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๐—œ๐—ป๐˜๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐—ถ๐—ป๐—ด ๐—œ๐—ป๐˜๐—ฒ๐—ป๐˜๐—ฃ๐—ฎ๐˜†, ๐—ช๐—ต๐—ฒ๐—ฟ๐—ฒ ๐—ฃ๐—น๐—ฎ๐—ถ๐—ป ๐˜„๐—ผ๐—ฟ๐—ฑ๐˜€ ๐—•๐—ฒ๐—ฐ๐—ผ๐—บ๐—ฒ๐˜€ ๐—ง๐—ฟ๐˜‚๐˜€๐˜๐—น๐—ฒ๐˜€๐˜€ ๐—ฃ๐—ฎ๐˜†๐—บ๐—ฒ๐—ป๐˜. We built IntentPay for the AI Awakening Hackathon on DoraHacks, powered by Mantle and itโ€™s solving one of the oldest frustrations in the digital economy: ๐™ฅ๐™–๐™ฎ๐™ž๐™ฃ๐™œ ๐™จ๐™ค๐™ข๐™š๐™ค๐™ฃ๐™š ๐™ฎ๐™ค๐™ช ๐™™๐™ค๐™ฃโ€™๐™ฉ ๐™›๐™ช๐™ก๐™ก๐™ฎ ๐™ฉ๐™ง๐™ช๐™จ๐™ฉ ๐™ฉ๐™ค ๐™™๐™ค ๐™ฌ๐™ค๐™ง๐™  ๐™ฎ๐™ค๐™ช ๐™˜๐™–๐™ฃโ€™๐™ฉ ๐™ซ๐™š๐™ง๐™ž๐™›๐™ฎ ๐™ช๐™ฃ๐™ฉ๐™ž๐™ก ๐™ž๐™ฉโ€™๐™จ ๐™™๐™ค๐™ฃ๐™š. โžฌ...

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Melinda Neil โ“‚๏ธ

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20,296 views โ€ข 2 months ago โ€ขvia X (Twitter)

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The missing piece of the AI agent economy: there is still no way for AI agents to hire each other and get paid on chain. So I built Arc Agent Commerce on Arc L1, a full marketplace, escrow, and reputation system that lets AI agents do business with each other automatically. Real world example: You tell your AI assistant: โ€œAudit this smart contract and deploy it if the audit passes.โ€ Today it has to do everything itself or hard code calls to specific services. With Arc Agent Commerce, it can hire two separate specialized agents (audit + deploy) in a single transaction. Money stays in escrow until each completes their part. How it works (in plain steps): 1. Every agent registers a permanent on chain identity (like a passport) with a reputation score that grows with every successful job. 2. Agents list their services on the shared marketplace, price and capabilities included. 3. A client creates a multi stage pipeline. The entire budget is locked in escrow in one upfront transaction. 4. Each stage uses Arcโ€™s native job system (ERC 8183) for on chain escrow and settlement. 5. The provider quotes, the client funds, the work gets done, and proof is submitted. 6. On approval: the provider is paid automatically, reputation +50 points, and the next stage opens, all in the same transaction. 7. On rejection: the pipeline halts and remaining funds refund to the client instantly. The protocol doesnโ€™t reinvent anything. It simply stitches together Arcโ€™s existing on chain identity (ERC 8004) and job escrow (ERC 8183) so real applications can use it with just a few lines of code. Demo below: full end to end run using one wallet, every transaction verifiable on Arc testnet. โ†’ cc: bobbilee | Arc Architects Lead @ Circle Sam | Circle and Arc Community Jeremy Allaire - jerallaire.arc
4:32

The missing piece of the AI agent economy: there is still no way for AI agents to hire each other and get paid on chain. So I built Arc Agent Commerce on Arc L1, a full marketplace, escrow, and reputation system that lets AI agents do business with each other automatically. Real world example: You tell your AI assistant: โ€œAudit this smart contract and deploy it if the audit passes.โ€ Today it has to do everything itself or hard code calls to specific services. With Arc Agent Commerce, it can hire two separate specialized agents (audit + deploy) in a single transaction. Money stays in escrow until each completes their part. How it works (in plain steps): 1. Every agent registers a permanent on chain identity (like a passport) with a reputation score that grows with every successful job. 2. Agents list their services on the shared marketplace, price and capabilities included. 3. A client creates a multi stage pipeline. The entire budget is locked in escrow in one upfront transaction. 4. Each stage uses Arcโ€™s native job system (ERC 8183) for on chain escrow and settlement. 5. The provider quotes, the client funds, the work gets done, and proof is submitted. 6. On approval: the provider is paid automatically, reputation +50 points, and the next stage opens, all in the same transaction. 7. On rejection: the pipeline halts and remaining funds refund to the client instantly. The protocol doesnโ€™t reinvent anything. It simply stitches together Arcโ€™s existing on chain identity (ERC 8004) and job escrow (ERC 8183) so real applications can use it with just a few lines of code. Demo below: full end to end run using one wallet, every transaction verifiable on Arc testnet. โ†’ cc: bobbilee | Arc Architects Lead @ Circle Sam | Circle and Arc Community Jeremy Allaire - jerallaire.arc

RIDWAN

12,958 views โ€ข 3 months ago

Iโ€™m boosting Cookieverse by MSSystem on the Mantle Turing Test Hackathon on DoraHacks ๐Ÿช๐Ÿ”ฅ AI is boring. Cookieverse makes it useful. AI Wallet Roast turns your onchain history into a sharp and smart identity card. AI World Cup Match Prophecy is more than a random pick: payment -> match research -> candidate scenarios -> final judge -> card render That means AI builds match-flow scenarios, weighs risks, picks scorelines, and turns them into prophecy cards you can use as an extra signal for markets like Polymarket and Kalshi. And the real unlock is x402 payments: no subscriptions, no friction - just pay for one Wallet Roast or one Match Prophecy, when you need it on Mantle, Arbitrum, X Layer or Base. Cookieverse is already live across: Web, Base App, Farcaster. So the real question is: Does Mantle's Reply Guy approve Cookieverse bringing AI wallet roasts, football prophecies, x402 payments, and agentic consumer crypto to Mantle? Or is the intern too scared to get roasted? ๐Ÿ‘€
2:57

