Agent design is still hard(lucumr.pocoo.org)
383 points by the_mitsuhiko | 219 comments
Armin Ronacher's blog post on lessons learned building AI agents, covering SDK choice, caching, reinforcement, failure isolation, shared state, and model choice.
Screenshot pending…
Related stories
We no longer use LangChain for building our AI agents(octomind.dev)
431 points by ma_za | 253 comments
Octomind blog post explaining why the company stopped using LangChain for its AI agents and what it learned using it in production.
What AI-Native Looks Like(fagnerbrack.com)
14 points by fagnerbrack | 7 comments
A blog post by Fagner Brack on Medium describing what an AI-native approach to software development with stable infrastructure looks like.
Pion, an agent designed to run any company autonomously(andonlabs.com)
466 points by lukaspetersson | 564 comments
Andon Labs blog post announcing Pion, an AI agent designed to run any company fully autonomously, and explaining why they built it.
Notes on OpenAI's new o1 chain-of-thought models(simonwillison.net)
641 points by loganfrederick | 566 comments
Simon Willison's blog post with notes on OpenAI's o1-preview and o1-mini models, covering chain-of-thought training, API details, hidden reasoning tokens and examples.
Agents.md speaks Unix, and you should too(fmind.dev)
10 points by fmind-dev | 2 comments
Blog post by Médéric Hurier arguing that AGENTS.md files should guide coding agents using Unix tools, with lessons from his dotfiles and human review.