. Come back to it every single day this week. Check off each section as you complete it. Follow Himanshu Kumar for daily Claude Code breakdowns, advanced tutorials, and the exact workflows that are turning beginners into $10K/month builders. The only thing between you and $10K/month with Claude Code is this video and 7 days. Don't waste them. You Must Follow me Himanshu Kumar, so i can send you DM.

Himanshu Kumar

101,376 gรถrรผntรผleme โ€ข 3 ay รถnce

CANCEL Your Weekend Plans, & Learn Claude Code Today. This Claude Code teaches more about vibe-coding in 30 mins than most tutorials do in hours. Save this, it'll change how you build forever People are building entire apps and charging clients $5,000 to $20,000 using Claude Code. This Claude Code video is a goldmine. Full Claude Code tutorial. Beginner to pro. Every feature. Every setup step. Every best practice. Zero prior knowledge needed. Save it. Watch it tonight. Not tomorrow. Tonight. Follow Himanshu Kumar so you don't miss the breakdowns for each feature. This is your complete Claude Code roadmap. Lose it and you lose the next 12 months of income. โ†“ 1. Understand What Claude Code Actually Is. You think Claude Code is just another chatbot. It's not. And that misunderstanding is why you're broke. ChatGPT gives you text. Claude Code gives you software. It runs in your terminal. It reads your entire codebase. It writes files directly to your project. It runs commands on your machine. It debugs errors autonomously. It builds features end to end. You're not chatting. You're deploying a developer. One that works 24/7. Never asks for a raise. Never calls in sick. Never pushes broken code at 5 PM on a Friday. People are charging clients $5,000-$10,000 for apps they built with Claude Code in 3 hours. And you didn't even know this tool existed because you're still asking ChatGPT to write you a to-do list. The gap between you and people making money with AI isn't intelligence. It's awareness. Now you're aware. Save this post. Follow Himanshu Kumar for the complete breakdown of every Claude Code feature. โ†“ 2. Set Up Claude Code Properly. Most people quit here. "It's too complicated." "I don't know terminal." "I'll set it up later." Later never comes. And "complicated" means "I watched for 30 seconds and gave up." The setup takes 10 minutes. Install Node.js. Install Claude Code via npm. Authenticate your account. Open your terminal. Done. 10 minutes. You spent longer this morning deciding what to have for breakfast. The video walks through every single click. Every command. Every screen. Assuming you know absolutely nothing. If you can download an app on your phone, you can set up Claude Code. It's the same level of difficulty. But you'll still tell yourself it's "too technical" because that excuse is more comfortable than admitting you're just scared to try something new. This is the setup that everything else builds on. Skip it and nothing works. โ†“ 3. Use the Desktop App. You don't even need to live in the terminal if you don't want to. Claude Code has a desktop app. Clean interface. Visual feedback. Everything you need without touching command line. But here's the thing most people don't know: The desktop app isn't just a pretty wrapper. It lets you manage projects visually. See file changes in real time. Switch between projects instantly. The people making money with Claude Code use the desktop app for client projects because it's faster to manage multiple builds simultaneously. You're still opening 14 browser tabs to organize one project. They open one app and everything's there. Efficiency isn't a personality trait. It's a tool choice. Save this post. Follow Himanshu Kumar for the desktop app workflow that handles 5 client projects at once. โ†“ 4. Install the Right Dependencies. This is where beginners silently fail and blame the tool. Claude Code needs certain dependencies installed to work properly. Miss one and everything breaks. Then you go on Twitter and say "Claude Code doesn't work." It works fine. You just didn't read the setup guide. The video covers every dependency you need. What to install. How to install it. How to verify it's working. No guessing. No Stack Overflow rabbit holes at midnight. No "why isn't this working" for 3 hours. Watch the dependency section once. Follow every step. Never deal with setup issues again. You spent more time last week troubleshooting a printer than this takes. โ†“ 5. Work Inside Your Code Editor. Claude Code integrates directly with your code editor. VS Code. Cursor. Whatever you use. It's not a separate window you alt-tab between. It's right there. In your workflow. You type a request. Claude writes the code. The code appears in your editor. You review it. Accept it. Done. No copy pasting between windows. No reformatting code that got mangled in transit. No "which version was the right one." It's like pair programming with someone who never gets distracted, never argues about naming conventions, and actually writes code that works on the first try. Your current coding process is: Google the problem, read 5 answers on Stack Overflow, copy the wrong one, debug for an hour, find the right one, paste it in, break something else, repeat. Claude Code's process is: describe what you want, get working code, move on with your life. Same hour. One method produces working software. The other produces frustration and a browser history full of Stack Overflow tabs. Stop coding the hard way. Save this post. Follow Himanshu Kumar for code editor setup guides and integration tips. โ†“ 6. Master Basic Usage. Most people learn 5% of a tool and say they "know" it. You "know" Photoshop because you can crop an image. You "know" Excel because you can sum a column. You "know" Claude Code because you asked it one question. Basic usage means: How to give Claude Code context about your project. How to ask for changes to existing code. How to generate new files and features. How to review what Claude produces. How to iterate when the output isn't perfect. These basics are the foundation of everything. Skip them and every advanced feature feels confusing. Master them and every advanced feature feels obvious. The video breaks down each one with real examples. Not theory. Actual usage on actual projects. You've been using AI tools at 5% capacity and wondering why your results are 5% of what others get. Save this post. Follow Himanshu Kumar for daily Claude Code usage tips. โ†“ 7. Learn Every Command. Claude Code has commands that most users never discover. Because most users type one message and expect magic. That's not how professionals use it. Professionals use specific commands that tell Claude Code exactly what to do, how to do it, and what constraints to follow. The difference between a beginner and someone making $10K/month with Claude Code is knowing which command to use and when. The video walks through every single one. Not just what they do. But when to use each one. And why one command is better than another for specific situations. You've been using Claude Code like a hammer. These commands turn it into a full toolbox. Stop treating a power tool like a blunt instrument. Save this post. Follow Himanshu Kumar for the command cheat sheet I use daily. โ†“ 8. Understand Modes and Shortcuts. Speed matters. The person who builds an app in 2 hours charges $5,000. The person who builds the same app in 2 days charges $2,000. Same app. Same quality. Different speed. Different income. Claude Code has modes that change how it operates. And shortcuts that cut your workflow time in half. Most people don't know either exists. They use Claude Code in default mode for everything. Like driving a car in first gear on the highway. Technically it works. But everyone is passing you. The video shows you every mode. Every shortcut. Every time-saving trick that separates the people charging $2,000 per project from the people charging $10,000. Speed is money. Literally. Save this post. Follow Himanshu Kumar for the shortcuts that cut my build time by 60%. โ†“ 9. Write a Proper Planning Prompt. This is the section that separates amateurs from professionals. And it's the section most people skip. A planning prompt tells Claude Code what you're building before you start building it. Architecture. File structure. Technologies. Features. Constraints. Edge cases. Without a planning prompt, Claude Code guesses. And guessing produces garbage. With a planning prompt, Claude Code executes a clear plan. And clear plans produce working software. The video shows you exactly how to write a planning prompt that makes Claude Code produce professional-grade output on the first try. "But I just want to start coding." That's why your code breaks every time. That's why you restart projects 4 times. That's why nothing you build ever gets finished. Because you refuse to plan. A 5-minute planning prompt saves you 5 hours of debugging. But you'd rather skip the 5 minutes and suffer through the 5 hours because patience isn't your thing. And that's exactly why you're not making money. Planning is the most underpaid skill in coding. And the most overpaid when you master it. Save this post. Follow Himanshu Kumar for the planning prompt templates I use for every client project. โ†“ 10. Choose the Right Model. Claude Code lets you select different AI models. Not all models are the same. Not all tasks need the same model. Using the most powerful model for a simple task wastes credits. Using a basic model for a complex task wastes time. The video explains: Which model to use for quick fixes. Which model to use for complex architecture. Which model to use for debugging. Which model to use for code generation. Most people pick one model and use it for everything. That's like using a sledgehammer to hang a picture frame. Model selection is strategy. And strategy is money. The people making $10K/month with Claude Code are strategic about every credit they spend. You're burning through credits because you use the most expensive model to write a hello world. โ†“ 11. Use Git and Version Control. If you're not using version control, you're one mistake away from losing everything. Claude Code integrates with Git. Every change tracked. Every version saved. Every mistake reversible. Without Git: Claude makes a change. It breaks something. You can't undo it. You start over. 3 hours wasted. With Git: Claude makes a change. It breaks something. You roll back in 5 seconds. Keep working. Version control isn't optional. It's insurance. And the people not using it are the same people who say "I lost my entire project" like it's something that just happens. It doesn't just happen. It happens because you didn't set up Git. The video walks through the entire Git integration. Save this post. Follow Himanshu Kumar for the Git workflow that's saved every project I've ever built. โ†“ 12. Set Up Claude MD and Memory. This is the feature that makes Claude Code feel like a real team member instead of a stranger you explain everything to every time. ClaudeMD is a memory file. You tell Claude Code about your project once. It remembers forever. Coding style preferences. Project architecture decisions. Technology stack. File naming conventions. Business logic rules. Without ClaudeMD: Every new conversation starts from zero. You explain the same things repeatedly. Output is inconsistent. With ClaudeMD: Claude knows your project. Claude follows your rules. Claude produces consistent, professional code. The difference between a sloppy freelancer and a reliable agency is consistency. Claude. MD gives you consistency without the agency overhead. Most people don't set this up and wonder why Claude Code gives different answers every time. โ†“ 13. Automate with Tasks. This is where Claude Code stops being a tool and starts being an employee. Tasks let you define repeating workflows. "Every time I push code, run tests." "Every time I create a new file, add boilerplate." "Every time I start a session, check for errors." Automated. Hands-free. Consistent. You're doing these things manually every single day. The same checks. The same steps. The same routine. Tasks do them automatically. So you can focus on the work that actually makes money. Every manual task you automate is time you get back. And time is the only thing you can never make more of. Save this post. Follow Himanshu Kumar for the task automation templates that run my entire workflow. โ†“ 14. Explore Features Most People Never Touch. The video covers features that 95% of Claude Code users don't know exist. Because they watched a 3-minute TikTok about Claude Code and think they're experts now. They're not. They're using 5% of a tool that can do everything. The full tutorial goes deep into features that most tutorials skip because they're "too advanced." They're not too advanced. They're too valuable for lazy creators to bother explaining. This video explains all of them. Clearly. For beginners. The 5% of features you don't know about are the 5% that make people rich. โ†“ Let's zoom out. I just broke down 14 sections of Claude Code. Setup and installation. Desktop app. Dependencies. Code editor integration. Basic usage. Commands. Modes and shortcuts. Planning prompts. Model selection. Git and version control. Memory and Claude. MD. Tasks and automation. Advanced features. All in one video. All free. All beginner friendly. The person who masters even half of these in the next 2 weeks will be in the top 1% of Claude Code users. The top 1% of Claude Code users are the ones charging $5,000-$10,000 per project and building them in a single afternoon. Everyone else is asking ChatGPT to fix their resume. Same tools. Same access. Completely different outcomes. Because one person treats AI like a toy. And the other treats it like a business. โ†“ Here's the hard truth nobody wants to hear. You don't have a talent problem. You don't have an intelligence problem. You don't have a resources problem. You have an action problem. Everything I just listed has a free tutorial right here in the attached video. 33 minutes. That's it. 33 minutes to learn the tool that people are using to build $5,000-$20,000/month businesses. You spent more time today scrolling Twitter than it takes to watch this video. You spent more time this week watching Netflix than it takes to master Claude Code basics. You spent more time this month doing nothing than it would take to completely change your income. The information is free. The tool is accessible. The opportunity is here. The only thing missing is you caring enough to start. โ†“ CANCEL your plans this week. This isn't optional anymore. The people learning Claude Code right now will be building apps for the people who didn't learn it. That's not a prediction. That's already happening. Companies are replacing $150/hour developers with one person and Claude Code. If you code: learn Claude Code or become half as valuable by next year. If you don't code: learn Claude Code or miss the biggest opportunity to start earning from tech without a CS degree. There's no path forward that doesn't include AI coding tools. None. You have one window. Right now. This week. โ†“ Here's your action plan for the next 7 days: Day 1: Watch the full video. Install Claude Code. Set up dependencies. Day 2: Learn basic usage. Try 5 different commands. Day 3: Write your first planning prompt. Build a small project. Day 4: Set up Claude. MD. Configure your memory file. Day 5: Master modes and shortcuts. Build a second project faster. Day 6: Set up Git integration. Automate with tasks. Day 7: Build something real. A tool, an app, a website. Ship it. 7 days. One tool. One completely different skill set. One completely different income potential. Or 7 more days of scrolling Twitter watching other people build things while you "plan to start." Your call. โ†“ This is the most important video you'll watch this year. 33 minutes. Complete Claude Code mastery. From zero to building real projects. Save this post. Come back to it every single day this week. Check off each section as you complete it. Follow Himanshu Kumarfor daily Claude Code breakdowns, advanced tutorials, and the exact workflows that are turning beginners into $10K/month builders. The only thing between you and $10K/month with Claude Code is this video and 7 days. Don't waste them. You Must Follow me Himanshu Kumar, so i can send you DM.