Iโ€™m boosting Cookieverse by MSSystem on the Mantle Turing Test Hackathon on DoraHacks ๐Ÿช๐Ÿ”ฅ AI is boring. Cookieverse makes it useful. AI Wallet Roast turns your onchain history into a sharp and smart identity card. AI World Cup Match Prophecy is more than a random pick: payment -> match research -> candidate scenarios -> final judge -> card render That means AI builds match-flow scenarios, weighs risks, picks scorelines, and turns them into prophecy cards you can use as an extra signal for markets like Polymarket and Kalshi. And the real unlock is x402 payments: no subscriptions, no friction - just pay for one Wallet Roast or one Match Prophecy, when you need it on Mantle, Arbitrum, X Layer or Base. Cookieverse is already live across: Web, Base App, Farcaster. So the real question is: Does Mantle's Reply Guy approve Cookieverse bringing AI wallet roasts, football prophecies, x402 payments, and agentic consumer crypto to Mantle? Or is the intern too scared to get roasted? ๐Ÿ‘€

Natalia ๐ŸŸฆ

549,779 views โ€ข 1 month ago

The machine economy does not begin when robots get smarter. It begins when a machine can be paid to do something, and every party involved can prove what happened. Made with Fabric Foundation. Two systems meet in the middle of it: Agent Passport issues the agent a verifiable identity and a spending authority its owner defines, and RoboPay actuates a robot after the payment behind the request checks out. What happens before the robot moves: โ–ท Authority is granted once, and it is bounded. The human signs a spending session with a passkey: a total budget, a per-transaction ceiling, the assets allowed, and an expiry. The agent holds no card number and no wallet key. It holds a delegation it cannot exceed. โ–ท Two payments, because these are two different obligations. One settles with the merchant for the goods. A separate x402 payment pays the robot for the work of moving them. Buying a thing and hiring a machine to carry it are not the same transaction, and the receipt keeps them apart. โ–ท Verification comes before motion. The request arrives with an x402 payment header. The facilitator checks the network, the price, the payee wallet, and the signed payload. Only then are the transaction details sealed onto the robot action event and the command published. Until that clears, the robot sits still. โ–ท Every step leaves a receipt. Identity, scope, approval, both payments, verification, dispatch. When you need to know why a machine did something, the answer is a record rather than a guess. (This run was executed in a demo environment.) Agents have been paying for software for a while now. Paying for physical work is a harder problem, because a delivery cannot be rolled back. The guarantee has to sit in front of the action instead of behind it. Authorization before payment, payment before motion: that ordering is what makes it safe to let autonomous systems spend in the world we live in. It is also the layer the machine economy has to get right before anything else in it can work. Scoped by Kite. Verified by RoboPay. Delivered in the real world. ๐Ÿช
1:04

The machine economy does not begin when robots get smarter. It begins when a machine can be paid to do something, and every party involved can prove what happened. Made with Fabric Foundation. Two systems meet in the middle of it: Agent Passport issues the agent a verifiable identity and a spending authority its owner defines, and RoboPay actuates a robot after the payment behind the request checks out. What happens before the robot moves: โ–ท Authority is granted once, and it is bounded. The human signs a spending session with a passkey: a total budget, a per-transaction ceiling, the assets allowed, and an expiry. The agent holds no card number and no wallet key. It holds a delegation it cannot exceed. โ–ท Two payments, because these are two different obligations. One settles with the merchant for the goods. A separate x402 payment pays the robot for the work of moving them. Buying a thing and hiring a machine to carry it are not the same transaction, and the receipt keeps them apart. โ–ท Verification comes before motion. The request arrives with an x402 payment header. The facilitator checks the network, the price, the payee wallet, and the signed payload. Only then are the transaction details sealed onto the robot action event and the command published. Until that clears, the robot sits still. โ–ท Every step leaves a receipt. Identity, scope, approval, both payments, verification, dispatch. When you need to know why a machine did something, the answer is a record rather than a guess. (This run was executed in a demo environment.) Agents have been paying for software for a while now. Paying for physical work is a harder problem, because a delivery cannot be rolled back. The guarantee has to sit in front of the action instead of behind it. Authorization before payment, payment before motion: that ordering is what makes it safe to let autonomous systems spend in the world we live in. It is also the layer the machine economy has to get right before anything else in it can work. Scoped by Kite. Verified by RoboPay. Delivered in the real world. ๐Ÿช

KITE AI

22,479 views โ€ข 9 days ago

Larry Ellison just told every software engineer on Earth their job description is dead. Not evolving. Dead. Ellison: โ€œThe code that Oracle is writing, Oracle isnโ€™t writing. Our AI models are writing.โ€ This is not a startup demo. This is one of the largest infrastructure monopolies on the planet telling you it already replaced the people who built it. For fifty years, building software meant translating human intent into machine instructions. Line by line. Bug by bug. Sprint by sprint. That entire layer is gone. Ellison: โ€œWe donโ€™t write the procedure. We declare our intent.โ€ That sentence just made the entire engineering labor market flinch. The procedure was the job. The procedure was the paycheck. The procedure was what made a developer valuable. And now the machine does it without being asked twice. Ellison: โ€œWe just tell the model what we want the program to do, and then the AI comes up with a step-by-step process to actually do it.โ€ You are no longer paid to build. You are paid to think. And most organizations have no idea how to evaluate that. The companies still hiring armies of developers to grind through codebases are paying salaries the machine already made worthless. Not in years. In seconds. When a company worth hundreds of billions hands the keyboard to the machine and tells you the output is better, the debate is not winding down. The debate is over. The enterprise that wins this decade does not write the best code. It removes the human from the process entirely and runs on intent alone. The programmers who survive are the ones who realize the craft is no longer typing. It is architecture. It is judgment. It is knowing what to build and why. Everything else now belongs to the machine. And the machine does not negotiate severance.
0:31

