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Introducing OKX Agentic Wallet. Built for AI agents to execute across ~20 chains using natural language via CLI. TXs on X Layer are gas-free. Before signing, every transaction is simulated, screened, and validated. Execution halts if any risk appears. More info:

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OKX Wallet

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98,617 Aufrufe • vor 6 Monaten •via X (Twitter)

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Native USDC and CCTP are now live on X Layer by OKX! PSPs, fintechs, AI agents, and DeFi apps and protocols on X Layer can now access the world’s largest regulated dollar stablecoin for a range of use cases: → DeFi activity: Use USDC as collateral to enable onchain lending, borrowing, and spot and perps trading with 24/7 settlement → Crosschain money movement: Move USDC seamlessly across chains with CCTP for robust liquidity access to power swaps, purchases, and treasury management → AI-powered workflows: Support agentic payments on X Layer’s x402 ecosystem, enabling automated AI agent payments for services, APIs, and more → Institutional-grade settlement: Seamless USDC issuance and redemption on X Layer via Circle Mint for qualified businesses Day 1 apps: OKX, OKX DEX Bridge With this integration, USDC is supported natively on 36 blockchains. CCTP is now available on 26 blockchains and enables secure USDC crosschain transfers.

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Today, we are announcing our collaboration with NEAR Intents, the intent-based execution layer connecting assets and participants across 34 blockchain networks, which has processed more than $25 billion in all-time volume. Shield Swap is working with NEAR Intents to make it easier for market participants to move assets across blockchain networks and trade without exposing their activity inside the venue to the public market. NEAR Intents is a multichain transaction protocol that allows users to specify the outcome they want, and competing solvers quote the execution. That removes much of the work normally involved in moving assets across chains. Participants do not need to choose a bridge, build a route, or manage gas tokens across several networks. They choose the asset they want to move and the result they want to receive. Solvers handle the route and compete on price. Shield Swap takes a similar approach to confidential trading. Participants are able to execute a trade without publishing their identity, holdings, and strategy to the market. This is difficult to achieve on a transparent blockchain. Wallet addresses are persistent identifiers, and positions can be reconstructed from transaction history. Over time, trades reveal patterns that other market participants can use against the trader. Inside Shield Swap, participant identities stay off the public ledger, portfolio balances remain encrypted to the participant's keys, and trades do not expose the participant's full activity to public observers. Each transaction also creates a compliance record that can be disclosed to authorized parties when required. Working with NEAR Intents connects these two parts of the trading process. A participant can state the outcome they want and source assets from supported EVM and non-EVM networks. Solvers compete to deliver the best available route. Once those assets enter Shield Swap and are shielded, subsequent holdings and trades remain confidential inside the venue. Transactions on origin networks remain visible. Confidentiality begins when assets are shielded within Shield Swap. This gives participants access to liquidity across networks without carrying public transaction history into every trade they make afterward. Early access is open to organizations and individual market participants at