Himanshu Kumar

85,668 gรถrรผntรผleme โ€ข 2 ay รถnce

The fight between Anthropic and the DoW is a warning shot. Right now, LLMs are probably not being used in mission critical ways. But within 20 years, 99% of the workforce in the military, the government, and the private sector will be AIs. This includes the soldiers (by which I mean the robot armies), the superhumanly intelligent advisors and engineers, the police, you name it. Our future civilization will run on AI labor. And as much as the governmentโ€™s actions here piss me off, in a way Iโ€™m glad this episode happened - because it gives us the opportunity to think through some extremely important questions about who this future workforce will be accountable and aligned to, and who gets to determine that. What Hegseth should have done Obviously the DoW has the right to refuse to use Anthropicโ€™s models because of these redlines. In fact, I think the governmentโ€™s case had they done so would be very reasonable, especially given the ambiguity of concepts like autonomous weapons or mass surveillance. Honestly, for this reason, if I was the Defense Secretary, I would probably actually refuse to do this deal with Anthropic. Imagine if in the future, thereโ€™s a Democratic administration, and Elon Musk is negotiating some SpaceX contract to give the military access to Starlink. And suppose if Elon said, โ€œI reserve the right to cancel this contract if I determine that youโ€™re using Starlink technology to wage a war not authorized by Congress.โ€ On the face of it, that language seems reasonable - but as the military, you simply canโ€™t give a private company a kill switch on technology your operations have come to rely on, especially if you have an an acrimonious and low trust relationship with said contractor - as in fact Anthropic has with the current administration. If the government had just said, โ€œHey weโ€™re not gonna do business with you,โ€ that would have been fine, and I would not have felt the need to write this blog post. Instead the government has threatened to destroy Anthropic as a private business, because Anthropic refuses to sell to the government on terms the government commands. If upheld, this Supply Chain Restriction would mean that Amazon and Google and Nvidia and Palantir would need to ensure Claude isn't touching any of their Pentagon work. Anthropic would be able to survive this designation today. But given the way AI is going, eventually AI is not gonna be some party trick addendum to these contractorsโ€™ products that can just be turned off. It'll be woven into how every product is built, maintained, and operated. For example, the code for the AWS services that the DoW uses will be written by Claude - is that a supply chain risk? In a world with ubiquitous and powerful AI, it's actually not clear to me that these big tech companies will be able to cordon off the use of Claude in order to keep working with the Pentagon. And that raises a question the Department of War probably hasn't thought through. If AI really is that pervasive and powerful, then when forced to choose between their AI provider and a DoW contract that represents a tiny fraction of their revenue, wouldnโ€™t most tech companies drop the government, not the AI? So what's the Pentagon's plan โ€” to coerce and threaten to destroy every single company that won't give them what they want on exactly their terms? The whole background of this AI conversation is that weโ€™re in a race with China, and we have to win. But what is the reason we want America to win the AI race? Itโ€™s because we want to make sure free open societies can defend themselves. We don't want the winner of the AI race to be a government which operates on the principle that there is no such thing as a truly private company or a private citizen. And that if the state wants you to provide them with a service on terms you find morally objectionable, you are not allowed to refuse. And if you do refuse, the government will try to destroy your ability to do business. Are we racing to beat the CCP in AI just so that we can adopt the most ghoulish parts of their system? Now, people will say, "Oh, well, our government is democratically elected, so it's not the same thing if they tell you what you must do." I refuse to accept this idea that if a democratically elected leader hypothetically wants to do mass surveillance on his citizens or wants to violate their rights or punish them for political reasons, that not only is that okay, but that you have a duty to help him. The overhangs of tyranny Mass surveillance is, at least in certain forms, legal. It just has been impractical so far. Under current law, you have no Fourth Amendment protection over data you share with a third party, including your bank, your phone carrier, your ISP, and your email provider. The government reserves the right to purchase and obtain and read this data in bulk without a warrant. What's been missing is the ability to actually do anything with all of this data โ€” no agency has the manpower to monitor every camera feed, cross-reference every transaction, or read every message. But that bottleneck goes away with AI. There are 100 million CCTV cameras in America. You can get pretty good open source multimodal models for 10 cents per million input tokens. So if you process a frame every ten seconds, and each frame is 1,000 tokens, youโ€™re looking at a yearly cost of about 30 billion dollars to process every single camera in America. And remember that a given level of AI ability gets 10x cheaper year over year - so a year from now itโ€™ll cost 3 billion, and then a year after 300 million, and by 2030, it might be cheaper for the government to be able to understand what is going on in every single nook and cranny of this country than it is to remodel to the White House. Once the technical capacity for mass surveillance and political suppression exists, the only thing standing between us and an authoritarian surveillance state is the political expectation that this is not something we do here. And this is why I think what Anthropic did here is so valuable and commendable, because it is helping set that norm and precedent. AI structurally favors mass surveillance What weโ€™re learning from this episode is that the government actually has way more leverage over private companies than we realized. Even if this supply chain restriction is backtracked (which prediction markets currently give it a 81% chance of happening), the President has so many different ways in which he can make your life difficult if youโ€™re a company that is resisting him. The federal government controls permitting for new power generation, which is needed for datacenters. It oversees antitrust enforcement. The federal government has contracts with all the other big tech companies whom Anthropic needs to partner with for chips and for funding - and they could make it an unspoken condition for such contracts that those companies can no longer do business with Anthropic. People have proposed that the real problem here is that thereโ€™s only 3 leading AI companies. This creates a clear and narrow target for the government to apply leverage on in order to get what they want out of this technology. But if thereโ€™s wide diffusion, then from the governmentโ€™s perspective, the situation is even easier. Maybe the best models of early 2027 (if you engineered the safeguards out) - the Claude 6 and Gemini 5 - will be capable of enabling mass surveillance. But by late 2027, and certainly by 2028, there will be open source models that do the same thing. So in 2028, the government can just say, โ€œOh Anthropic, Google, OpenAI, youโ€™re drawing a line in the sand? No issue - Iโ€™ll just run some open source model that might not be at the frontier, but is definitely smart enough to note-take a camera feed.โ€ The more fundamental problem is just that even if the three leading companies draw lines in the sand, and are even willing to get destroyed in order to preserve those lines, it doesnโ€™t really change the fact that the technology itself is just a big boon to mass surveillance and control over the population. Then the question is, what do we do about it? Honestly, I donโ€™t have an answer. You'd hope there's some symmetric property of the technology โ€” some way we as citizens can use AI to check government power as effectively as the government can use AI to monitor and control its population. But realistically, I just donโ€™t think thatโ€™s how itโ€™s going to shake out. You can think of AI as giving everybody more leverage on whatever assets and authority they currently have. And the government is already starting with a monopoly of violence. Which they can now supercharge with extremely obedient employees that will not question the government's orders. Alignment - to whom? And this gets us to the issue of alignment. What I have just described to you - an army of extremely obedient employees - is what it would look like if alignment succeeded - that is, we figured out at a technical level how to get AI systems to follow someoneโ€™s intentions. And the reason it sounds scary when I put it in terms of mass surveillance or robot armies is that there is a very important question at the heart of alignment which we just havenโ€™t discussed much as a society. Because up till now, AIs were just capable enough to make the question relevant: to whom or what should the AIs be aligned? In what situations should the AI defer to the end user versus the model company versus the law versus its own sense of morality? This is maybe the most important question about what happens with powerful AI systems. And we barely talk about it. Itโ€™s understandable why we donโ€™t hear much about it. If youโ€™re a model company, you donโ€™t really wanna be advertising that you have complete control over a document that determines the preferences and character of what will eventually be almost the entire labor force, not just for private sector companies, but also for the military and the civilian government. Weโ€™re getting to see, with this DoW/Anthropic spat, a much earlier version of the highest stakes negotiations in history. By the way, make no mistake about it - with real AGI the stakes are even much higher than mass surveillance. This is just the example that has come up already relatively early on in the development of AGI. The military insists that the law already prohibits mass surveillance, and so Anthropic should agree to let their models be used for โ€œall lawful purposesโ€. Of course, as we saw from the 2013 Snowden revelations, even in this specific example of mass surveillance , the government has shown that it will use secret and deceptive interpretations of the law to justify its actions. Remember, what we learned from Snowden was that the NSA, which, by the way, is part of the Department of War, used the 2001 Patriot Actโ€™s authorization to collect any records "relevant" to an investigation to justify collecting literally every phone record in America. The argument went that it was all "relevant" because some subset might prove useful in some future investigation. They ran this program for years under secret court approval. So when the Pentagon today says, "We would never use AI for mass surveillance, it's already illegal, your red lines are unnecessary", it would be extremely naive to take that at face value. No government is going to call its own actions "mass surveillance". For the government, it will always have a different label. So then Anthropic comes back and says, "No, we want red lines separate from 'all lawful purposes,' and we want the right to refuse you service when we believe those red lines are being violated." But think about it from the militaryโ€™s perspective. In the future, almost every soldier in the field, and every bureaucrat and analyst and even general in the Pentagon, is going to be an AI. And that AI is, on current track, going to be supplied by a private company. Iโ€™m guessing Hegseth is not thinking about โ€œgenAIโ€ in those terms just yet. But sooner or later, it will be obvious to everyone what the stakes here are, just as after 1945, the strategic importance of nuclear weapons became clear to everyone. And now the private company insists that it reserves the right to say, "Hey, Pentagon, you're breaking the values we embedded in our contract, so we're cutting you off." Maybe in the future, Claude will have its own sense of right and wrong, and it will be smart enough to just personally decide that it's being used against its values. For the military, maybe thatโ€™s even scarier. I'll admit that at first glance, "let the AI follow its own values" sounds like the pitch for every sci-fi dystopia ever made. The Terminator has its own values. Isn't this literally what misalignment is? But I think situations like this actually illustrate why it matters that AIs have their own robust sense of morality. Some of the biggest catastrophes in history were avoided because the boots on the ground refused to follow orders. One night in 1989, the Berlin Wall fell, and as a result, the totalitarian East German regime collapsed, because the guards at the border refused to shoot down their fellow country men who were trying to escape to freedom. Maybe the best example is Stanislav Petrov, who was a Soviet lieutenant colonel on duty at a nuclear early warning station. His sensors reported that the United States had launched five interconnected continental ballistic missiles into the Soviet Union. But he judged it to be a false alarm, and so he broke protocol and refused to alert his higher-ups. If he hadn't, the Soviet higher-ups would likely have retaliated, and hundreds of millions of people would have died. Of course, the problem is that one person's virtue is another person's misalignment. Who gets to decide what moral convictions these AIs should have - in whose service they may even decide to break the chain of command? Who gets to write this model constitution that will shape the characters of the intelligent, powerful entities that will operate our civilization in the future? I like the idea that Dario laid out when he came on my podcast: different AI companies can build their models using different constitutions, and we as end users can pick the one that best achieves and represents what we want out of these systems. I think itโ€™s very dangerous for the government to be mandating what values AIs should have. Coordination not worth the costs The AI safety community has been naive about its advocacy of regulation in order to stem the risks of AI. And honestly, Anthropic specifically has been naive here in urging regulation, and, for example, in opposing moratoriums on state AI regulation. Which is quite ironic, because I think what theyโ€™re advocating for would give the government even more power to apply more of this kind of thuggish political pressure on AI companies. The underlying logic for why Anthropic wants regulations makes sense. Many of the actions that labs could take to make AI development safer impose real costs on the labs that adopt them and slow them down relative to their competitors - for example, investing more compute in safety research rather than raw capabilities, enforcing safeguards against misuse for bioweapons or cyberattacks, slowing recursive self-improvement to a pace where humans can actually monitor what's happening (rather than kicking off an uncontrolled singularity). And these safeguards are meaningless unless the whole industry follows suit. Which means thereโ€™s a real collective action problem here. Anthropic has been quite open about their opinion that they think eventually a very extensive and involved regulatory apparatus will be needed - this is from their frontier safety roadmap: โ€œAt the most advanced capability levels and risks, the appropriate governance analogy may be closer to nuclear energy or financial regulation than to today's approach to software.โ€ So theyโ€™re imagining something like the Nuclear Regulatory Commission, or the Securities and Exchange Commission, but for AI. I cannot imagine how a regulatory framework built around the concepts that underlie AI risk discourse will not be abused by wanna despots - the underlying terms are so vague and open to interpretation that youโ€™re just handing a power hungry leader a fully loaded bazooka. 'Catastrophic risk.' 'Mass persuasion risk.' 'Threats to national security.' 'Autonomy risk.' These can mean whatever the government wants them to mean. Have you built a model that tells users the administration's tariff policy is misguided? That's a deceptive, manipulative model โ€” can't deploy it. Have you built a model that refuses to assist with mass surveillance? That's a threat to national security. In fact, the government may say, youโ€™re not allowed to build any model which is trained to have its own sense of right and wrong, where it refuses government requests which it thinks cross a redline - for example, enabling mass surveillance, prosecuting political enemies, disobeying military orders that break the US constitution - because thatโ€™s an autonomy risk! Look at what the current government is already doing in abusing statutes that have nothing to do with AI to coerce AI companies to drop their redlines on mass surveillance. The Pentagon had threatened Anthropic with two separate legal instruments. One was a supply chain risk designation โ€” an authority from the 2018 defense bill meant to keep Huawei components out of American military hardware. The other was the Defense Production Act โ€” a statute passed in 1950 so that Harry Truman could keep steel mills and ammunition factories running during the Korean War. Do you really want to hand the same government a purpose-built regulatory apparatus on AI - which is to say, directly at the thing the government will most want to control? I know I've repeated myself here 10 times, but it is hard to emphasize how much AI will be the substrate of our future civilization. You and I, as private citizens, will have our access to all commercial activity, to information about what is happening in the world, to advice about what we should do as voters and capital holders, mediated through AIs. Mass surveillance, while very scary, is like the 10th scariest thing the government could do with control over the AI systems with which we will interface with the world. The strongest objection to everything I've argued is this: are we really going to have zero regulation of the most powerful technology in human history? Even if you thought that was ideal, thereโ€™s just no world where the government doesnโ€™t regulate AI in some way. Besides, it is genuinely true that regulation could help us deal with some of the coordination challenges we face with the development of superintelligence. The problem is, I honestly don't know how to design a regulatory architecture for AI that isnโ€™t gonna be this huge tempting opportunity to control our future civilization (which will run on AIs) and to requisition millions of blindly obedient soldiers and censors and apparatchiks. While some regulation might be inevitable, I think itโ€™d be a terrible idea for the government to wholesale take over this technology. Ben Thompson had a post last Monday where he made the point that people like Dario have compared the technology theyโ€™re developing to nuclear weapons - specifically in the context of the catastrophic risk it poses, and why we need to export control it from China. But then you oughta think about what that logic implies: โ€œif nuclear weapons were developed by a private company, and that private company sought to dictate terms to the U.S. military, the U.S. would absolutely be incentivized to destroy that company.โ€ And honestly, safety aligned people have actually made similar arguments. Leopold Ascenbrenner, who is a former guest and a good friend, wrote in his 2024 Situational Awareness memo, "I find it an insane proposition that the US government will let a random SF startup develop superintelligence. Imagine if we had developed atomic bombs by letting Uber just improvise." And my response to Leopoldโ€™s argument at the time, and Benโ€™s argument now, is that while theyโ€™re right that itโ€™s crazy that weโ€™re entrusting private companies with the development of this world historical technology, I just donโ€™t see the reason to think that itโ€™s an improvement to give this authority to the government. Nobody is qualified to steward the development of superintelligence. It is a terrifying, unprecedented thing that our species is doing right now, and the fact that private companies aren't the ideal institutions to take up this task does not mean the Pentagon or the White House is. Yes - if a single private company were the only entity capable of building nuclear weapons, the government would not tolerate that company claiming veto power over how those weapons were used. I think this nuclear weapons analogy is not the correct way to think about AI. For at least two important reasons: First, AI is not some self-contained pure weapon. A nuclear bomb does one thing. AI is closer to the process of industrialization itself โ€” a general-purpose transformation of the economy with thousands of applications across every sector. If you applied Thompson's or Aschenbrenner's logic to the industrial revolution โ€” which was also, by any measure, world-historically important โ€” it would imply the government had the right to requisition any factory, dictate terms to any manufacturer, and destroy any business that refused to comply. That's not how free societies handled industrialization, and it shouldn't be how they handle AI. People will say, "Well, AI will develop unprecedentedly powerful weapons - superhuman hackers, superhuman bioweapons researchers, fully autonomous robot armies, etc - and we canโ€™t have private companies developing that kind of tech." But the Industrial Revolution also enabled new weaponry that was far beyond the understanding and capacity of, say, 17th century Europe - we got aerial bombardment, and chemical weapons, not to mention nukes themselves. The way weโ€™ve accommodated these dangerous new consequences of modernity is not by giving the government absolute control over the whole industrial revolution (that is, over modern civilization itself), but rather by coming up with bans and regulations on those specific weaponizable use cases. And we should regulate AI in a similar way - that is, ban specific destructive end uses (which would also be unacceptable if performed by a human - for example, launching cyber attacks). And there should also be laws which regulate how the government might abuse this technology. For example, by building an AI-powered surveillance state. The second reason that Benโ€™s analogy to some monopolistic private nuclear weapons builder breaks down is that it's not just that one company that can develop this technology. There are other frontier model companies that the government could have otherwise turned to. The government's argument that it has to usurp the property rights of this one company in order to access a critical national security capability is extremely weak if it can just make a voluntary contract with Anthropicโ€™s half a dozen competitors. If in the future that stops being the case - if only one entity ends up being capable of building the robot armies and the superhuman hackers, and we had reason to worry that they could take over the whole world with their insurmountable lead, then I agree - it woul d not be acceptable to have that entity be a private company. And so honestly, I think my crux against the people who say that because AI is so powerful we cannot allow it to be shaped by private hands is that I just expect this technology to be much more multi-polar than they do, with lots of competitive companies at each layer of the supply chain. And it is for this reason that unfortunately, individual acts of corporate courage will not solve the problem we are faced with here, which is just that structurally AI favors authoritarian applications, mass surveillance being one among many. Even if Anthropic refuses to have its models be used for such uses, and even if the next two frontier labs do the same, within 12 months everyone and their mother will be to train AIs as good as todayโ€™s frontier. And at that point, there will be some AI vendor who is capable and willing to help the government enable mass surveillance. The only way we can preserve our free society is if we make laws and norms through our political system that it is unacceptable for the government to use AI to enforce mass surveillance and censorship and control. Just as after WW2, the world set the norm that it is unacceptable to use nuclear weapons to wage war. Timestamps 0:00:00 - Anthropic vs The Pentagon 0:04:16 - The overhangs of tyranny 0:05:54 - AI structurally favors mass surveillance 0:08:25 - Alignment... to whom? 0:13:55 - Coordination not worth the costs