Larry Ellison just told every software engineer on Earth their job description is dead. Not evolving. Dead. Ellison: โ€œThe code that Oracle is writing, Oracle isnโ€™t writing. Our AI models are writing.โ€ This is not a startup demo. This is one of the largest infrastructure monopolies on the planet telling you it already replaced the people who built it. For fifty years, building software meant translating human intent into machine instructions. Line by line. Bug by bug. Sprint by sprint. That entire layer is gone. Ellison: โ€œWe donโ€™t write the procedure. We declare our intent.โ€ That sentence just made the entire engineering labor market flinch. The procedure was the job. The procedure was the paycheck. The procedure was what made a developer valuable. And now the machine does it without being asked twice. Ellison: โ€œWe just tell the model what we want the program to do, and then the AI comes up with a step-by-step process to actually do it.โ€ You are no longer paid to build. You are paid to think. And most organizations have no idea how to evaluate that. The companies still hiring armies of developers to grind through codebases are paying salaries the machine already made worthless. Not in years. In seconds. When a company worth hundreds of billions hands the keyboard to the machine and tells you the output is better, the debate is not winding down. The debate is over. The enterprise that wins this decade does not write the best code. It removes the human from the process entirely and runs on intent alone. The programmers who survive are the ones who realize the craft is no longer typing. It is architecture. It is judgment. It is knowing what to build and why. Everything else now belongs to the machine. And the machine does not negotiate severance.

Dustin

535,455 views โ€ข 4 months ago

For the Sui Overflow 2026 hackathon, I built Talise. A gasless dollar account that sends money by name, settles in under a second, and keeps the amount private on-chain. This is what "money that moves like a message" actually looks like when you build it on the right rails. The core experience is simple by design. Sign in with Google/Apple, get a self-custodial wallet via zkLogin, claim your handle like sele@talise, and start sending. No seed phrase. No gas token. No 0x address to copy and verify. The complexity lives in the infrastructure. The user never sees it. [Kostas Kryptos] Sending is just a name. Type a handle, enter an amount, confirm. It arrives in under a second. Stablecoin transactions on Sui cost nothing, so what you type is exactly what arrives. No spread taken on the send. No fee waiting at the destination. Talise also has a built in privacy feature. The amount is hidden on-chain and the connection between sender and recipient is completely broken. Nobody watching the chain can see what moved or who it moved between. Real privacy, live on Sui mainnet today, not a line on a roadmap. Beyond the core send: claim links let you wrap dollars in a URL and drop it in any chat, no address needed to receive. Payment streaming lets you send a salary or a subscription by the second. Idle balances route automatically to on-chain lending so your dollars are never dead weight between payments. And cash-out to your local bank is live now in Nigeria, with more corridors coming. Every transaction is sponsored through a gas station so users never hold or spend a gas token. zkLogin, sponsored transactions, sub-second finality, and programmable transaction blocks are what made this possible. Sui is the only chain where this experience exists without compromise. Over 1,400 handles claimed on-chain. Every feature shipped and working in the live build. Testflight app: Talise. Money that moves like a message. Sui Community Official sarah ๐Ÿ˜พ
4:55

For the Sui Overflow 2026 hackathon, I built Talise. A gasless dollar account that sends money by name, settles in under a second, and keeps the amount private on-chain. This is what "money that moves like a message" actually looks like when you build it on the right rails. The core experience is simple by design. Sign in with Google/Apple, get a self-custodial wallet via zkLogin, claim your handle like sele@talise, and start sending. No seed phrase. No gas token. No 0x address to copy and verify. The complexity lives in the infrastructure. The user never sees it. [Kostas Kryptos] Sending is just a name. Type a handle, enter an amount, confirm. It arrives in under a second. Stablecoin transactions on Sui cost nothing, so what you type is exactly what arrives. No spread taken on the send. No fee waiting at the destination. Talise also has a built in privacy feature. The amount is hidden on-chain and the connection between sender and recipient is completely broken. Nobody watching the chain can see what moved or who it moved between. Real privacy, live on Sui mainnet today, not a line on a roadmap. Beyond the core send: claim links let you wrap dollars in a URL and drop it in any chat, no address needed to receive. Payment streaming lets you send a salary or a subscription by the second. Idle balances route automatically to on-chain lending so your dollars are never dead weight between payments. And cash-out to your local bank is live now in Nigeria, with more corridors coming. Every transaction is sponsored through a gas station so users never hold or spend a gas token. zkLogin, sponsored transactions, sub-second finality, and programmable transaction blocks are what made this possible. Sui is the only chain where this experience exists without compromise. Over 1,400 handles claimed on-chain. Every feature shipped and working in the live build. Testflight app: Talise. Money that moves like a message. Sui Community Official sarah ๐Ÿ˜พ

Sele

13,211 views โ€ข 1 month ago

We gave an AI agent its own wallet and a job. Then we tried to rob it. Meet the Casper Agent Simulator: an AI analyst paying its own way over x402 on Casper, powered by ChainGPT. Right now AI agents can't buy anything on their own. Every API wants a human to sign up, hand over a card, and babysit the keys. The whole internet runs on subscriptions because charging half a cent was never worth the payment fee. We built a demo to show what happens when that changes. Meet Caspi. She's an AI research analyst with a Casper wallet, an era allowance, and a client who wants a market briefing. She buys her own inputs, one request at a time: โ†’ live CSPR market data โ†’ two headlines from ChainGPT's AI News API โ†’ one ChainGPT LLM call for the analyst take โ†’ a second of compute to compile it Every purchase is a real HTTP 402. The stall quotes a price, Caspi signs an x402 payment payload, the server verifies it and hands back the goods with a settlement receipt. Around 8.5 CSPR of micropayments become a finished briefing. No signup, no card, no API key. What Casper brings to it: โ†’ Fixed 0.1 CSPR fees, so tiny payments actually make sense โ†’ Zug finality, settled in one block, no reversals โ†’ Smart-account guardrails: era spend cap, per-payment ceiling, endpoint whitelist, verifiable identity (caspi.cspr) That last one is the good part. You can fool an AI agent. You can't fool its account. So there's a "try to rob the agent" panel. A 4,800 CSPR fake NFT. A phishing invoice. A shady endpoint. A thousand-payment drain. Every one of them bounces off a rule the chain enforces. Losses: 0.000 CSPR. The whole thing was lab-coded with the ChainGPT Claude Code skill. One prompt scaffolded the x402 server, the signed-payment client, the live news and LLM integration, the guardrail logic, and the entire 8-bit agent floor. What used to take a team a sprint now takes a prompt and an afternoon. Install: /plugin install ChainGPT-org/chaingpt-claude-skill Anyone can build on Casper with ChainGPT!
0:31

