What's a good loop for someone just getting into loops

❗️ A new YC tool that analyzes your AI coding habits promises "your code never leaves your machine." By their own code, it does. What leaves your system: - Your code, in excerpts. Tool-output snippets are literal source: a Read returns file contents, an Edit carries what you changed. Anything you paste into a prompt goes too. All sent to the LLM proxy. - The file paths your agent read, edited, or created, plus the bash commands it ran. - Your git identity. The script posts your local git user[.]name and user[.]email to a YC endpoint. - Recent commits, per-commit line counts, code-quality aggregates, and telemetry. Sentry error reporting is on by default (--no-sentry opts out). So much for "your code never leaves your machine."

introducing Ralv, the 3D interface to manage AI agents ◆ run multiple coding agents in parallel ◆ infinite 3D canvas instead of chat window ◆ use with claude code & codex subscription we also just launched on producthunt 👇

so let me get this straight typescript twitter will write a 500-tweet thread about why type safety matters but branded types — the one thing that makes type safety actually real — that's "too complex" you'll write processOrder(userId: string, orderId: string) and then spend 3 days debugging when someone swaps the args Schema.brand takes 2 lines. the swap becomes a compiler error. your type safety is a costume

𝕏 just launched the official 𝕏 MCP server. And you can connect it to your OpenClaw to scrape data, find posts, conduct real-time research, and more. Just plug this link into your OpenClaw agent and ask it to help you configure. the setup: github.com/xdevplatform/xmcp

We have partnered with @Xiaomi to bring their excellent MiMo V2 Pro model to Hermes Agent via the Nous Portal - completely free to use for the next 2 weeks! Access now on the latest version of Hermes Agent: 'hermes update'

Introducing WarpGrep, a fast context subagent that improves coding agent performance. WarpGrep speeds up coding tasks 40% and reduces context rot by 70% on long horizon tasks by treating context retrieval as its own RL trained system. Inspired by Cognition’s SWE-Grep - we’re opening access to Claude Code, Codex, OpenCode or any coding agent via MCP (or through our SDK)