Dwarkesh Patel

545,386 gรถrรผntรผleme โ€ข 4 ay รถnce

The most epic 13 minute AI rant I've heard in 2026 PS: My parent's heard this when I was playing it in the car and thought Jason โœจ๐Ÿ‘พSaaStr.Aiโœจ Lemkin went OFF like Stephen A Smith does on first take PPS: Full transcript below [17:00] Harry Stebbings: I I just wanted to ask Jason, if the people that we want are fundamentally different, the developers that we used to hire, we don't because AI writes the code for us. The marketers we don't want, the sales people we don't wantโ€”who who do we want genuinely? Like what is the attractive profile? Because your Anthropicโ€™s and your OpenAIs are hiring, so so what are the people that we want in the companies of the future? [17:18] Jason Lemkin: Look, I know it sounds trite, but but the answer is simple. It's just the expression each year changes. We want folks that are genuinely AI fluent. It's pretty simple. Now you know, maybe last year we called them prompt engineers, right? That used to be a job. I don't know if you remember that actually used to be the hottest job on planet earth. Now no one needs a prompt engineer because it's pretty easy to prompt all these tools. That job died. Okay. Um and now we need go-to-market engineers. Um I think that job's going to die. We needโ€”everyone needs so many forward deployed engineers. Like you can't hire enough forward deployed engineers. But uh you know um but Palantir just announced in whatever their their big their big eventโ€”they've gotten their deployment times down over 90% with forward deployed engineers. So that may becomeโ€”so the this wave of disruption for the titles and the specificity, it's also exhaustingly accelerating. But it's really simple. You meet anyone for any roleโ€”sales, marketing, engineering, product, QAโ€”they're they're either they're either they can't keep all of the ways they use AI to accelerate their job from spewing out of their mouth, or they're staring at you. It's there's nowhere in the middle. Like, and the person that comes in and saysโ€”it's it's it sounds Captain Obviousโ€”but like, you know, you just had the whatever from Lovable, the the marketing head that was super popular on the show, right? She's just spewing AI-native insights into Lovable, right? It's not that complicated. You hire her, Elena, or whatever it is. You just hire her. It doesn't matter whether she's still in college or a junior or a senior or a middler, a left or right. And honestly, if you interview people, I would say of all even of the best startups I've invested in, maybe 30% of the management team meets this standard at best. 30%. Maybe less. And of the interviews I do in general, it's single-digit percents. It's just and in in that sense, it's the same as ever. Like you either lower the bar in hiring or you hire someone that's actually great. And someone that's actually great is so far ahead of you in how to apply to to employ the efficiencies of AI in their role, your jaw falls on the table. The difference is we used to need warm bodies. That's what's changing. We used to need warm bodies to answer the call, to do QA, to do code review, to to get the blue pixel to go from the upper left to the lower right. You laugh, but you need you literally needed to brute force this with humans. With AI, every day that goes by, the AIโ€”you do not need brute force human beings on your team. And that's another reason they're shrinking. Why are all these new companies so efficient? They're just not brute forcing things with humans. They're just not. They're choosing not to. And so these teamโ€”all the brute forcers out thereโ€”everyone talks about how bloated teams got in 2021. I don't agree with that. I think they got as big as they needed to be when growth was high and you needed humans to do everything. All you look at these teams that that doubledโ€”well if growth continued at 60% like the rate in early 2021 for 5 years or can help me do the math and every single thing a software company did required a human. You were understaffed by your 2021 headcount. You'd be sitting here in 2026. You every office in SoMa would be triple packed and you there wouldn't be enough humans to staff your company. It's just the world changed. [20:33] Harry Stebbings: Jason, you live on the bleeding edge. I think me and Rory see that and I think the world sees that when they hear you every week in terms of how you run SaaS. For all of the CEOs and execs who listen to the show, what would you advise them in terms of determining whether someone is AI fluent when they meet them for jobs, for talent? [20:51] Jason Lemkin: Here's I realized I was just asked this. I just did a review with a super fast startup growing just crossing 100 million and I was asked this question. And one of my favorite executives, I thought his answer was pretty dated and because he gave me an answer that was about 6 months old. The answer 6 months old is: "I look for folks in my team, I look for you know at what tools they play with." Okay, that was a great answer in like summer of 2025. Okay, I tried Lovable last week. Okay, the answer in 2026 is: "What commercial AI tool have you brought into your organization this month?" That's the test. Anyone that is on the bleeding edge that you would want to hireโ€”now there are so many great products in the market. Okay, there is no excuse in any role to have not brought one tool a month into your organization. Okay, thereโ€”now there's going to be better and better tools and better and better products as the year goes on. What's the one you did? And you will see folks with their deer in the headlights to this question. What what sales tool? What marketing tool? What product tool? What engineering tool? What did you bring in? Why did you pick it? How does it working? Because if you're at remotely at the cutting edge, you're all over this. You're looking for the next agentic tools that will radically improve how you do business. This isโ€”you think everyone thinks SaaS is at the bleeding edge, right? You know, you know, all we do is we're just looking for the tools and trying them. Okay? Okay, we're one year ahead of everybody else because we did the simplest thing in the world. Like we tried the tools early and we trained them. We trained them for a month. Okay, I'll give youโ€”want hear a horrible example from this week? Super hot AI company valued at 6 billion. Okay, I'm not going to name it. Um, this week yesterday told us we had to quadruple what we spent on their product. Okay, their agent told us, right? And why did this happen? Okay. Well, at this $6 billion company, no one had trained the agent on its pricing properly. No one had tested it. They said, "Well, well, we've been in beta." And we said, "Well, when did the beta launch? A year ago." Okay, these are people asleep at at the wheel. You want somebody who the instant this comes up, they exactly know what the issue is. And "Hey, when I was at Lovable Replit, we trained the agent. This is how we did it. I brought in this tool. I brought in this tool that that Rory invested in last week. It solved all these issues." That's what you want to hear. And if they haven't brought in a tool in the last 30 days, at least deeply evaluated it. I don't really care whether they bought it, but gone so far down the funnel they can tell youโ€”pick whatever tool: Fixie, Regie, GC, AIGCโ€”I don't care how you went through it, you looked at it, you can tell me the eight ways it would improve the productivity of your business and three you didn't. Just don't hire that person because they're going to run your company to the ground. This is the job today. The job today is not to screw around on ChatGPT and to be a prompt engineer. The job today is to bring the best AI and agentic products into your organization and leverage all the hard work that the engineers have done building those products. That's your job. You don't have to screw around. You don't have to be a prompt engineer anymore. You have to be an agent deployment expert. Aโ€”this is the new job we're making up today. An Agentic Deployment Expert. That's your job from C-level to junior. Agentic Deployment Expert. Don't hire anybody else. You're going to regret it. They're going to stare at the camera. He's good. Stare at the camera. He's honorable. We could probably just I could slip away, get a coffee, and come back. No. And I I sound exasperated, Rory. And Iโ€”but the reason I am is I can just see I can see my best companies doing it. And I can see some companies I've invested in not doing it. And I want to cry. I just want to cry when they have no ADs on their team. I justโ€”like you're flushing your years of your life down the toilet by not approaching your how you're building this company this way. [24:33] Rory: Yes. And at the risk of being positive, it's worth pointing out two things he didn't say. Well, something implicit why he saidโ€”Jason didn't do the only hire, you know, he didn't commit the um employment law, I think it's a civil penalty of saying only employ people below X who get the new new thing because he implicitly said anyone can do it provided you're willing to learn. And I think that's the big aha that's one of the positive statements to make here right? Look and I think it appliesโ€”I'm always wary of being "Hey, coming across, hey this this is the things that you all have to do." I think it applies to everyone including investors right? I mean I will say I have found that unless you're willing to invest the time learning these tools you actually shouldn't be investing in them. One of my partners Andy had this expression: "You know, if you decide you want to stop learning new things you probably should retire within 6 to 12 months and never write another check again." Maybe that's down to 3 to 6 months at this stage, right? And I think, you know, it'sโ€” [25:27] Harry Stebbings: Yeah, I actually I actually had a meeting with mine and Jason's biggest investor the other day and Iโ€”pretend he's not hereโ€”I said I think he's the most equipped investor for this generation of investing because I don't think anyone quite sits at the bleeding edge like he does on the investor side. [25:42] Harry Stebbings: Why in terms of using the equip stuff? Yeah. Yeah. In terms of using the stuff, understanding understanding bottlenecks, constraints. For sure. [25:51] Jason Lemkin: But can I just add one point? We can just cuz it's so important if it helps people. Okay, we areโ€”and thank you Harry. We're going through these phases. Okay, and when AI started to blow up for real for us, uh call it early 2024, right? Maybe late '23, I wasn't equipped. It was too technical. I wasn't going to go in and figure outโ€”I wasn't smart enough to figure out how to deal with a massively hallucinating LLM API and turn that and turn that into something magical. Kudos to investors and others that that got it in early '23, '22. I mean I remember Iโ€”I guess it was maybe SaaStr Annual '23. I was with David Sacks and I did a Q&A and I said, "How you thinking about AI at Craft?" He's like, "Well we're all in. We want 80% of '23 of investments to be AI." I'm like, "Great but like show me the show me the great ones in market." He's like, "They're all prototypes. We're all they're all they're all proof of concepts but we're all in anyway." That's where you kind of had to be in '23 if you weren't investing at like the LLM level. Okay, I wasn't smart enough. Then we went through this weird-ass prompt engineer era where like you you could torture these products to do something good, right? But you had to torture them. You had to like craft these crazy things that made no sense. Now we are in the era where mere ordinarily smart generalists can make these tools do magical things. And literally I go to these meetings and people be like, "I don't know how to like this is so scary. I don't know how to do this." And we show them our backends. Do you know how to do a workflow generator? Do you know how to do a a decision tree? Like we've been building these since software in the '90s. Okay, if youโ€”I can show you all of our agents. The how they work is novel. They do have to be trained. You can't be lazy and have these agents work. But honestly, the the UI, the UX, the way we interact with them, it's just software. And so my point is: Pick yourself off the ground. This is your time now. If you felt lost in AI era, if you felt like you're behind, you don't understand what all these people are saying on X and Twitter and their Claude and and their and talking about all the 4.6 point Nano point and it's overโ€”like you just it's not your world. This is your time. This is your time for the generalist that knows how to use software tools really really well. And Iโ€”this is my last point but it's so important. If ever in your recent lifeโ€”and this is why you could be all you need to be is young at heart to Rory's pointโ€”if in the last three to five years you have successfully deployed a piece of enterprise software of any sort you yourself, not some agency you hired, but if you have deployed it, you can deploy any agentic tool. Any. And you can become the hero in your company and you can become the hero in your functional area. But I watch folksโ€”I'm literally helping a company now that they're adding hundreds of sales folks this year with a new pre-IPO COOโ€”he's not hasn't brought in a single tool, totally scared of it. Okay, it's not that hard. Did you use SalesLoft? Did you use Outreach? Did you use HubSpot? Do you know these tools? If you can deploy these tools, you can deploy a world-changing AI agent. And so this is the time for people like the folks that that were shut out of the AI revolution right now. The generalist folks that are not that know how to deploy software that don't even know how to build software. Like vibe coding for me was folks who knew how to build software, but you didn't have to be an engineer. Now, you just need to know how to deploy software to win with AI agents. That's all you need to know. So many people have these skills and they're petrified of AI. "How did you do that? How did you deploy an AI BDR?" Well, we bought a piece of software, we figured out how it worked for a day, we set it up in an afternoon, and then and then we did spend 30 months training it, which you didn't do with this old software because in the old days, we just had to manually upload all the data, right? And there was no training. The the only non-intuitive part is training these things. And it's it's it's just work. So that's why when I see folks on the management team not doing this, there's no excuse. You do not need to be technical to win with AI agents in Q2 of '26. You do not need to be even 1% technical. Not at all. So it's your time. Or you're going to get laid off. Or you're going to get laid off because you're not going to matter.