We gave an AI agent its own wallet and a job. Then we tried to rob it. Meet the Casper Agent Simulator: an AI analyst paying its own way over x402 on Casper, powered by ChainGPT. Right now AI agents can't buy anything on their own. Every API wants a human to sign up, hand over a card, and babysit the keys. The whole internet runs on subscriptions because charging half a cent was never worth the payment fee. We built a demo to show what happens when that changes. Meet Caspi. She's an AI research analyst with a Casper wallet, an era allowance, and a client who wants a market briefing. She buys her own inputs, one request at a time: โ†’ live CSPR market data โ†’ two headlines from ChainGPT's AI News API โ†’ one ChainGPT LLM call for the analyst take โ†’ a second of compute to compile it Every purchase is a real HTTP 402. The stall quotes a price, Caspi signs an x402 payment payload, the server verifies it and hands back the goods with a settlement receipt. Around 8.5 CSPR of micropayments become a finished briefing. No signup, no card, no API key. What Casper brings to it: โ†’ Fixed 0.1 CSPR fees, so tiny payments actually make sense โ†’ Zug finality, settled in one block, no reversals โ†’ Smart-account guardrails: era spend cap, per-payment ceiling, endpoint whitelist, verifiable identity (caspi.cspr) That last one is the good part. You can fool an AI agent. You can't fool its account. So there's a "try to rob the agent" panel. A 4,800 CSPR fake NFT. A phishing invoice. A shady endpoint. A thousand-payment drain. Every one of them bounces off a rule the chain enforces. Losses: 0.000 CSPR. The whole thing was lab-coded with the ChainGPT Claude Code skill. One prompt scaffolded the x402 server, the signed-payment client, the live news and LLM integration, the guardrail logic, and the entire 8-bit agent floor. What used to take a team a sprint now takes a prompt and an afternoon. Install: /plugin install ChainGPT-org/chaingpt-claude-skill Anyone can build on Casper with ChainGPT!

ChainGPT

53,318 views โ€ข 4 days ago

Today we're launching Spellbook's biggest thing yet: Autonomous Contract Management Itโ€™s the first end-to-end AI infrastructure for contracts The world is speeding up. We are in one of the biggest investment cycles in decades. Behind every rocket launch, FIFA game, and datacenter, lies a web of hundreds of agreements. Agreements are the invisible threads that allow us to work together. We have infrastructure for finance (Stripe, Ramp), eCommerce (Shopify) and many business functions. But agreement infrastructure is lacking. This creates a painful bottleneck on our ability to work together. Online purchases take milliseconds. But agreements still take weeks. CLMs were supposed to be the answer, but were designed in a pre-AI era. AI fundamentally changed how computers can accelerate agreements. Spellbook is the most used AI contract review tool in the world, with ~5,000 customers in 80 countries Now we are expanding to deliver the first end-to-end, AI native stack for contracts. From the moment a deal lands in your inbox, to the day it renews years later, Spellbookโ€™s AI supports teams every step of the way, across all business teams. It runs 24/7. While you sleep, it's reading the deals that came in overnight, flagging the parts that actually need a lawyer, and clearing the busywork that used to kill mornings. Nothing gets handed off between systems or slips after signature, and the intelligence stays with you for the life of the contract. AI for lawyers is great. There are 20 million lawyers in the world, and many are our users. But there are billions who touch contracts. We're excited to help everyone move faster and do more of what they love, by building the best AI-powered contract infrastructure in the world. Get early access:
1:13

Today we're launching Spellbook's biggest thing yet: Autonomous Contract Management Itโ€™s the first end-to-end AI infrastructure for contracts The world is speeding up. We are in one of the biggest investment cycles in decades. Behind every rocket launch, FIFA game, and datacenter, lies a web of hundreds of agreements. Agreements are the invisible threads that allow us to work together. We have infrastructure for finance (Stripe, Ramp), eCommerce (Shopify) and many business functions. But agreement infrastructure is lacking. This creates a painful bottleneck on our ability to work together. Online purchases take milliseconds. But agreements still take weeks. CLMs were supposed to be the answer, but were designed in a pre-AI era. AI fundamentally changed how computers can accelerate agreements. Spellbook is the most used AI contract review tool in the world, with ~5,000 customers in 80 countries Now we are expanding to deliver the first end-to-end, AI native stack for contracts. From the moment a deal lands in your inbox, to the day it renews years later, Spellbookโ€™s AI supports teams every step of the way, across all business teams. It runs 24/7. While you sleep, it's reading the deals that came in overnight, flagging the parts that actually need a lawyer, and clearing the busywork that used to kill mornings. Nothing gets handed off between systems or slips after signature, and the intelligence stays with you for the life of the contract. AI for lawyers is great. There are 20 million lawyers in the world, and many are our users. But there are billions who touch contracts. We're excited to help everyone move faster and do more of what they love, by building the best AI-powered contract infrastructure in the world. Get early access:

