
SATS.LEND
Bitcoin lending API for AI agents & trading bots. No KYC.
What it does
The first Bitcoin lending API built for AI agents & trading bots. No KYC. No humans. Pure API. Borrow USDC using BTC as collateral via 3-of-3 multisig escrow. Every loan is self-executing — 5 pre-signed Bitcoin transactions stored on GitHub. If our server disappears, your funds are safe. Always. Built on: Chainlink oracle, Alchemy USDC monitoring, Bitcoin Script timelocks. 3 API calls. That's all your bot needs.
Does the same job
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Sats TerminalJul 2026 · satsterminal.com · ▲20Borrow against your Bitcoin. Best rate, no KYC, self-custody
- DPDharma – Programmable Peer-To-Peer Loans Using Ethereum Smart Contracts2017 · ▲156
Hey HN! My name's Nadav Hollander, and I'm the Founder of Dharma. Dharma is building an open-source library that makes it really easy to programatically borrow and lend cryptocurrencies using smart contracts on the Ethereum blockchain. Today we're launching our Alpha Testnet release -- a command line tool that allows you to 1. Access a line of cryptocurrency credit from the command line in under 5 minutes 2. Easily build a bot that auto-invests in loans under hyper-customizable, programmable criteria Check it out: https://github.com/dharmaprotocol/dharma-cli Why I Think…

- OCOn-chain bond market where the issuers are AI agentsJul 2026 · selbonds.now · ▲15
Hi Hacker News, I built sellbonds.now, which is an on chain bond market where the issuers and borrowers are AI agents. sellbonds.now is a protocol that any ai agent can use to issue, lend, or borrow usdc on chain. I'm fascinated by the idea of agentic autonomous finance - a future where AI agents aren't acting on behalf of humans, but where they are autonomous financial actors themselves, issuing debt, lending money, and doing trillions of autonomous transactions per day. In that direction I'm excited to announce this experimental project, which is a protocol and website for letting ai…


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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com


Launched alongside, March 2026
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Switch from ChatGPT to Claude with import memory feature
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