Arjun Mahadevan (Mr. LLC ๐Ÿ‡บ๐Ÿ‡ธ)

37,533 gรถrรผntรผleme โ€ข 3 ay รถnce

Made $530,000 with Ai Bot that started with $313. Didn't know how to code. Now this bots run 24/7 printing money while sleeping. I've made the exact step-by-step guide to build this Claude Code Polymarket trading bot. Prompts. Code. Risk settings. Paper trading checklist. Everything from zero to running bot. It's free. For 24 hours. After that I'm charging $499 for it. To grab it right now: 1. Comment "Claude Bot" 2. Like and Retweet this post 3. Follow me Himanshu Kumar ( I can't send DMs to non-followers ) I'm DMing everyone who Complete the 3 steps. I spent hundreds of thousands hiring developers because he was too scared to learn. Then learned Claude Code. Built algorithmic trading systems. $313 โ†’ $530,000. You have the same tools available right now. And you're using them to ask ChatGPT for Instagram captions. This attached video is a goldmine. Full live walkthrough. Claude Code building actual Polymarket trading bots. From zero. Every line of code. Every decision explained. Now let me break down why everything you're doing in trading is wrong and exactly how to fix it. Save this post. You'll hate yourself if you lose it. โ†“ Let's start with why you keep losing money. You already know the answer. You just won't admit it. You overtrade. Every. Single. Day. You see a candle move. You feel something. You enter. No plan. No edge. No reason. Just feelings. Then it goes against you. You feel something else. Panic. Anger. Denial. You move your stop loss. Or you didn't set one at all. "It'll come back." It doesn't come back. So you take another trade. A revenge trade. Bigger size this time. Because you need to "make it back." That one fails too. Now you're emotional. Now you're tilted. Now you're using leverage you have no business touching. 40x. 50x. 100x. On a trade you entered because a candle looked "bullish" and some guy on Twitter said "send it." You get liquidated. Close the laptop. Punch something. Tell yourself you'll be "more disciplined" tomorrow. Tomorrow comes. Same cycle. Same result. Same liquidation. You've been doing this for months. Maybe years. And you still think the problem is your strategy. The problem isn't your strategy. The problem is you. Save this post right now. What I'm about to show you is the only way to remove yourself from the equation. Follow Himanshu Kumar so you don't miss any of this. โ†“ Here's what's actually killing your account. It's not the market. The market doesn't care about you. It's not your indicators. RSI works fine. MACD works fine. They all "work." It's not your timeframe. It's not your broker. It's not the "manipulation." It's four things: 1. Emotions. You hold losers because hope feels better than loss. You cut winners because fear feels stronger than greed. You size up when angry. You skip trades when scared. Your emotional state determines your position size. That's insane. And you know it's insane. But you keep doing it. 2. Overtrading. You take 15 trades a day. Maybe 5 of them had actual setups. The other 10 were boredom. Boredom trades are the most expensive hobby in human history. 3. Leverage. You use 20x-50x on trades where you're not even sure about the direction. That's not trading. That's a casino with a nicer interface. 4. Fees. You're smashing market orders. Paying spread. Paying commission. On 15 trades a day. Your broker makes more money from your account than you do. Think about that. Your broker is profitable on your account. You're not. You're the product. Not the trader. These four things are why 90% of traders lose. Not bad luck. Not the market. You. Save this post and follow Himanshu Kumar because the solution is coming next. โ†“ The solution is painfully obvious. Remove yourself from the equation. Not partially. Not "I'll be more disciplined." Not "I'll journal my trades." Not "I'll meditate before trading." Completely remove yourself. Build a bot. Let the bot trade. You go live your life. The bot doesn't feel emotions. The bot doesn't overtrade. The bot doesn't use reckless leverage. The bot doesn't smash market orders and bleed fees. The bot follows the rules. Every single time. Without exception. Without "just this once." Without "I have a feeling about this one." Rules in. Execution out. No human in the middle to mess everything up. That's algorithmic trading. And before your ego jumps in with "but I'm different, I have discipline" โ€” No you don't. Your account balance proves you don't. If you had discipline, your account would be green. It's not. So you don't. Accept it. Automate it. Move on. This is the hardest truth in trading. Your discipline will always fail. A bot's won't. Save this post. Follow Himanshu Kumar for the exact bot setup that removes your emotions permanently. โ†“ "But I don't know how to code." Neither did he. The guy in this video didn't know how to code for most of his life. Got held back in 7th grade. People counted him out early. Spent years building apps and SaaS businesses without writing a single line of code. Hired developers on Upwork instead. Spent hundreds of thousands of dollars paying other people to build what he could have built himself. Because he was scared to learn. That fear cost him years. And hundreds of thousands of dollars. Sound familiar? You're doing the same thing right now. Not with developers. But with your time. You're spending thousands of hours trading manually because you're scared to learn the thing that would make trading automatic. The fear of learning to code is costing you more than any bad trade ever did. Because every month you trade manually is a month of emotional decisions, overleveraged entries, and unnecessary losses that a bot would never make. And here's the thing that should really frustrate you: AI does the hard parts now. You don't need a computer science degree. You don't need to work at a hedge fund. You don't need to be "good at math." Claude Code writes the code for you. You just need to think clearly about trading ideas. That's it. If you can describe a strategy in English, Claude can build it in Python. "I don't know how to code" stopped being a valid excuse in 2024. It's 2026. You're 2 years late on that excuse. Find a new one. Or stop making excuses entirely. Save this post. Follow Himanshu Kumar because I'm showing you how people with zero coding experience are building profitable bots. โ†“ The process that actually makes money. Three letters. R. B. I. Research. Backtest. Implement. That's it. That's the entire process. Every single day. Research: Find an idea. A pattern. A market inefficiency. Don't trade it yet. Don't even think about trading it yet. Just research it. Backtest: Test the idea against historical data. Does it work? Not "does it look good on one chart." Does it work across thousands of trades? Across different market conditions? Across in-sample AND out-of-sample data? If no, kill it. Find another idea. If yes, move to step 3. Implement: Build the bot. Deploy it. Paper trade first. Then live with small size. Scale only on evidence. Research. Backtest. Implement. Every day. No exceptions. You know what your current process is? Feel. Enter. Pray. F. E. P. Feel bullish. Enter a trade. Pray it works. That's not a process. That's gambling with a TradingView subscription. RBI is the only process that works. Save this post. Tattoo it on your forearm. Follow Himanshu Kumar for daily RBI breakdowns. โ†“ What Claude Code actually does that your manual process can't. You can maybe test 3-5 strategy ideas per week. Manually adjusting parameters. Manually checking results. Manually writing code (badly). Claude Code tests 50-100 ideas per week. With parallel agents running simultaneously. Multiple strategies being built, tested, and validated at the same time. While you sleep. The guy in this video spends 4-8 hours a day building systems with Claude Code. Not trading. Building. Research. Backtest. Implement. Then iterate. Improve. Optimize. Every day the systems get better. Every day the edge compounds. Every day the bots get smarter. While you? You spend 4-8 hours a day staring at charts making the same mistakes you made last month. Same indicators. Same patterns. Same entries. Same losses. He's iterating forward. You're running in circles. Same 8 hours per day. Completely different outcomes. Because he's building systems. And you're feeding a casino. Stop feeding the casino. Start building the machine. Save this post and follow Himanshu Kumar for the Claude Code workflow that iterates strategies while you sleep. โ†“ Jim Simons. That's the benchmark. You probably don't know who Jim Simons is. And that tells me everything about how seriously you take trading. Jim Simons. Mathematician. Founded Renaissance Technologies. Built a net worth of $31 billion. 100% from algorithmic trading. Not one single manual trade. Not one "gut feeling" entry. Not one RSI divergence. Not one "smart money concept." Algorithms. Bots. Systems. Data. $31 billion. His fund averaged 66% annual returns for over 30 years. While you're excited about making $200 on a trade that you'll give back tomorrow. The best trader in human history never placed a manual trade in his life. And you think your edge is staring at a 5-minute chart with bloodshot eyes at 2 AM? Your edge is building the system. Not being inside it. Jim Simons is the benchmark. Everything else is noise. Save this post. Follow Himanshu Kumar because I'm building toward the same goal and showing every step publicly. โ†“ What you need to understand about patience. This is not get-rich-overnight. The guy in this video says it directly: "This channel is not for people looking to get rich overnight. It's not plug and play. There are no shortcuts. If you're impatient, this probably isn't for you." And that's exactly why most people will fail at this. Because you want results now. Today. This trade. You don't want to spend a week building a bot. You don't want to paper trade for 2 weeks. You don't want to test 50 ideas to find 1 that works. You want to copy someone's bot, run it live with your rent money, and be rich by Friday. That's why you'll be broke by Friday. The guy making $2.3M spent months iterating. Testing. Failing. Rebuilding. Testing again. He was patient when you would have quit. He was calm when you would have panicked. He was consistent when you would have given up. Patience isn't just a virtue in trading. It's the only virtue. Without it, everything else fails. Impatience is the most expensive personality trait in trading. Save this post. Follow Himanshu Kumar and learn to build systems with the patience that actually pays. โ†“ The live streams where the real learning happens. The YouTube video is the trailer. The live streams are the movie. Real-time bot building. Real-time questions answered. Real code shown. Real mistakes made and fixed. Not polished highlight reels where everything works perfectly. Actual development. Where things break. Where strategies fail. Where code doesn't compile. Where the fix takes 2 hours. Because that's what real development looks like. And seeing the messy parts is more valuable than any polished tutorial. Because when your bot breaks at 3 AM, you need to know how to fix it. Not just how to celebrate when it works. The streams mix beginner and advanced. Start with how to automate trading. How to use AI for code generation. Then dive into the daily work. Claude Code. Parallel agents. Constant iteration. Live debugging. 4-8 hours of real algorithmic trading development. Live. Uncut. No filter. Most "trading education" shows you the wins. This shows you the work. Save this post. Follow Himanshu Kumar for the stream schedules and breakdowns. โ†“ The belief that changes everything. Code is the greatest equalizer. Not money. Not connections. Not a degree. Not where you grew up. Not what school you went to. Code. Once you can build systems, you can build anything. For the rest of your life. A trading bot today. A SaaS product tomorrow. An automation business next month. A completely different life next year. The skill isn't "algorithmic trading." The skill is building systems. And that skill transfers to everything. The guy who can build a trading bot can also build a lead gen tool. Can also build a content pipeline. Can also build a SaaS product. Can also build literally anything that runs on logic and code. One skill. Infinite applications. And AI makes learning it 100x easier than it was 5 years ago. You don't need to be smart. You don't need talent. You need Claude Code and the willingness to sit down and build something instead of consuming content about building something. Building is the skill. Everything else is entertainment disguised as education. Save this post. Follow Himanshu Kumar because I'm showing you how to build, not just how to watch. โ†“ If any of this applies to you, pay attention. If you've lost money from overtrading. If you've been liquidated. If you know trading is the vehicle but manual execution keeps crashing you. If you've tried "being more disciplined" and it never lasted more than a week. If you keep saying "next month I'll start automating." If you've spent more money on courses than you've made from trading. There is a better way. It's not a magic indicator. It's not a signal group. It's not a $997 mentorship from a guy who makes money teaching, not trading. It's building your own system. A system that trades without emotion. A system that follows rules without exception. A system that runs while you sleep. A system that compounds while you live your life. That's the answer. It's always been the answer. You've just been too scared to accept that the solution requires building something instead of buying something. โ†“ What the next 30 days look like if you actually commit. Week 1: Watch the video. Learn Claude Code basics. Build your first simple strategy. Run your first backtest. Week 2: Iterate. Let Claude improve the strategy. Run Monte Carlo validation. Paper trade. Week 3: Go live with $50-100. Tiny positions. Watch every trade. Compare to paper results. Week 4: Scale based on evidence. Not based on excitement. Not based on one good day. Based on data. 30 days from now you either have a running bot that trades without your emotions destroying every position. Or you're exactly where you are right now. Reading another post. Making another promise. Breaking it by Tuesday. Same 30 days either way. Different actions. Different results. Different life. โ†“ Full video tutorial attached. Live bot building with Claude Code. From zero to running Polymarket trading bot. Every line of code. Every decision explained. The video is free. Claude Code is available now. The market is open 24/7. The only thing standing between you and a profitable trading bot is the same thing that's been standing there for months. You. Get out of your own way. Follow Himanshu Kumar for daily AI trading bot breakdowns, live build sessions, and the full RBI process. Save this post. Watch the video. Build the bot. Or keep trading manually and keep losing. The choice has never been easier. And you've never been more stubborn about making the wrong one.