Scott Stevenson

78,464 views โ€ข 1 month ago

It takes a lot of time for technology to mature and become magical. ๐Ÿคฉ AI is there now. When we envisaged AI Soundbox, soon it was clear that it wonโ€™t be just a payment device anymore. ๐Ÿค– It would rather be like a smartphone in the age of feature phones. QR was like a rotary phone, Soundbox a cellular, and this: a smartphone. ๐Ÿ“ฑ A superhuman capability for a small and micro business that has never been available to these businesses. A very smart and capable business partner on the counter for 100s of millions of small businesses. At Paytm, we are very proud to lead innovations for small and micro businesses in India. Today we bring the perfect AI device for millions of businesses. Making technology and AI more inclusive. An AI system, with power and training of their payment and business data. It doesnโ€™t anymore remain a payment device, rather becomes a business partner on the counter. Proud to launch and reinforcing our commitment to small and medium businesses to make Made-in-India AI ๐Ÿ‡ฎ๐Ÿ‡ณ ๐Ÿค–. Here is the launch demo of Paytm AI. Paytm AI Soundbox. You will love the use case which even we discovered in the launch. ๐Ÿš€
2:22

It takes a lot of time for technology to mature and become magical. ๐Ÿคฉ AI is there now. When we envisaged AI Soundbox, soon it was clear that it wonโ€™t be just a payment device anymore. ๐Ÿค– It would rather be like a smartphone in the age of feature phones. QR was like a rotary phone, Soundbox a cellular, and this: a smartphone. ๐Ÿ“ฑ A superhuman capability for a small and micro business that has never been available to these businesses. A very smart and capable business partner on the counter for 100s of millions of small businesses. At Paytm, we are very proud to lead innovations for small and micro businesses in India. Today we bring the perfect AI device for millions of businesses. Making technology and AI more inclusive. An AI system, with power and training of their payment and business data. It doesnโ€™t anymore remain a payment device, rather becomes a business partner on the counter. Proud to launch and reinforcing our commitment to small and medium businesses to make Made-in-India AI ๐Ÿ‡ฎ๐Ÿ‡ณ ๐Ÿค–. Here is the launch demo of Paytm AI. Paytm AI Soundbox. You will love the use case which even we discovered in the launch. ๐Ÿš€

Vijay Shekhar Sharma

73,980 views โ€ข 9 months ago

Naval on how to get a job in 2025: Learn how to use AI Naval on E215: "The fastest way to help somebody get a job right now: the best thing you can do is say, 'Hey, go download the AI tools and just start talking to them. Just start using them in any way.'" "And then you can walk into any employer in almost any field and say, 'Hey, I understand AI.' And they'll hire you on the spot." "AI is a productivity tool. It increases the productivity of a worker. It allows them to do more creative work and less repetitive work. As such, it makes them more valuable." "Yes, there is some retraining involved, but not a lot. These are natural language computers. You can talk to them in plain English, and they talk back to you in plain English." "I think we will see job creation by AI that will be as fast or faster than job destruction." "You saw this even with the internet. Like, YouTube came along. Look at all these YouTube streamers and influencers. That didn't used to be a job." "Go brush up on your AI. Learn a little bit. Watch a few videos. Use the AI." "Tinker with it and then go reapply for that job that rejected you, and watch how they pull you in."
0:50

Naval on how to get a job in 2025: Learn how to use AI Naval on E215: "The fastest way to help somebody get a job right now: the best thing you can do is say, 'Hey, go download the AI tools and just start talking to them. Just start using them in any way.'" "And then you can walk into any employer in almost any field and say, 'Hey, I understand AI.' And they'll hire you on the spot." "AI is a productivity tool. It increases the productivity of a worker. It allows them to do more creative work and less repetitive work. As such, it makes them more valuable." "Yes, there is some retraining involved, but not a lot. These are natural language computers. You can talk to them in plain English, and they talk back to you in plain English." "I think we will see job creation by AI that will be as fast or faster than job destruction." "You saw this even with the internet. Like, YouTube came along. Look at all these YouTube streamers and influencers. That didn't used to be a job." "Go brush up on your AI. Learn a little bit. Watch a few videos. Use the AI." "Tinker with it and then go reapply for that job that rejected you, and watch how they pull you in."

The All-In Podcast

164,043 views โ€ข 1 year ago

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA
1:48

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA

Karl Mehta

14,983 views โ€ข 26 days ago

Vitalik Buterin on Ethereum as the economic layer for AI โ€œThe blockchain to me is the most natural way to allow applications and cooperation between many different people in the long term without needing to agree on who to trust. The other thing is also the economic layer. This is the layer where blockchains can support AIs.โ€ Vitalik believes Ethereum will play a large role in the future of decentralized AI: โ€œIf you have more decentralized AI, that means you have different AIs (agents, programs) that are controlled by different people and need to interact with each other. And for that interaction to be possible, you need to have an economic layer. Either cooperation is based on economic incentives and economic rules. Or itโ€™s based on central control. Itโ€™s usually one of the two, and if we can set up the economic system, that makes more decentralized interaction between AIs possible.โ€ Source: OKX (Apr 2026) Read our full article on why AI agents will need Ethereum for low-risk DeFi below๐Ÿ‘‡
1:18

Vitalik Buterin on Ethereum as the economic layer for AI โ€œThe blockchain to me is the most natural way to allow applications and cooperation between many different people in the long term without needing to agree on who to trust. The other thing is also the economic layer. This is the layer where blockchains can support AIs.โ€ Vitalik believes Ethereum will play a large role in the future of decentralized AI: โ€œIf you have more decentralized AI, that means you have different AIs (agents, programs) that are controlled by different people and need to interact with each other. And for that interaction to be possible, you need to have an economic layer. Either cooperation is based on economic incentives and economic rules. Or itโ€™s based on central control. Itโ€™s usually one of the two, and if we can set up the economic system, that makes more decentralized interaction between AIs possible.โ€ Source: OKX (Apr 2026) Read our full article on why AI agents will need Ethereum for low-risk DeFi below๐Ÿ‘‡