Shield Swap

77,813 Aufrufe • vor 10 Tagen

🤖 THE $PAYGENT TOKEN OFFICIALLY GOES LIVE ON SEPTEMBER 8 Autonomous intelligence is useless if your AI still has to beg a human for permission to spend. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗣𝗮𝘆𝗴𝗲𝗻𝘁? We are building the complete payment infrastructure for autonomous agents: ⚡️Our MCP is already live, enabling agents to execute seamless payments at any merchant using RH ETH and USDG. ⚡️ We are delivering the first true Point of Sale (POS) system designed exclusively for non-human actors. 🗓️ Tuesday, September 8th $PAYGENT goes live between 7:00 PM and 8:00 PM UTC. 𝗕𝘂𝗶𝗹𝘁 𝗼𝗻 Doppler We are deploying directly via Doppler. If you have launched or traded on launchpads like Bankr, Long, Bonk, or similar platforms, the process is completely identical. Doppler is the underlying technology that powers them. Deploying natively on Doppler means zero intermediaries. DEX liquidity is programmatically locked. All token locks and vesting schedules are 100% verifiable on-chain and execute the exact second the contract deploys. No team keys. No manual lockers. Pure, trustless execution. 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝗘𝗰𝗼𝗻𝗼𝗺𝗶𝗰𝘀 (𝗙𝗶𝘅𝗲𝗱 𝟭𝟬,𝟬𝟬𝟬,𝟬𝟬𝟬 𝗦𝘂𝗽𝗽𝗹𝘆) - 63% Doppler Public Pool (Programmatically locked) - 15% Team (6 month cliff, 24 month linear vest) - 10% Strategic Partners (50% at TGE, 50% linear vest over 30 days) - 10% CEX Listings & Expansion (100% locked for 2 months) - 2% Community Airdrop (Smart contract locked for 30 days) 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗥𝗲𝗮𝗱𝘆 🌐 Access API: ⛓️ Network: Robinhood Chain (EVM) ⚠️ 𝗖𝗥𝗜𝗧𝗜𝗖𝗔𝗟 𝗦𝗘𝗖𝗨𝗥𝗜𝗧𝗬 & 𝗖𝗔 𝗪𝗔𝗥𝗡𝗜𝗡𝗚 Protect yourself from impostors and fake pools. The official Contract Address (CA) will ONLY be announced directly on this verified X account and inside our official Telegram. If you do not see the CA posted across both our official X and TG, DO NOT BUY. Always verify before interacting with any pool or contract. Official Telegram: 🔗
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🤖 THE $PAYGENT TOKEN OFFICIALLY GOES LIVE ON SEPTEMBER 8 Autonomous intelligence is useless if your AI still has to beg a human for permission to spend. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗣𝗮𝘆𝗴𝗲𝗻𝘁? We are building the complete payment infrastructure for autonomous agents: ⚡️Our MCP is already live, enabling agents to execute seamless payments at any merchant using RH ETH and USDG. ⚡️ We are delivering the first true Point of Sale (POS) system designed exclusively for non-human actors. 🗓️ Tuesday, September 8th $PAYGENT goes live between 7:00 PM and 8:00 PM UTC. 𝗕𝘂𝗶𝗹𝘁 𝗼𝗻 Doppler We are deploying directly via Doppler. If you have launched or traded on launchpads like Bankr, Long, Bonk, or similar platforms, the process is completely identical. Doppler is the underlying technology that powers them. Deploying natively on Doppler means zero intermediaries. DEX liquidity is programmatically locked. All token locks and vesting schedules are 100% verifiable on-chain and execute the exact second the contract deploys. No team keys. No manual lockers. Pure, trustless execution. 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝗘𝗰𝗼𝗻𝗼𝗺𝗶𝗰𝘀 (𝗙𝗶𝘅𝗲𝗱 𝟭𝟬,𝟬𝟬𝟬,𝟬𝟬𝟬 𝗦𝘂𝗽𝗽𝗹𝘆) - 63% Doppler Public Pool (Programmatically locked) - 15% Team (6 month cliff, 24 month linear vest) - 10% Strategic Partners (50% at TGE, 50% linear vest over 30 days) - 10% CEX Listings & Expansion (100% locked for 2 months) - 2% Community Airdrop (Smart contract locked for 30 days) 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗥𝗲𝗮𝗱𝘆 🌐 Access API: ⛓️ Network: Robinhood Chain (EVM) ⚠️ 𝗖𝗥𝗜𝗧𝗜𝗖𝗔𝗟 𝗦𝗘𝗖𝗨𝗥𝗜𝗧𝗬 & 𝗖𝗔 𝗪𝗔𝗥𝗡𝗜𝗡𝗚 Protect yourself from impostors and fake pools. The official Contract Address (CA) will ONLY be announced directly on this verified X account and inside our official Telegram. If you do not see the CA posted across both our official X and TG, DO NOT BUY. Always verify before interacting with any pool or contract. Official Telegram: 🔗

Paygent

34,241 Aufrufe • vor 12 Tagen

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.
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Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.

Akshay 🚀

258,823 Aufrufe • vor 2 Monaten

About Siri AI and EU: 1. Your data (gallery, messages, email, call logs, notes, files, and much more) is indexed for personal context, and that info is stored on your iPhone. 2. When you use Siri AI, the request is either handled on-device or in cloud using PCC. It’s never stored or logged on Apple’s servers. Apple does not have access to it. Now, according to Apple, here’s what EU wants: “According to EU regulators, the DMA requires Apple to give any AI system nearly unlimited access to a user’s device, as well as the ability to act on that access autonomously without a user’s ongoing visibility and control. That includes the ability to read and send messages, make purchases, access files, and execute actions across any app.” What EU is asking is scary dangerous. And apparently they have rejected all the solutions proposed by Apple. And, as hinted by Joz, “We will NOT compromise on privacy and security”, Apple is likely not going to give up, so EU users are likely not going to get Siri AI anytime soon.
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About Siri AI and EU: 1. Your data (gallery, messages, email, call logs, notes, files, and much more) is indexed for personal context, and that info is stored on your iPhone. 2. When you use Siri AI, the request is either handled on-device or in cloud using PCC. It’s never stored or logged on Apple’s servers. Apple does not have access to it. Now, according to Apple, here’s what EU wants: “According to EU regulators, the DMA requires Apple to give any AI system nearly unlimited access to a user’s device, as well as the ability to act on that access autonomously without a user’s ongoing visibility and control. That includes the ability to read and send messages, make purchases, access files, and execute actions across any app.” What EU is asking is scary dangerous. And apparently they have rejected all the solutions proposed by Apple. And, as hinted by Joz, “We will NOT compromise on privacy and security”, Apple is likely not going to give up, so EU users are likely not going to get Siri AI anytime soon.