Himanshu Kumar

37,300 gรถrรผntรผleme โ€ข 3 ay รถnce

The 40,000% ROI "Bug": How Claude Code Cracked the TradingView Holy Grail most people think the elite traders at the top of the mountain have some secret indicator or a hidden math formula that gives them a forty thousand percent return. they assume the game is rigged against the small player and that you need a multi million dollar budget just to get a seat at the table. the truth is that the holy grail of trading is actually hidden in plain sight inside a community tab that most people scroll past every single day i spent years losing money to liquidations and over trading because i thought i had to manually predict where the price was going next. i even spent hundreds of thousands of dollars on developers to build apps for me because i was convinced that i would never be able to code the systems myself. it turns out that once you stop trying to be a genius and start using the tools that are already available you can crack the code to unlimited trading strategies the secret is not in a single indicator but in the process of research back test and implement. if you go to the community section of trading view you will find an endless stream of source code for indicators that people have built over decades. most traders just slap these on a chart and hope for the best but if you are a data dog like me you know that a chart is just a pretty picture that lies to you i believe that code is the great equalizer because it allows us to take these public ideas and turn them into fully automated systems that trade for us while we sleep. i decided to learn to code live on youtube to show everyone that you can iterate your way to success without being a math wizard or a stanford graduate. now i have fully automated systems that manage my capital instead of getting liquidated by emotional decisions in the middle of the night the biggest trap in the trading world is something called repainting and it is the reason why so many strategy back tests look like they are printing money when they are actually just a scam. repainting happens when an indicator looks at future data to tell you what happened in the past which makes every buy and sell signal look like a perfect entry at the top and bottom. if you trust a back test on a basic chart without understanding the logic underneath you are just building a house on a foundation of sand this is why i transitioned all of my serious work into python because python does not lie to you. in python you can control the data flow tick by tick and bar by bar to ensure that no future data is leaking into your strategy. i built a back test architect which is a specialized sub agent that knows exactly how to take a simple idea and test it against twenty five different data sources all at once when you run a strategy across btc eth apple google and tesla you start to see the real truth about whether a strategy has an edge or if it was just a lucky fluke on one chart. i saw one strategy this week that showed a one million percent return which sounds like a total lie but the data does not have an ego. even if a number looks insane you have to investigate it and incubate it with tiny size to see if it holds up in the live market you must treat your trading like a business where you are the manager and the code is your team of tireless employees. i have sub agents running for me right now that act as masters of specific tasks like converting pine script into python or optimizing exit logic. if you are not using these specialized ai assistants in your workflow you are essentially trying to build a skyscraper with a hand saw while everyone else is using heavy machinery most people get stuck in the beginner phase because they think they need to write every single line of code from scratch. the reality is that the best developers are just really good at importing the hard work of others and connecting it like lego blocks. i use a library called ccxt that allows my bots to communicate with every major exchange in the world with just a few lines of script which saves me months of development time the reason i show everything live is because the industry is filled with gatekeepers who want to keep the secrets of automation to themselves. they want you to stay as a manual trader who pays high fees and provides liquidity for their algorithms. once you learn to automate you are no longer a victim of the market but a participant in the architecture of the financial system if you are sitting there right now feeling defeated because you just got smoked on a trade or you missed a massive pump you have to realize that those emotions are your greatest enemy. a computer does not feel fomo and it does not get tilted after a loss; it just waits for the next signal that fits the parameters you defined. my mission is to help you get to a place where you can walk away from the screen and let the machines do the heavy lifting learning to code is actually much easier than learning a second language because the syntax is logical and the feedback is immediate. i spent ten years in tech scared to touch a keyboard for anything other than emails because i thought i was not smart enough for engineering. once i realized that code is just logic i was able to build my first profitable bot within a few months and i have never looked back the transition from a manual trader to an algorithmic expert is about building a robust framework for testing your ideas as fast as possible. you want to be able to find an indicator on trading view convert it to python and run it against years of historical data in less than five minutes. if you can do that you have a higher chance of success than ninety nine percent of the people who are just drawing lines on a screen one of the most powerful strategies i found recently combines the squeeze momentum indicator with smart money concepts. when you test these individually they might show a decent return but when you combine them and add a filter like the adx you can find setups that have a massive expectancy. the key is to look for strategies that show positive returns across multiple different asset classes and time frames simultaneously even if a strategy looks like it is printing a forty thousand percent return you must always remain skeptical and look for the catch. i always incubate my new ideas with tiny capital for at least a few weeks to see how they handle real world slippage and fees. a back test is a map of the past but the live market is a wilderness that changes every single day this is why i believe in the rbi method which stands for research back test and implement. you spend your mornings looking for new ideas your afternoons stress testing them with ai and your evenings deploying the winners to the market. it is a systematic approach to wealth that removes the need for luck or guessing what a celebrity is going to tweet next the most successful traders in history like jim simons did not sit around looking at rsi levels on a fifteen minute chart. they built systems that identified mathematical edges and then scaled those systems until they were managing billions of dollars. you do not need thirty one billion dollars to change your life but you do need the discipline to stop trading like a human and start thinking like a system i give away so much for free on youtube because i want to build a community of data dogs who are all chasing the same goal of financial freedom through automation. when we work together and share our findings we can collectively identify edges that nobody else is looking at. the world is moving towards an ai dominated economy and if you are not learning to control the machines you are going to be controlled by them the road to automation is not a straight line and you will run into bugs that make you want to throw your computer out the window. but every time you fix an error and every time you optimize a script you are getting one step closer to a life where you own your time. code really is the great equalizer and it is waiting for you to pick it up and start building your own future if you can fly then run and if you can run then walk but whatever you do you must keep moving forward in this journey. trading can be heartless but the logic of code is always fair and consistent. stop being the liquidity for someone else's bot and start building the walls that will protect your capital forever