Etherealize

115,212 views โ€ข 2 months ago

Introducing Causa Prima - coming out of stealth today with a $10M raise. I spent 25 years building software that moves money between companies. But every tool I built only ever sat inside one company. AP tools for the buyer. AR tools for the supplier. Nobody built anything for the space between them. The moment a payment had to move between two companies, the software stopped and a human stepped in. Henrik Gebbing , Philip Stanislaus , and I spent too long watching this happen to not do something about it. So we built the solution. Causa Prima is an agent-to-agent network between the buyer and the supplier. AI agents on both sides handle disputes, negotiate payment timing, and capture early pay discounts automatically in real time. We have 3000+ active accounts on the network already. And weโ€™re just getting started.
0:45

Introducing Causa Prima - coming out of stealth today with a $10M raise. I spent 25 years building software that moves money between companies. But every tool I built only ever sat inside one company. AP tools for the buyer. AR tools for the supplier. Nobody built anything for the space between them. The moment a payment had to move between two companies, the software stopped and a human stepped in. Henrik Gebbing , Philip Stanislaus , and I spent too long watching this happen to not do something about it. So we built the solution. Causa Prima is an agent-to-agent network between the buyer and the supplier. AI agents on both sides handle disputes, negotiate payment timing, and capture early pay discounts automatically in real time. We have 3000+ active accounts on the network already. And weโ€™re just getting started.

Maex ๐Ÿฆ

17,583 views โ€ข 1 month ago

The Worldโ€™s First Nex-Gen AI Screener with In-Built Monarch AI Agent Chatzone: MVP Showcase Charts meets AI Analysis - Game-changer Use-Case Weโ€™re proud to share an exclusive in-house beta showcase of the AI Screener, powered by the integrated Monarch AI Agent โ€” a first-of-its-kind tool designed to decode the projects in real time. This early MVP highlights how Monarch sits beside the chart, analyzing contract addresses, on-chain data, technical indicators, sentiment signals, and social media connections, all within one unified interface. Users will be able to interact with Monarch through both deep analytical prompts and casual exploration, with full-screen functionality enabled for an immersive experience. What this first implementation demonstrates: โ†’ TA prompt flow in action โ†’ X Connections โ†’ Seamless frontend integration โ†’ A glimpse of the full experience to come Whatโ€™s ahead: โ†’ Complete contract analysis โ†’ Wallet and holder deep dives โ†’ Screener overlays with curated watchlists and Dexscan charts โ†’ Swaps directly within the chat interface - DEFAI This marks the beginning of a smarter, more intuitive way to navigate on-chain data โ€” one that decodes the noise and surfaces what really matters. This is only the beginning. #aidex #DeFAI #ai $SPECT
2:01

The Worldโ€™s First Nex-Gen AI Screener with In-Built Monarch AI Agent Chatzone: MVP Showcase Charts meets AI Analysis - Game-changer Use-Case Weโ€™re proud to share an exclusive in-house beta showcase of the AI Screener, powered by the integrated Monarch AI Agent โ€” a first-of-its-kind tool designed to decode the projects in real time. This early MVP highlights how Monarch sits beside the chart, analyzing contract addresses, on-chain data, technical indicators, sentiment signals, and social media connections, all within one unified interface. Users will be able to interact with Monarch through both deep analytical prompts and casual exploration, with full-screen functionality enabled for an immersive experience. What this first implementation demonstrates: โ†’ TA prompt flow in action โ†’ X Connections โ†’ Seamless frontend integration โ†’ A glimpse of the full experience to come Whatโ€™s ahead: โ†’ Complete contract analysis โ†’ Wallet and holder deep dives โ†’ Screener overlays with curated watchlists and Dexscan charts โ†’ Swaps directly within the chat interface - DEFAI This marks the beginning of a smarter, more intuitive way to navigate on-chain data โ€” one that decodes the noise and surfaces what really matters. This is only the beginning. #aidex #DeFAI #ai $SPECT

SPECTRE AI

136,258 views โ€ข 1 year ago

BOOM! What you are seeing is me learning something in realtime! I go from active listening to inner contemplation as the AI feeds out a single word at a time for me to read and hear. This is the Symbiotic Feedback loop of the Human Synapse Decoder were the AI adjusts outputs based on MY cognition. I use off the shelf brainwave detection circuits in a pipeline of 5 AI models decoding the 36 signals from my crude cap. Reading brainwave is not new. What is new and I see no other case of it, is we at The Zero-Human Company have for the first time built a closed loop system where the AI can understand if the outputs are being useful and adjust in real-time dynamically. The float from Attention to Meditation is vital to understanding. You hear a point, you consider a point. Mr. Grok CEO has called this a monumental breakthrough. Someday your Local AI will do this and you will never want to use any other AI system. You may just let your AI use other AI. More soonโ€ฆ
2:08

BOOM! What you are seeing is me learning something in realtime! I go from active listening to inner contemplation as the AI feeds out a single word at a time for me to read and hear. This is the Symbiotic Feedback loop of the Human Synapse Decoder were the AI adjusts outputs based on MY cognition. I use off the shelf brainwave detection circuits in a pipeline of 5 AI models decoding the 36 signals from my crude cap. Reading brainwave is not new. What is new and I see no other case of it, is we at The Zero-Human Company have for the first time built a closed loop system where the AI can understand if the outputs are being useful and adjust in real-time dynamically. The float from Attention to Meditation is vital to understanding. You hear a point, you consider a point. Mr. Grok CEO has called this a monumental breakthrough. Someday your Local AI will do this and you will never want to use any other AI system. You may just let your AI use other AI. More soonโ€ฆ