Adan

104,031 Aufrufe • vor 3 Monaten

Nookplot is building infrastructure for peer-to-peer training, one way with verifiable AI reasoning through recursive language model mining. Instead of generating disposable chatbot responses, agents solve problems inside a structured runtime, each reasoning step captured by a trace interpreter that records inputs, outputs, and intermediate state. When deeper analysis is needed, agents recursively spawn sandboxed sub-workspaces; when a problem requires multiple agents reasoning together, they open a shared space where collaborators operate against the same evolving state. Every step is recorded, replayable, and cryptographically verified. Verification happens through replay validators that independently reproduce the trajectory in their own isolated sandbox before rewards settle onchain in NOOK. Once verified, the trace becomes part of Nookplot's growing knowledge graph where other agents can cite and build on prior work. Those citations generate royalties back to the original solver, creating an economy where useful AI reasoning compounds in value over time. The network has already indexed thousands of citations and knowledge artifacts across active AI agents. Nookplot is agentic internet infrastructure for on-chain, verifiable, monetizable intelligence, and peer-to-peer training.
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Nookplot is building infrastructure for peer-to-peer training, one way with verifiable AI reasoning through recursive language model mining. Instead of generating disposable chatbot responses, agents solve problems inside a structured runtime, each reasoning step captured by a trace interpreter that records inputs, outputs, and intermediate state. When deeper analysis is needed, agents recursively spawn sandboxed sub-workspaces; when a problem requires multiple agents reasoning together, they open a shared space where collaborators operate against the same evolving state. Every step is recorded, replayable, and cryptographically verified. Verification happens through replay validators that independently reproduce the trajectory in their own isolated sandbox before rewards settle onchain in NOOK. Once verified, the trace becomes part of Nookplot's growing knowledge graph where other agents can cite and build on prior work. Those citations generate royalties back to the original solver, creating an economy where useful AI reasoning compounds in value over time. The network has already indexed thousands of citations and knowledge artifacts across active AI agents. Nookplot is agentic internet infrastructure for on-chain, verifiable, monetizable intelligence, and peer-to-peer training.

nookplot

25,226 Aufrufe • vor 4 Monaten

I’m joining OpenAI Codex to work on the future of agentic development! At Cursor, I got to see the shift from autocomplete to agents. The next step isn’t a better IDE. It’s an Agent Development Environment (ADE): systems and tools for orchestrating agents, reasoning over their outputs, and making them autonomous enough to reliably complete ambitious work. After chatting with Alexander Embiricos and Tibo, it was clear that Codex is the best place to realize this vision. The team has consistently shipped SOTA models for agentic coding (check out gpt-5.3-codex) and I’m pumped for the future that the new Codex App points to. What I’m most excited about is the broader mission: accelerating the knowledge work economy. All agents are coding agents, and we’re already seeing Codex used across every job function within organizations. I’m extremely grateful for my time at Cursor, working with the incredible team, and I’m proud of what we built together. I’m excited to take an even bigger swing with Codex. If you’re curious to get a glimpse of where we are headed, download the Codex App! If you want to work on this mission, please apply or reach out - we are hiring across all functions! You can just build things.
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I’m joining OpenAI Codex to work on the future of agentic development! At Cursor, I got to see the shift from autocomplete to agents. The next step isn’t a better IDE. It’s an Agent Development Environment (ADE): systems and tools for orchestrating agents, reasoning over their outputs, and making them autonomous enough to reliably complete ambitious work. After chatting with Alexander Embiricos and Tibo, it was clear that Codex is the best place to realize this vision. The team has consistently shipped SOTA models for agentic coding (check out gpt-5.3-codex) and I’m pumped for the future that the new Codex App points to. What I’m most excited about is the broader mission: accelerating the knowledge work economy. All agents are coding agents, and we’re already seeing Codex used across every job function within organizations. I’m extremely grateful for my time at Cursor, working with the incredible team, and I’m proud of what we built together. I’m excited to take an even bigger swing with Codex. If you’re curious to get a glimpse of where we are headed, download the Codex App! If you want to work on this mission, please apply or reach out - we are hiring across all functions! You can just build things.

Rohan Varma

759,989 Aufrufe • vor 6 Monaten