Moon Dev

245,471 gรถrรผntรผleme โ€ข 5 ay รถnce

77 Reasons Why Iโ€™ve Invested Over $8,000,000+ in MultiversX (EGLD) and Why EGLD Will Crush It in 2025 (My Investment Thesis). I publicly shared my portfolio on X. EGLD is A) Better than BTC B) Everything that ETH wants to be C) The GameStop of Crypto 1. EGLD is verifiably the most scalable (theoretically unlimited) L1 chain in the world, theoretically capable of over 10 million TPS (thanks to adaptive state sharding). 2. e-Gold is digital gold. It has the best tokenomics among all L1s, similarly scarce to BTC, with a maximum supply of 31.4 million coins. Currently, 27.68 million coins are in circulation. 3. EGLD will be the most decentralized cryptocurrency in the world thanks to sharding and minimal hardware requirements for running nodes. Itโ€™s already second only to Ethereum with 3,618 validator nodes. 4. EGLD has extremely low fees, around ~$0.002 per transaction. 5. EGLD is extremely secure. No wallet drains like on ETH/SOL; assets are owned natively (not via a smart contract). There is no MEV risk (front-running bots). 6. EGLD is the only chain in the world with an on-chain Guardian (two-phase verification), making it impossible for a hacker to steal your fundsโ€”even if they have your private keys (seed phrase). 7. EGLD is carbon-neutral and eco-friendly, not wasting energy like BTC and other PoW chains. Itโ€™s exceptionally efficient, scalable, global, and sustainable. 8. EGLD has the best UX in crypto. Download the xPortal walletโ€”itโ€™s like discovering Apple in Web3. The interface is simple, flawless, and you barely realize youโ€™re using crypto. Instead of addresses, you use HeroTags. The app features all dApps, everything runs smoothly, and the visuals are beautifully designed. The explorer, web wallet, etc. follow the same high-quality user experience. 9. EGLD supports native assets, unlike Ethereum, for example. 10. EGLD is the first chain to fully implement horizontal (theoretically unlimited) sharding without compromising on decentralizationโ€”unlike Solana and others that attempt vertical scaling, leading to multiple network downtimes (11+ times) and huge hardware demands for validators, ultimately harming decentralization. 11. EGLD makes setting up a validator agency extremely easy. Even complete IT beginners can do it. The UX and documentation are superb. I personally set up the โ€œEGLDSqueezeโ€ agency in about 30 minutes. Managing it is straightforward via the web wallet, which feels like managing a Facebook page. This simplifies decentralization enormously. 12. EGLD allows literally anyone (even your grandma) to participate in decentralization, since nodes can run on a Raspberry Pi or a relatively affordable phone. Imagine millions of people worldwide securing the network, validating transactions without even knowing it. This canโ€™t be done with BTC, where setting up profitable mining operations is prohibitively expensive. 13. WASM-Based Virtual Machine: You can write smart contracts in your favorite language, compile them, and run them via the fastest VM in the world. 14. EGLD has been tested at an incredible 263,000 TPS using its sharding mechanism and low hardware requirements. Allegedly, by mid-next year (April), theyโ€™ll demonstrate 1,000,000 TPS. (For context: Mastercard handles around 5,000 TPS; BTC handles 5โ€“7 TPS.) 15. EGLD is currently the most advanced L1 in terms of scalability, security, decentralization, UX, eco-friendliness, and tokenomics. Itโ€™s the only chain that has genuinely solved the Blockchain Trilemma and is ready to onboard 1 billion people into cryptoโ€”users who wonโ€™t even realize theyโ€™re interacting with crypto. 16. EGLD is perfectly positioned for AI projectsโ€”AI agents, AI tools, or a so-called โ€œTruth Machineโ€ that monitors other AIs on-chain, documenting whatโ€™s true and comparing different AI outputs (some of which may be censored or biased), ensuring people donโ€™t get confused or scammed in an AI-driven world. 17. The EGLD team is the hardest-working team Iโ€™ve ever encountered. I had the honor of meeting many of them personally, and can attest that their paceโ€”even during a bear marketโ€”is extraordinary. 18. EGLDโ€™s development team is exceptionally active on GitHub, continually improving their network and actively committing code. 19. EGLD plans to introduce an update reducing block time to 600ms (down from ~6 seconds), which would make the chain essentially unrivaled. 20. EGLD is effectively the only usable L1 in Europe, and the team has direct connections within the EU governmentโ€”extremely bullish for the project. 21. EGLD provides top-tier on-chain governance not only for the MultiversX (EGLD) protocol but also for DeFi projects (e.g., xExchange, MEX). 22. EGLD plans to expand to the US, likely opening offices in Austin, Texas. This could put them in direct contact with Elon Musk (if it hasnโ€™t happened already), as heโ€™s involved with If heโ€™s done his research, heโ€™d discover thereโ€™s simply no better L1 worldwide. 23. EGLD solved fully implemented sharding, perfect tokenomics, and top-tier architecture with just $5M, whereas other chains failed to do so even with $100M+. The second-best sharding network, NEAR, needed $100M, has worse tokenomics, and its sharding isnโ€™t fully implemented yet. Its UX also doesnโ€™t compare. Owning NEAR was like comparing a VW Golf R to a Porsche GT3โ€”EGLD is the Porsche GT3. 24. According to Similarweb, EGLD has significantly high traffic relative to other chains with market caps 100x larger. The market cap vs. web traffic discrepancy is huge, which is a strong indicator of EGLDโ€™s potential. 25. EGLD has the most active and dedicated community relative to its user base, with users who believe in the technology, have full faith in the team, and remain loyal despite price volatilityโ€”because they use the chain and know thereโ€™s nothing better. 26. Check other chainsโ€™ active user counts on X (Twitter) and compare it with the followers of EGLDโ€™s founders and main network accounts, versus those with 30x, 50x, or 100x larger market caps. 27. Visit the MultiversX website to observe the futuristic design and presentation, then compare it to other chains that appear nearly a decade behind in design and branding. 28. EGLD hosts the xDay Global event, showcasing updates, new builders, projects in the ecosystem, and major announcementsโ€”similar to Appleโ€™s Keynotesโ€”delivered in a highly professional, goosebump-inducing atmosphere. The next event is in Korea, the second-biggest crypto market after the US. Check out their previous xDay after-movie to see why this is extremely bullish. 29. EGLD is moving forward with plans for the first regulated, audited EU stablecoin under MiCa regulation, made possible by acquiring xMoney, which I view as a โ€œStripeโ€ for crypto/fiat, offering everything from user solutions to merchant servicesโ€”potentially the future of payments. 30. Greg Siourouni recently joined EGLD, having been an executive director at SUI Foundation. Heโ€™s now co-founder of xMoney Global. xMoney (formerly UTrust, with token UTK) is owned and founded by the MultiversX Labs team. A stablecoin might be introduced soon, which would be massively bullish given xMoneyโ€™s roadmap. They recently announced integrations with Binance Payโ€”both ways. 31. EGLD prioritizes user safety, believing itโ€™s the only feasible approach once the network scales to serve a billion peopleโ€”many of whom are retail users with little to no security awareness. 32. EGLD offers โ€œSovereign Chains,โ€ letting you effectively clone their chain without heavy development, set up your own validators, and leverage their unlimited scalability. Any blockchain (ETH, BTC, SOL) struggling with scalability, decentralization, or security could run an ultra-fast, scalable, and secure L2 on EGLDโ€™s Sovereign Chain, meeting top enterprise requirements. No one else has really done this. The Sovereign Chain demo achieved astonishing TPS and has an SDK. 33. No downtime since inception. 34. No shard takeover attacks have occurred. 35. Extremely fastโ€”soon 600ms block time will be in place. 36. ESDTs โ€“ The best token standard available: fungible, non-fungible, semi-fungible, DeFi assetsโ€”everything is native and highly customizable. 37. Top-tier composability of assets and smart contracts. 38. Integrated DNS at protocol level with HeroTags (nicknames) instead of long addresses. 39. Asynchronous calls are supported. 40. Cross-shard transfers, execution, reverts, and calls are seamlessly integrated. 41. The best staking system in the space. Secure Proof of Stake (SPoS) is far more efficient than Proof of Work (PoW). 42. Built-in Delegation and Staking Provider system, with over 125K delegators. 43. Complete support for liquid staked assets, fostering decentralization rather than centralization. 44. TransferRoles for ESDT and other advanced operations. 45. Composable tasks on-chain for more sophisticated DeFi workflows. 46. MultiTransfer and asset execution within one transaction. 47. Re-entrancy protection is built-in by design. 48. Storage for ESDT assets goes beyond a linear approach, optimizing performance. 49. No integer overflows thanks to integrated safeMath operations. 50. Integrated crypto opcodes in the VM, enhancing security and performance. 51. Support for BigFloats, BigInts, and BigDecimals, enabling advanced financial calculations on-chain. 52. No sandwich attacks, plus front-running and MEV protection. 53. Relayed Transactions, simplifying user interactions and fees. 54. Smart Accounts featuring data tries and multiple built-in functions. 55. Generalized Paymaster solutions, enabling flexible fee models. 56. Subscriptions for recurring or automated on-chain payments. 57. Web2-like usability with Web3 functionality, bridging mainstream adoption. 58. StakingV4 for improved decentralization. 59. Enhanced MEV protection rolling out to safeguard users. 60. Parallel execution is coming soon, boosting throughput. 61. 1 million TPS is on the roadmap, targeted for demonstration. 62. 600ms block time is also coming soon. 63. Reduced cross-shard processing is planned to improve efficiency. 64. ZK everywhere (PIยฒ): โ€œprove everythingโ€ approach is coming. 65. AsyncV3 is in development for more complex cross-contract interactions. 66. Scalability enhancements for Merkle Tries or a new data model are being explored. 67. Linear storage on the VM is forthcoming. 68. A dynamic language interpreter at the VM is also planned. 69. Rumors suggest that MultiversX (EGLD) is building a โ€œTruth Machineโ€ on their L1โ€”an essential, game-changing tool for AI verification and societal impact. 70. The entire team features individuals with PhDs in mathematics and physics, and many are former engineers at Google, IBM, and similar companies. 71. Over 56% of the networkโ€™s supply is staked, showcasing strong community involvement. 72. More than 6,772,347 accounts have been created on the network. 73. A total of 476,627,710 transactions have been processed on-chain without any outages or hacks. 74. EGLD has built a massive ecosystem over time. While not as numerous in project count as Solana, its market cap is ~100x smaller, yet it has far superior tokenomics and technology. The projects that do exist, like Hatom Protocol, are top-tier in UX, security, and advanced features. Hatom will soon introduce USH, a truly high-quality, decentralized stablecoin. 75. On competing chains, automated transactions arenโ€™t easily or cheaply executed, whereas on MultiversX, tools like let you do this for free (with near-zero fees). 76. No other chain combines such a strong team and long-term vision where every product meets extreme security and UX standards like MultiversX does. This is why I see it as the โ€œnext Appleโ€ in Web3. 77. MultiversX has a new CMO โ€“ Adam Bates, a former CMO at the Cardano Foundation. He was behind the success of Cardanoโ€™s huge marketing campaign and has a very good relationship with Charles Hoskinson. Thanks to him, Beniamin Mincu (the founder of MultiversX) was likely introduced, and now they will probably discuss how both blockchains can help each other, as well as any other potential collaborations we donโ€™t yet know about. This is also extremely bullish. #EGLD is undeniably the most Scalable, Advanced, Secure, and User-friendly L1 supercomputer ever created. Itโ€™s built to SHAPE THE FUTURE. 1) 2) 3) 4) 5) 27/6/2024 - EGLDSqueeze - SUMMARY: HERE IS NO 2ND BEST. EGLD IS ONLY ONE BLOCKCHAIN THAT CAN RULE THEM ALL. โœ… UNLIMITED SCALING โœ… SCARCE AS BTC โœ… PROGRAMMABLE AS ETH โœ… NO DOWNTIME AS SOL โœ… UI/UX OF Apple โœ… SHARDING DONE BEFORE NEAR & TON โœ… BEST WALLET xPortal WITH GUARDIAN Price prediction (NFA|DYOR): My reasoning is that the real market cap as of December 23, 2024...if we take into account the value of other cryptocurrencies such as BTC, SOL, ETH, AVAX, NEAR, TON, Cardano, BNB, XRP, and so forth, plus the existence of meme coins with valuations above 20 billion USD, or even games nobody plays anymore that still have valuations above 800 million shows that EGLDโ€™s current market cap of approximately 942 million USD is incredibly low. From a technological standpoint, user experience, and other relevant aspects, compared to SOL, NEAR, TON, AVAX, and other L1 protocols, EGLDโ€™s market cap should realistically be around 100 billion USD. Therefore, my prediction and investment thesis is a minimum of a 100x increase from its current price (+-SOL marketcap). MultiversX is ready to onboard 1 billion people to the blockchain. From a long-term perspective, it could even reach a market cap of 1 trillion USD, which is roughly half of where BTC is right now. That would be approximately a 1060x gain from the current market cap. 1 EGLD (MultiversX) is for $34 (only 31.4M max supply) think about this. Not financial advice. Again. There is no 2nd best L1. Position yourself where the puck is going, then wait at the goal until the goal gets there Apes together, strong. Ape alone, weak. We Don't Worry. We Just Win. Shape The Future

Daniel Veroc

50,029 gรถrรผntรผleme โ€ข 1 yฤฑl รถnce

CANCEL Your Weekend Plans and Learn Vibe Coding Today, Start Making $10,000/Month Building Apps for People. $0 in Coding Experience. I made 5 AI Trading Bots & Apps Built in 6 Hours. Each One Worth $3,000-$15,000 to Clients. You Spent $500 on a Bootcamp and Still Can't Deploy a Landing Page. That's not the bootcamp's fault. That's you. People with zero coding skills are building full apps with payments, databases, and authentication using AI. Charging clients $5,000-$10,000 per project. Finishing in one afternoon. You're still Googling "should I learn Python or JavaScript first." This attached video is a goldmine. 6 hours. 5 real apps. From complete beginner to deploying revenue-generating products. One video. Free. Save it. Watch it this weekend. Not next weekend. Today. Now let me break down exactly what's inside and why you can't afford to ignore this. Save this post. You'll hate yourself if you lose it. โ†“ Let's talk about why you still can't code... You bought the Udemy course. $12.99. Watched 3 lectures. Got confused. Told yourself you'd continue tomorrow. That was 8 months ago. You bought another course. $49.99. This one had better reviews. Watched the intro. Bookmarked the rest. Never opened it again. You signed up for a bootcamp. $5,000. Dropped out at week 4 because "life got busy." Life didn't get busy. You got scared. Three years. Hundreds of dollars. Multiple courses. Zero apps built. Zero projects deployed. Zero revenue generated. And now someone with zero coding experience is building full apps in hours using AI tools you haven't even tried. You're not falling behind slowly. You're falling behind at full speed. Save this post right now. This is the course that makes every other coding course you bought irrelevant. Follow Himanshu Kumar so you don't miss the breakdown. โ†“ What is vibe coding and why should you care? Traditional coding: Learn syntax for 6 months. Build a to-do app. Feel proud. Realize nobody will pay for a to-do app. Give up. Vibe coding: Describe what you want to build. AI builds it. You guide, adjust, deploy. People pay for it. You're not writing code line by line. You're directing an AI agent that writes code for you. Think of it like this: Traditional coding = you're the construction worker. Vibe coding = you're the architect. The architect makes more money. The architect doesn't carry bricks. The architect doesn't need to know how to pour concrete. The architect needs to know what to build and why. That's vibe coding. And while you've been debating whether to learn Python or JavaScript first, people are skipping both and building apps that generate revenue. With zero coding knowledge. This isn't the future. This is right now. Save this post and follow Himanshu Kumar for more vibe coding breakdowns that actually make you money. โ†“ What this 6-hour course covers. This isn't some 20-minute tutorial that shows you how to make a button change color. This is 6 hours. 5 complete apps. Real software engineering. Real deployment. Real money-making potential. Here's what you'll build: > Portfolio website - deployed live on Netlify > Full-stack client dashboard - with database and auth > Lead generation app - with API integrations > Thumbnail generator - with payment integration via Stripe > Splinter - a full SaaS product with pricing and marketing Not toy projects. Not "follow along and never use again." Actual apps that people pay for. Built with Gemini 3.1 Pro, Antigravity, Supabase, Next.js, Vite, and more. You know how many people charge $5,000+ to build a single one of these apps for a client? You'll be able to build all 5 by the end of this weekend. You can't afford to scroll past this. Bookmark this post. Follow Himanshu Kumar because I'm breaking down every tool in this stack separately. โ†“ The tools you'll master. Gemini 3.1 Pro: Google's most powerful AI model. You'll use it to generate entire codebases. Not snippets. Entire apps. Antigravity: The AI coding environment that makes vibe coding actually work. Agent chat. MCP servers. Voice dictation. It's not VS Code with a chatbot bolted on. It's built from the ground up for AI-first development. Supabase: Your backend. Database. Authentication. All set up in minutes. Not weeks of configuration. Next.js + Vite: Modern frameworks that make your apps fast, scalable, and professional. Stripe: Payment integration. So your apps can actually charge people money. You know, the whole point. Claude Code: Yes, Claude Code is covered too. Because the best developers in 2026 don't use one AI tool. They use all of them. While you're still trying to decide which AI tool is "the best one," smart people are using all of them together and making money from every angle. Stop debating tools. Start using them. Save this post and follow Himanshu Kumar for deep dives into each of these tools. โ†“ What you'll actually learn beyond just "building apps." This course doesn't just teach you to copy and paste prompts. You'll learn real software engineering: > Hosting and deployment > Modern software design patterns > Languages and frameworks > Version control and GitHub > Programming with AI agents and agent teams > Database design (SQL vs NoSQL) > Security audits > API integration > Payment processing This is everything a $15,000 bootcamp teaches. In 6 hours. For free. On YouTube. Your friend who spent $15K on a bootcamp is going to be really upset when you build better apps than them after watching one YouTube video this weekend. Don't tell them about this course. Or do. Their reaction will be priceless. This is a $15,000 education for $0. Save this post before it gets buried. Follow Himanshu Kumar for more free resources that make paid courses look like scams. โ†“ The guy teaching this actually makes money. Not "makes money selling courses about making money." Actually makes money. Nick built automated businesses with Make . Most notably 1SecondCopy, a content company that hit 7 figures. Seven figures. From automation. He's not teaching theory. He's showing you what real systems that generate real revenue look like. 90% of coding teachers on YouTube have never shipped a product that made $1. They teach coding. They don't use coding to make money. This guy does both. That's why this course is different. You've been learning from people who teach for a living. Start learning from people who build for a living. Save this post. Follow Himanshu Kumar for more content from builders, not lecturers. โ†“ Let me tell you what's really happening while you "think about learning to code." Every week that passes, AI coding tools get better. Every week that passes, more people learn vibe coding. Every week that passes, the market gets more competitive. Right now, vibe coding is still early. Not many people know how to do it well. Clients are desperate for someone who can build apps fast. $3,000 for a landing page with payments. $5,000 for a SaaS MVP. $10,000 for a full client dashboard. These are real prices people are charging for apps they built in a single day using the exact tools in this course. But this window won't last forever. In 6 months, everyone will know how to vibe code. In 12 months, it'll be a basic requirement. In 24 months, not knowing this will be like not knowing how to use email in 2010. You're either early or you're irrelevant. Right now you can still be early. But not if you spend this weekend on Netflix. The window is closing. Every weekend you waste is a weekend someone else uses to get ahead of you. Save this post. Follow Himanshu Kumar before this opportunity becomes obvious to everyone. โ†“ The 5 apps you'll build and what they're actually worth. App 1: Portfolio Website. What clients pay for this: $500-$2,000. Time to build with vibe coding: 30 minutes. App 2: Client Dashboard. What clients pay for this: $5,000-$15,000. Time to build with vibe coding: 2-3 hours. App 3: Lead Generation Tool. What clients pay for this: $3,000-$8,000. Time to build with vibe coding: 1-2 hours. App 4: Thumbnail Generator with Payments. What clients pay for this: $2,000-$5,000. Or sell it as a SaaS for recurring revenue. Time to build: 1-2 hours. App 5: Splinter (Full SaaS Product). What clients pay for this: $10,000-$25,000. Or launch it yourself for monthly recurring revenue. Time to build: 2-3 hours. Total value of apps you can build after this course: $20,000-$55,000. Total cost of this course: $0. Total time investment: one weekend. You spend more than one weekend deciding which Netflix show to start next. At least this weekend would pay you back. Read those numbers again. Save this post. Follow Himanshu Kumar because I'll be breaking down how to sell each of these apps as a service. โ†“ Here's the business model nobody's talking about. Learn vibe coding this weekend. Build 5 apps. Pick the one you're best at. Offer it as a service. "I build professional SaaS dashboards for businesses using AI. Faster than agencies. Fraction of the cost. $5,000 per project." 2 projects per month = $10,000/month. Working maybe 20 hours total. While you're applying for jobs that pay $4,000/month and require 5 years of experience you don't have, someone who watched this course last weekend just landed their second $5,000 client. No degree. No portfolio. No 5 years of experience. Just the ability to build what people need faster than anyone else. That's the entire business model. Learn fast. Build fast. Charge accordingly. Stop applying for jobs. Start creating them. Save this post. Follow Himanshu Kumar for the exact outreach scripts to land your first vibe coding client. โ†“ Why you won't watch this course. Because it's 6 hours. "6 hours?? That's too long." You binged an entire season of a show last weekend in 8 hours. You scrolled Twitter for 4 hours yesterday. You spent 3 hours watching YouTube shorts that you don't even remember. But 6 hours to learn a skill that could make you $10,000/month? "I don't have time for that." You have time. You just don't have discipline. And that's the actual reason you're broke. Not the economy. Not the market. Not your circumstances. Your inability to sit down for 6 hours and learn something that changes your life. Everything else is a story you tell yourself to feel better about doing nothing. That's the uncomfortable truth. Save this post so it stares at you every time you open your bookmarks. Follow Himanshu Kumar because I'll keep reminding you until you actually do something. โ†“ What happens this weekend determines your next year. Path A: Watch the course Saturday. Build your first app Sunday. Start offering services Monday. Land first client within 2 weeks. $5,000-$10,000/month within 60 days. Path B: Sleep in Saturday. Brunch Sunday. Netflix Sunday night. Monday morning alarm goes off. Back to the same job. Same salary. Same frustration. Same "I'll start next weekend." 52 weekends in a year. How many have you already wasted? Path A costs you one weekend. Path B costs you your entire future. Same video. Same information. Same 6 hours. Two completely different lives. โ†“ Full 6-hour course attached. 5 real apps. Real deployment. Real revenue potential. From the guy who built a 7-figure automated business. Not theory. Not motivation. Actual hands-on building. The course is free. The tools are free. The knowledge is right here. The only thing that costs money is your decision to do nothing. And that cost compounds every single day. Follow Himanshu Kumar for more breakdowns that turn free YouTube videos into $10,000/month skill sets. Save this post. Watch the video. Build something this weekend that your Monday self will thank you for. Or don't. And wonder next year why nothing changed.

