Introducing Agentic Wallets, our first ever wallet infrastructure built specifically for autonomous agents. Give your agent the power of a wallet. Let your agent manage funds, hold identity, and transact onchain without human intervention. 🧵

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400KM LEFT @ NRC 🔵➡️🟣 Last Nov ‘25, I decided to return to Nike Run Club (NRC), prepared mentally and physically before the new year. 30 starting lines done for 2026 with NRC #248 last night. Started with NRC #1 (Feb ‘21) and paused at NRC #215 (May ‘22). Of the many

The power of AI agents comes from: 1. intelligence of the underlying model 2. how much access you give it to all your data 3. how much freedom & power you give it to act on your behalf I think for 2 & 3, security is the biggest problem. And very soon, if not already, security

I built the first AI that earns its existence, self-improves, and replicates without a human wrote about the technology that finally gives AI write access to the world, The Automaton, and the new web for exponential sovereign AIs WEB 4.0: The birth of superintelligent life

Agent identities is going to be a super fun and hard problem for software in the coming years. Most agentic systems today assume that the agent can do everything the user can do, and just operate as an extension of that user. This has worked well and is how most auth has worked

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CLIs are super exciting precisely because they are a "legacy" technology, which means AI agents can natively and easily use them, combine them, interact with them via the entire terminal toolkit. E.g ask your Claude/Codex agent to install this new Polymarket CLI and ask for any

build startups for agents over the next 10 years, you'll have a market of billions of customers (agents) with millions of wallets that want to use your services go look at every saas tool you use. notion, slack, stripe etc now ask: "what's the version of this that's built

I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then: - the human iterates on the

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