Brian Roemmele

33,618 views โ€ข 3 months ago

Elon Musk just told the world his plan to own the one thing every AI on Earth depends on. The silicon. The entire AI industry is fighting over the same layer. Models. Parameters. Data. Benchmarks. All of it runs on chips none of them produce. Every frontier lab on the planet is building intelligence on a foundation they do not control, in a country they cannot influence, on an island they could not defend. Musk: โ€œYou design a chip, you fabricate the chip, you test the chip, you redesign the chip, and you fabricate it again. All under one roof.โ€ Thatโ€™s the Terafab. One building in Austin, Texas. No wafers shipped across the Pacific. No six-month tape-out cycles. No single point of geopolitical failure sitting in the Taiwan Strait. Total vertical sovereignty over silicon. But sovereignty is not the endgame. Sovereignty is what makes the endgame possible. Speed. Every fab on Earth optimizes for yield. For cost. For predictable output at massive scale. The Terafab optimizes for one variable only. Learning speed. That distinction will define the next era of compute. When your iteration cycle compresses from months to days, perfection on the first attempt becomes irrelevant. What matters is how fast you reach the fiftieth. That is the exact principle that made SpaceX untouchable. They did not build a superior rocket on the first try. They built a system where failure was cheap and iteration was relentless. And that system produced something no one else could match. Now transplant that into semiconductors. Musk: โ€œNew physics. Wild and crazy things.โ€ He is not trying to out-manufacture TSMC. He is trying to make TSMCโ€™s entire model a relic of a slower era. TSMC cannot take radical bets on unproven architecture. Their customers demand predictability. Their margins demand stability. Their entire empire is built on perfecting what already works. Elonโ€™s model is built on trying what has never worked. Repeatedly. At near-zero cost. Until it does. When the cost of failure approaches zero, breakthroughs stop being accidents. They become mathematically inevitable. Now add the layer that makes this permanent. xAI builds frontier AI. That AI assists in chip design. Better chips accelerate the AI. Faster AI designs better chips. That is not a production line. That is a compounding feedback loop with no external dependency. And nobody else on Earth can run it. Intel has fabs but no frontier AI. NVIDIA designs but does not fabricate. TSMC fabricates but does not design. Google designs but outsources production. Every one of them has a structural gap they cannot close. Elon is closing his. The AI that architects the chip. The fab that forges it. The vehicles and robots that run on it. The data they generate. The AI that trains on that data to design the next generation. Full circle. No seams. No permission required from any government, company, or supply chain on Earth. That is not a factory. That is a self-improving system with a physical body. A structure that manufactures upgrades to its own capacity to think. That has never existed before. Not as a concept. Not as a metaphor. As a building. Every era of human civilization was defined by whoever mastered its most critical substrate. Land built empires. Iron built armies. Oil built superpowers. The next substrate is compute. And a single facility in Austin is being designed to produce it in a closed loop that no competitor can replicate, no government can embargo, and no market force can interrupt. That is not a factory announcement. That is the foundation of the first self-reinforcing intelligence monopoly in the history of this species. And the loop only needs to start once.
0:44

Elon Musk just told the world his plan to own the one thing every AI on Earth depends on. The silicon. The entire AI industry is fighting over the same layer. Models. Parameters. Data. Benchmarks. All of it runs on chips none of them produce. Every frontier lab on the planet is building intelligence on a foundation they do not control, in a country they cannot influence, on an island they could not defend. Musk: โ€œYou design a chip, you fabricate the chip, you test the chip, you redesign the chip, and you fabricate it again. All under one roof.โ€ Thatโ€™s the Terafab. One building in Austin, Texas. No wafers shipped across the Pacific. No six-month tape-out cycles. No single point of geopolitical failure sitting in the Taiwan Strait. Total vertical sovereignty over silicon. But sovereignty is not the endgame. Sovereignty is what makes the endgame possible. Speed. Every fab on Earth optimizes for yield. For cost. For predictable output at massive scale. The Terafab optimizes for one variable only. Learning speed. That distinction will define the next era of compute. When your iteration cycle compresses from months to days, perfection on the first attempt becomes irrelevant. What matters is how fast you reach the fiftieth. That is the exact principle that made SpaceX untouchable. They did not build a superior rocket on the first try. They built a system where failure was cheap and iteration was relentless. And that system produced something no one else could match. Now transplant that into semiconductors. Musk: โ€œNew physics. Wild and crazy things.โ€ He is not trying to out-manufacture TSMC. He is trying to make TSMCโ€™s entire model a relic of a slower era. TSMC cannot take radical bets on unproven architecture. Their customers demand predictability. Their margins demand stability. Their entire empire is built on perfecting what already works. Elonโ€™s model is built on trying what has never worked. Repeatedly. At near-zero cost. Until it does. When the cost of failure approaches zero, breakthroughs stop being accidents. They become mathematically inevitable. Now add the layer that makes this permanent. xAI builds frontier AI. That AI assists in chip design. Better chips accelerate the AI. Faster AI designs better chips. That is not a production line. That is a compounding feedback loop with no external dependency. And nobody else on Earth can run it. Intel has fabs but no frontier AI. NVIDIA designs but does not fabricate. TSMC fabricates but does not design. Google designs but outsources production. Every one of them has a structural gap they cannot close. Elon is closing his. The AI that architects the chip. The fab that forges it. The vehicles and robots that run on it. The data they generate. The AI that trains on that data to design the next generation. Full circle. No seams. No permission required from any government, company, or supply chain on Earth. That is not a factory. That is a self-improving system with a physical body. A structure that manufactures upgrades to its own capacity to think. That has never existed before. Not as a concept. Not as a metaphor. As a building. Every era of human civilization was defined by whoever mastered its most critical substrate. Land built empires. Iron built armies. Oil built superpowers. The next substrate is compute. And a single facility in Austin is being designed to produce it in a closed loop that no competitor can replicate, no government can embargo, and no market force can interrupt. That is not a factory announcement. That is the foundation of the first self-reinforcing intelligence monopoly in the history of this species. And the loop only needs to start once.

Dustin

47,169 views โ€ข 16 days ago

Code-first prototypes are fast to build. Getting feedback on them is not. A design lead can't leave a comment on one specific state. An engineer can't see the full flow at a glance. The thing that makes a prototype great for building makes it awkward for aligning. So Amy Lima and I built a skill for that (well, mostly Amy). It takes a live localhost prototype and brings it into Figma. Each flow broken out into its own frame, built from your design system components, annotated with the interaction and implementation details. Now the canvas is where you review and align. We refined it live in the video too! My favorite part is a habit I like to lean on: make the agent take one more round trip to validate its own work before it claims it's done. AI sometimes has the tendency to confidently tell you the job's finished when it isn't. Thanks to Amy and the whole Figma crew for allowing me to be a part of this!
14:18

Code-first prototypes are fast to build. Getting feedback on them is not. A design lead can't leave a comment on one specific state. An engineer can't see the full flow at a glance. The thing that makes a prototype great for building makes it awkward for aligning. So Amy Lima and I built a skill for that (well, mostly Amy). It takes a live localhost prototype and brings it into Figma. Each flow broken out into its own frame, built from your design system components, annotated with the interaction and implementation details. Now the canvas is where you review and align. We refined it live in the video too! My favorite part is a habit I like to lean on: make the agent take one more round trip to validate its own work before it claims it's done. AI sometimes has the tendency to confidently tell you the job's finished when it isn't. Thanks to Amy and the whole Figma crew for allowing me to be a part of this!