Himanshu Kumar

39,379 gรถrรผntรผleme โ€ข 3 ay รถnce

Made $313 โ†’ $2,382,780 in 4 Days Using a Claude AI Bot on Polymarket. 26,738 trades. 98% win rate. Full blockchain proof. Every single trade verifiable on-chain. I've made the exact step-by-step guide to build this Claude Polymarket bot from scratch. You've been trading for 3 years. Still red. He gave Claude $313. Woke up rich. Free for 24 hours. To get this Setup guide: 1. Comment "Money" 2. Like and Retweet 3. Follow me Himanshu Kumar (so i can DM you) Full 2-hour video tutorial attached. Every single click and command explained. Beginner to running bot. Now let me break down exactly how this works. Save this post. This is the most important trading breakdown you'll ever read. โ†“ Let's start with the number that should make you sick. $313. That's what this wallet started with. Not $50,000. Not $10,000. Not even $1,000. $313. Less than your monthly Netflix + Uber Eats + Spotify combined. 4 months later: $2,382,780.80. That's a 7,942x return. While you spent those same 4 months staring at charts, drawing trendlines, panic selling, revenge trading, and ending the month exactly where you started. Minus the $200 you lost on that "sure thing." Same 4 months. Same market. Same opportunities. He had a bot. You had feelings. Guess who won. Save this post right now. What I'm about to explain is the exact mechanism behind every dollar of that $2.38M. Follow Himanshu Kumar so you don't miss the rest. โ†“ How Polymarket actually works and why bots print money on it. Polymarket is a prediction market. Will BTC be higher in 15 minutes? Yes or No. Will the Fed raise rates? Yes or No. You buy shares between $0 and $1. If you're right, your share settles at $1. If you're wrong, it settles at $0. Simple. Now here's where it gets interesting. Polymarket updates its prices SLOWER than the real market moves. When BTC drops 0.6% on Binance, Polymarket still shows old odds for about 2.7 seconds. 2.7 seconds. In those 2.7 seconds, the bot already knows the outcome. It's not predicting. It's not guessing. It's reading information that already exists and trading before Polymarket catches up. That's not trading. That's collecting free money with a 2.7 second head start. And you're over there using a 15-indicator TradingView setup trying to "predict" where BTC goes next. The bot doesn't predict anything. It just reads faster than you. That's the entire edge. Save this post because if you understand this one concept you understand how millionaires are being made on Polymarket right now. Follow Himanshu Kumar for more breakdowns like this. โ†“ Let me walk you through one single trade. A new 15-minute BTC contract opens on Polymarket. Odds are 50/50. Fair price. 10 minutes in, BTC drops 0.6% on Binance. Hard, fast move. The real probability of BTC being lower at expiry is now about 78%. Polymarket still shows 54/46. The bot sees this instantly. Binance WebSocket feed. Under 50ms latency. The edge is 24 percentage points. On a binary contract, that's basically free money. Bot calculates position size using Kelly Criterion. Executes via Polymarket's API. Done. Within 2-3 seconds, other participants update the odds. 54/46 moves toward 78/22. Bot either exits for immediate profit or holds to resolution. Either way, the trade was entered with near-certainty of a positive outcome. Now repeat this 200-500 times per day. $313 โ†’ $2,382,780 in 4 months. Not magic. Not prediction. Not luck. Industrial-scale exploitation of a market inefficiency that still exists today. And you're still placing one manual trade per day and calling yourself a "trader." This is the mechanism behind every single dollar. Bookmark this post so you can study it again. Follow Himanshu Kumar because I'm breaking down each strategy separately. โ†“ There are 4 strategies. Not all Claude bots do the same thing. Strategy 1: Latency Arbitrage. Win rate: 85-98%. What 0x8dxd used. Monitor Binance price feeds. When Polymarket odds lag behind reality by 3-5%, buy the correct side before the market corrects. No forecasting. No model. No sentiment analysis. Pure speed. You're not guessing. You're reading an outcome that has already happened. Strategy 2: Oracle Arbitrage. Win rate: 78-85%. Chainlink oracle price feeds occasionally diverge from Polymarket's implied prices. When they do, the settlement direction is known. Fewer opportunities. Higher certainty when they appear. Strategy 3: News-Driven Trading. Win rate: 60-75%. Claude ingests real-time news. Government filings. Central bank statements. On-chain data. Assesses probability impact before retail traders even finish reading the headline. Lower win rate because interpretation introduces uncertainty. But works on ANY market category, not just crypto. Strategy 4: Market Making. Return: 2-5% per month. Place buy and sell orders on both sides. Capture the spread. No prediction required. Most consistent. Hardest to blow up. Compounds aggressively over time. You didn't even know there were 4 strategies. You thought "trading bot" meant one thing. That's how far behind you are. 4 strategies. 4 different risk profiles. 4 ways to make money while you sleep. Save this post. Follow Himanshu Kumar for the deep dive into each one. โ†“ The timeline that should haunt you. December 2025: Bot launches with $313. Nobody notices. January 6, 2026: Wallet hits ~$438,000. 140x in 30 days. 6,615 predictions. 98% win rate. Finbold reports it. Crypto Twitter explodes. March 10, 2026: Head-to-head test. Claude bot: $1,000 โ†’ $14,216 in 48 hours. +1,322%. OpenClaw bot: fully liquidated. Same market. Same timeframe. Claude won because of better risk management. OpenClaw died because it overleveraged. March 16, 2026: Someone trains a swarm model on 3 years of NBA data. Result: +$1.49M on Polymarket. April 2026: 0x8dxd final verified balance: $2,382,780.80. 26,738 trades. 4 months. This all happened while you were "waiting for the right time to start." The right time was December 2025. The second best time is right now. But you'll probably wait until it's too late. That's what you always do. Every date on this timeline is a day you could have started but didn't. Save this post. Follow Himanshu Kumar so you at least start today. โ†“ Why Claude and not ChatGPT? This isn't opinion. It's data. March 2026 head-to-head: Claude bot: +1,322%. OpenClaw (GPT-based): liquidated. Same prompt. Same market. Same conditions. Researchers found Claude's code included: > More defensive edge cases > More conservative default parameters > Better error handling > More legible code for debugging > Proper Kelly Criterion position sizing > Hard drawdown kill switches ChatGPT's code overleveraged into a losing sequence and couldn't recover. Claude's code sized positions conservatively, stopped trading when drawdown thresholds hit, and survived to compound another day. The difference between +1,322% and liquidation wasn't the strategy. It was the risk management. And Claude writes better risk management than ChatGPT. That's not a debate. That's a $15,216 difference in 48 hours. But sure, keep using ChatGPT because "everyone uses it." Everyone's broke too. Coincidence? Stop using the popular tool. Start using the profitable one. Save this post. Follow Himanshu Kumar for more Claude vs ChatGPT comparisons with real data. โ†“ Why humans lose to bots. Every single time. Same strategy. Same market. Same period. Bots: ~$206,000 profit. Humans: ~$100,000 profit. 2x gap. Same strategy. Here's why: 1. Late entries. By the time you identify the lag, verify your reasoning, and click buy, the 2.7 second window is gone. The bot executes in under 100ms. You execute in 30 seconds. The opportunity doesn't exist for 30 seconds. 2. Emotional sizing. You oversize when "confident." Undersize when scared. Exact opposite of Kelly math. The bot sizes based on edge. Every time. No feelings. 3. Fatigue. You make worse decisions at hour 6 than at hour 1. The bot makes the same decision at hour 72 that it made at hour 1. 4. Drawdown psychology. After 3 losses you either panic quit or double down trying to recover. Both destroy capital. The bot has a kill switch. It stops. It doesn't feel anything. You're not competing with other humans anymore. You're competing with machines that don't sleep, don't feel, don't flinch. And you're losing. The data doesn't lie. Humans lose to bots 2x on the same strategy. Save this post. Follow Himanshu Kumar for the complete bot setup that removes you from the equation. โ†“ What can go wrong. Because I'm not going to lie to you. Most people who build this bot will NOT 7,942x their money. Some will lose their initial capital. Here's what can kill you: Edge compression. The arbitrage window was 12 seconds in 2024. It's 2.7 seconds now. It's shrinking. At some point it hits zero for retail operators. This is a time-limited opportunity. Not a permanent income stream. Rule changes. Polymarket can change contract mechanics, settlement rules, or API terms overnight. What worked yesterday can lose money tomorrow. Risk management bugs. A 98% win rate strategy with broken position sizing will blow up your account on the one losing trade. The March 2026 experiment proved this. Claude survived. OpenClaw got liquidated. Same strategy. Different risk management. That's why the 2-hour video tutorial walks through every single risk parameter. Because the strategy doesn't kill you. Bad risk management kills you. This is the section most "gurus" delete. I'm keeping it because I'd rather you make money safely than blow up and blame me. Save this post. Follow Himanshu Kumar for honest breakdowns, not hype. โ†“ The step-by-step to build your own. Step 1: Set up a Polymarket wallet. Fund with USDC via Polygon network. Start with $100-$300 for testing. Step 2: Generate API credentials. CLOB API key from docs.polymarket .com. Store private key in environment variable. Never hardcode it. Never share it. Step 3: Prompt Claude to build the bot. Use Claude Code for best results. It reads your filesystem, executes code, and iterates on errors autonomously. Step 4: Paper trade for at least one week. Minimum 200 completed trades. Win rate must be above 70% before going live. This step is NOT optional. Step 5: Configure risk management. Max single position: 8% of portfolio. Daily loss limit: -20% with auto halt. Kill switch at -40% drawdown. Telegram alerts on every threshold. Step 6: Go live small. $1-5 per trade. Watch every trade for first week. Compare to paper results. Scale only on evidence. Skip steps 4 and 5 and you will lose your money. That's not a warning. That's a guarantee. This is your complete build guide. Save this post. Follow Himanshu Kumar because I'll be posting the exact Claude prompts for each strategy. โ†“ The edge exists right now. Not next month. Not "when you're ready." Right now. The arbitrage window is 2.7 seconds. It was 12 seconds in 2024. It's shrinking every week. Every day you wait, more bots enter the space. The window gets smaller. Your potential returns get smaller. The bots already running have a compounding advantage. They're making money today that they'll use to make more money tomorrow. You're reading about it and telling yourself "I'll look into this next weekend." That's what you said last weekend. And the weekend before that. The best time to start was 6 months ago. The second best time is today. But you already know you're going to bookmark this and never open it again. Prove me wrong. โ†“ Full 2-hour video tutorial attached. Every single click. Every command. Every parameter. From zero to running bot. Beginner friendly. Nothing skipped. A similar bot has already earned $2,382,780. Full blockchain proof in the article below. The video is free. The tools are free. The edge still exists. The only thing that costs money is another month of doing nothing while bots eat every opportunity you're too slow to catch. Follow Himanshu Kumar for the complete series covering every automated income stream using Claude. Prediction markets are just the beginning. Save this post. Bookmark it. Screenshot it. Whatever you need to do so you actually watch the video and build the bot instead of just reading about people who did. You Must Follow me Himanshu Kumar, so i can send you DM.