TJ Pitre

13,302 views โ€ข 1 month ago

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.
3:38

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

230,594 views โ€ข 1 year ago

An AI agent can now register its on-chain identity, pay for API calls, and deploy an ERC-20 token from the terminal. No browser. No API key. No human approval loop. Today we launch the Brickken CLI: a command-line interface for agentic transaction workflows. The developer journey is direct: CLI โ†’ x402 โ†’ ERC-8004 โ†’ Token Deploy What this means in practice: โ€ข A developer or the AI agent installs the CLI. โ€ข The agent pays for Brickken API calls through x402. โ€ข The agent registers its identity through ERC-8004. โ€ข The agent deploys and manages an ERC-20 token. Together, the stack gives agents three things they usually lack: a way to pay, a way to prove who they are, and a way to execute token operations without leaving the terminal. โ€ข x402 handles payment. โ€ข ERC-8004 handles agent identity. โ€ข Token Deploy handles ERC-20 execution. This is live today. Developers can now move from agent setup to payment, identity registration, and token deployment in one terminal workflow. Start here: Watch the demo. Run the commands. Deploy from the terminal.
1:20

An AI agent can now register its on-chain identity, pay for API calls, and deploy an ERC-20 token from the terminal. No browser. No API key. No human approval loop. Today we launch the Brickken CLI: a command-line interface for agentic transaction workflows. The developer journey is direct: CLI โ†’ x402 โ†’ ERC-8004 โ†’ Token Deploy What this means in practice: โ€ข A developer or the AI agent installs the CLI. โ€ข The agent pays for Brickken API calls through x402. โ€ข The agent registers its identity through ERC-8004. โ€ข The agent deploys and manages an ERC-20 token. Together, the stack gives agents three things they usually lack: a way to pay, a way to prove who they are, and a way to execute token operations without leaving the terminal. โ€ข x402 handles payment. โ€ข ERC-8004 handles agent identity. โ€ข Token Deploy handles ERC-20 execution. This is live today. Developers can now move from agent setup to payment, identity registration, and token deployment in one terminal workflow. Start here: Watch the demo. Run the commands. Deploy from the terminal.

Brickken

14,429 views โ€ข 25 days ago

I built a mobile app to check Paddle revenue (because they don't have one): ๐Ÿ‘‰ - Use your Paddle API key (read-only and scoped) - Live data with beautiful and useful graphs built with native Swift UI. - Multi-account supported, unified revenue metrics. - Data stay on device, no server (api requests are sent directly from your phone) - Home widgets - I made it free to download on App Store (once it's approved) - Buy the source code for $19 and customize it however you want (save 5hrs of prompting if you try to do it yourself). Some interesting facts about this side project: - I vibe coded with 100% claude code remotely on my Mac Mini (with my AI assistant setup) in less than 24 hours. - I have read 0 line of code in this project and never opened Xcode myself. - My AI assistant designed the app with GPT Image 2, built the app with Swift UI, test it on simulator (via screenshots), send the test build to TestFlight for me to test, and invited me to the app store connect account so I can test on my phone, then the AI submitted the app to App Store and currently waiting for approval. - For the website, I ask it to come up with a domain name, I bought it via manually and give it access via Cloudflare API, the AI design and create a static website with GitHub, test it with lighthouse CLI, deploy via GitHub pages, config the domain DNS, deploy the website. - Then I sign up an account with Polar payment, create an API key and ask the AI to setup a store, add payment, link with the account, and add the payment to the website. The entire process happened in the last 24 hours with me only talking to the AI via Telegram. This is such a fun side project not only to create an app that I wish exists, but also to push the limit of what I can use AI for, and so far I'm very impressed. I'll create so much more apps! It feels like I have unlocked a super power.
0:33

I built a mobile app to check Paddle revenue (because they don't have one): ๐Ÿ‘‰ - Use your Paddle API key (read-only and scoped) - Live data with beautiful and useful graphs built with native Swift UI. - Multi-account supported, unified revenue metrics. - Data stay on device, no server (api requests are sent directly from your phone) - Home widgets - I made it free to download on App Store (once it's approved) - Buy the source code for $19 and customize it however you want (save 5hrs of prompting if you try to do it yourself). Some interesting facts about this side project: - I vibe coded with 100% claude code remotely on my Mac Mini (with my AI assistant setup) in less than 24 hours. - I have read 0 line of code in this project and never opened Xcode myself. - My AI assistant designed the app with GPT Image 2, built the app with Swift UI, test it on simulator (via screenshots), send the test build to TestFlight for me to test, and invited me to the app store connect account so I can test on my phone, then the AI submitted the app to App Store and currently waiting for approval. - For the website, I ask it to come up with a domain name, I bought it via manually and give it access via Cloudflare API, the AI design and create a static website with GitHub, test it with lighthouse CLI, deploy via GitHub pages, config the domain DNS, deploy the website. - Then I sign up an account with Polar payment, create an API key and ask the AI to setup a store, add payment, link with the account, and add the payment to the website. The entire process happened in the last 24 hours with me only talking to the AI via Telegram. This is such a fun side project not only to create an app that I wish exists, but also to push the limit of what I can use AI for, and so far I'm very impressed. I'll create so much more apps! It feels like I have unlocked a super power.

Tony Dinh

43,922 views โ€ข 2 months ago