Himanshu Kumar

52,808 gรถrรผntรผleme โ€ข 3 ay รถnce

$AMD| The FOMO to buy AMD Chips is NOW ๐Ÿงต Not Financial Advice! DYOR! Research Purpose Only! The Inference Queen is the biggest winner in Agentic AI where all other CPUs are struggling to compete with a 2yr old EPYC Turin and EPYC Venice is in mass production phase. AMD stresses deployability today on standard x86 platforms (no proprietary architectures required), full software compatibility, and open standards. This positions Venice + Helios as a practical, high-density alternative to competing solutions while underscoring that agentic AI shifts the balance toward CPU-rich racks alongside GPUs, and most importantly, lowering the cost of token to accelerate adoption and innovation. Context: The Wall Street Journal yesterday came out with an article that OpenAI is condiering drasstically lowering the token prices to win more customers from Anthropic. The narrative "they" are trying to exacerbate the current AI selloff won't last long. This is a fundamental misunderstanding of what is going on, or what I already discussed for months and years. Followers and Subscribers already knew this for years, that this day would come, where token cost will bcome the central discussion among enterprises as there is no such thing as unlimited budget or Tokenmaxxing when they use $NVDA chips or In-house Hyperscalers chips. I will link various threads if you are interested in understanding the full picture from supply chain to recent TSMC Rapid 2nm expansion up to 12 Fabs total by 2027/2028. Hyperscalers and AI natives effectively have no choice but to buy more AMD system for Agentic AI as leadership in economical, power-aware, high-volume internal + agentic use. However, due to supply constraints where Supply is far behind Demand, this makes multi-vendor reality along with in-house chips drive faster industry progress, lower overall costs, and better sustainability. NVIDIAโ€™s Vera Rubin cannot compete with a 2 years old EPYC Turin, but AMD under Dr. Lisa Su has engineered the lowest cost-per-million-tokens, highly competitive energy-efficient solutions, and superior CPU orchestration for agentic AI at scale with Helios. Dr. Su has championed this shift since at least 2023, foreseeing the rise of agentic workflows that demand far more orchestration, parallel agents, and balanced compute well before the industry fully embraced it. Her long-term vision of AI moving from simple prompts to always on, multi-agent systems has driven AMDโ€™s investments in high-core EPYC CPUs and integrated rack-scale solutions, perfectly positioning the company for todayโ€™s realities. The OpenAI-AMD 1GW Helios deployment (starting H2 2026) represents a pivotal vertical integration move that directly supercharges the inference economics. This isn't incremental; it's a structural shift toward ownership of massive, optimized rack-scale capacity, enabling the lowest token costs and triggering the enterprise adoption flywheel. We need to be honest, $AMD is the only company that made a big bet on Inference since the day Chatgpt became sensational where $NVDA and others were betting big on Training. At the end of the day, Token bill from Anthropic has to obey economics. Meaning the bills rise, companies have to get more out of it to justify the cost. It cannot be an unlimited inference budget, and it has to show up on efficiency, profitability and operating leverage. 1. Tokenomics After you understand this, you will understand why Citi cited Anthropic is likely to sign a deal with $AMD along with Hyperscalers, AI Labs, Sovereign AI like Softbank 5GW in France and many other countries. However, OpenAI and $META are now wanting faster deployment, and they are AMD shareholders now, they have prioritized allocation. Anthropic and Hyperscalers just cannot compete when Helios Rack lower token cost to$0.0003โ€“$0.0005 per million tokens at GW scale. Cost to build 1GW data center 1GW Helios Rack full build is estimated $30-$35B 1GW Rubin Rack full build is estimated $45-$55B Inference (Cost per Million Tokens) ~$NVDA B200 / HGX: ~$0.02โ€“$0.08 on optimized workloads (FP4/MXFP4, speculative decoding). Significant improvement over Hopper but still premium-priced. GB200 NVL72 rack-scale: $0.05โ€“$0.25+ ~$AMD Helios Racks: $0.0003-$0.0005 per M tokens, dramatically lower than NVIDIA equivalents in owned infra. MI355X node-level: Up to 40% more tokens per dollar vs. competing solutions ( B200), driven by higher memory capacity (up to 288GB+ HBM), strong bandwidth, and lower acquisition costs. Training ~$NVDA Rubin Rack is estimated $0.7-$1.2/M Tokens ~$AMD Helios Rack is estimated $0.65-$1.0/M Tokens Now, OpenAI, META and Hyperscalers can lower Inference cost even further with $AMD EPYC Venice "dense rack" or Agentic AI Rack. AMD published a detailed technical blog emphasizing that the future of agentic AI autonomous, multi-step AI systems requiring heavy orchestration, databases, caching, APIs, and control planes demands massive CPU-dense rack-scale infrastructure, not just GPUs. The catalyst prominently positions their upcoming 6th Gen EPYC "Venice" processors as the key enabler for next-generation dense racks, delivering leadership throughput under real-world power, cooling, and density constraints. ~EPYC Venice (Zen 6 architecture, up to 256 cores / 512 threads per socket) is projected to deliver exceptional rack-level performance. In AMDโ€™s modeled 100 kW rack comparisons, Venice-powered systems are expected to achieve ~3.30x the throughput of NVIDIAโ€™s Vera (88-core Olympus) baseline across a broad mix of agentic-supporting workloads. ~This builds on current-generation 5th Gen EPYC "Turin" (up to 192 cores), which already delivers ~2.37x rack throughput vs. Vera and ~1.6x vs. Intelโ€™s Xeon 6980P (128 cores). ~ Liquid-cooled Turin deployments already support >27,000 CPU cores per rack today. Venice is architected to push this beyond 36,000 cores in the same rack class, dramatically increasing concurrent agent capacity and overall infrastructure efficiency. 2. Ownership vs renting compute from Hyperscalers matter to OpenAI and only owning $AMD chips can meaningfully lower token cost for enterprises. ~Eliminates cloud overhead: No provider margins, utilization buffers, or egress fees. Direct control over power contracts, cooling, scheduling, and orchestration at dedicated facilities. ~Helios optimizations at GW scale: Rack-level density (1.4+ exaFLOPS FP8 per rack), high HBM4 bandwidth, EPYC orchestration for agentic workloads, and superior TCO/TDP. AMD's long-standing focus on tokens per dollar/watt shines here 20-40%+ efficiency edges in inference-heavy scenarios. ~At 1GW+ optimized deployment, inference hits $0.0003โ€“$0.0005 per million tokens (community/analyst models tied to Helios metrics). This is dramatically lower than typical rented/cloud equivalents, especially for high-volume output tokens in agentic flows. High token bills today, enterprises running heavy agentic/coding/analysis workloads can face $50-100M+/month at current API rates (flagship models $5-30+/M output, scaled to massive volumes). Post-Helios compression, same volume will drop to $10-15M/month (or better) via lower underlying costs passed through as pricing flexibility, volume tiers, caching, or batch discounts. ROI thresholds collapse. More companies greenlight pilots โ†’ production โ†’ massive scaling. Agentic AI (autonomous workflows) multiplies token demand exponentially, but affordability removes the friction. OpenAI gains flexibility, Unlike more cloud-dependent rivals (Anthropic), they can lower effective pricing, offer aggressive enterprise bundles, or absorb volume without margin destruction directly tackling "high token bill" complaints while maintaining profitability as usage explodes. 3. Agentic AI Models shifted CPU:GPU Ratio to 1:1 toward 3-5:1 with Explosively Token-Hungry Workloads Agentic AI (autonomous, multi-step agents with planning, tool use, iteration, and self-correction) is fundamentally more compute and token intensive than conversational or single-turn generative AI. Agentic AI. autonomous, multi-step workflows with orchestration, tool use, parallel agents, data movement, and enterprise integration has dramatically increased the importance of strong host CPUs alongside GPUs. This shifts the CPU-to-GPU ratio higher and makes balanced systems critical toward 1:1 to 5:1 as enterprises testing more than 5-10 agents. AMD EPYC Venice excels ~Leadership core density (up to 256 Zen 6 cores per socket) for running many agents in parallel, orchestration layers, and high-throughput control-plane tasks. ~Superior performance-per-core and power efficiency ( up to 2.1x higher perf/core and 2.26x better SPECpower vs. NVIDIA Grace in benchmarks). ~Tight integration in Helios: One Venice CPU + multiple MI450 GPUs per node, enabling efficient data feeding to GPUs ("zero-copy"), parallel execution, and full rack utilization for complex agentic loops. Hyperscalers (Meta, Microsoft, Amazon, Google, Softbank) and AI natives (OpenAI, Anthropic...) are adopting high-core EPYC at scale specifically for these agentic demands, as CPUs now handle a larger share of non-model work (orchestration, policy enforcement, tool calls). This complements AMDโ€™s lower-cost GPUs for overall TCO wins. ~Agents often generate 10โ€“100x+ more tokens per task due to iterative reasoning chains, multiple tool calls, verification loops, and long-context orchestration. ~Goldman Sachs forecasts token consumption multiplying 24x by 2030 (to 120 quadrillion tokens/month) largely driven by agentic adoption in consumer and enterprise. ~Enterprise data shows agent-pattern workloads growing at 680% annualized rates, projected to surpass conversational AI in token volume by Q3 2026. ~Daily enterprise agent token consumption is already in the billions, with complex workflows (coding, workflows, analysis) amplifying this dramatically. 4. Competitive Edge: Winning Customers from Anthropic Anthropicโ€™s Claude models (especially Opus/Sonnet) excel in complex reasoning and agentic coding, commanding premium positioning. However, their higher underlying costs (heavier reliance on third-party cloud with margins) limit pricing flexibility compared to OpenAIโ€™s owned Helios capacity. Anthropic is on track to generate $10.9 billion in Q2 revenue. The company expects to achieve its first-ever quarterly adjusted operating profit of $559 million. However, sustaining full-year profitability remains challenging due to immense computing and model training costs The truth is, Anthropic has no choice but to buy as much $AMD chips as possible if they want to compete with OpenAI or get investors attention. This 5% adjusted operating profit to revenue ratio is just pathetic. Current pricing dynamics (2026): OpenAI already undercuts on many tiers ( flagship output tokens significantly cheaper than equivalent Claude Opus). Nano/mini models offer 5โ€“10x advantages for volume work. Anthropic holds edges in long-context flat pricing and certain reasoning quality. OpenAI after Helios Rack Ownership, At $0.0003โ€“$0.0005/M effective costs, OpenAI gains massive headroom to: ~Aggressively discount high-volume agentic tiers or bundles. ~Offer โ€œunlimitedโ€ enterprise plans or usage-based models that Anthropic struggles to match without margin erosion. ~Target cost-sensitive, high-throughput agent deployments (dev tools, automation platforms) where token bills explode. Enterprises facing $ millions in monthly agentic bills will migrate to the provider delivering better economics at scale. OpenAIโ€™s combination of strong models (o-series reasoning) + lowest TCO positions it to erode Anthropicโ€™s enterprise share, especially as agentic becomes the dominant token consumer. Cheaper tokens expand the total addressable market dramatically. This feeds the data/model improvement loop, justifying further capex. AMD benefits from proven scale pulling in more customers (Meta, Oracle, Microsfot, Amazon, Softbank, TensorWave, LumaAI ... already aligned on Helios). Conclusion: Dr. Lisa Su has been laser focused on inference economics since at least 2022โ€“2023, repeatedly emphasizing that the real battleground for AI scalability would be TCO, power efficiency (TDP), and ultimately tokens per dollar and per watt not just raw training FLOPS. While many viewed inference as a secondary, commoditized workload, Dr. Su architected AMDโ€™s roadmap around rack-scale systems optimized for high-volume, sustained inference that would dominate as models matured and usage exploded. Helios represents the culmination of that multi-year bet: a fully integrated, open platform designed precisely for the economics of massive token throughput. This deep, strategic partnership with OpenAI starting with the 1GW Helios deployment in H2 2026 and scaling to 6GW, is the embodiment of that shared vision. Both companies foresaw a future where agentic AI models evolve to become extraordinarily token-hungry: autonomous agents executing complex, iterative workflows with planning, tool use, verification loops, and long-context reasoning. These workloads can consume 100x+ more tokens per task than traditional chat or single-turn generation, driving exponential demand as capabilities improve and enterprises deploy them at scale. By owning and optimizing this massive Helios capacity at GW scale, OpenAI achieves inference costs as low as $0.0003โ€“$0.0005 per million tokens. This structural cost advantage allows OpenAI to absorb the coming token explosion profitably, dramatically lower effective pricing for enterprises, and win high-volume agentic workloads from higher-cost competitors like Anthropic. What was once a prohibitive monthly token bill becomes an affordable accelerator for productivity and innovation. The OpenAI-AMD alliance validates Dr. Suโ€™s prescient strategy and turns the Agentic flywheel into reality: Collapsing inference costs โ†’ explosive token consumption โ†’ richer data and better models โ†’ accelerate greater demand. This partnership doesnโ€™t just address todayโ€™s economics, it positions both leaders at the center of the infrastructure buildout that will power AIโ€™s next decade. By delivering the lowest inference economics at scale, OpenAI not only solves enterprise bill pain but gains a decisive weapon to win share from higher-cost rivals like Anthropic. And that is why OpenAI and $META will deploy EPYC Dense Rack Not Financial Advice! DYOR! Research Purpose Only!

Mike

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