Running OpenWiki for Real: Why the Model You Pick Decides Everything
Part 2 of 3 — a real generation run, the model that couldn’t finish, the one that could, and what quality docs actually cost. In Part 1 I covered what OpenWiki is — LangChain’s take on Karpathy’s…
Read the full articleYou might also wanna read
Anthropic just confirmed why 90% of non-coding AI agents fail in production
Anthropic recently published an incredibly deep breakdown analyzing millions of real human-agent tool calls across their public API, and the
AI coding agents are flooding open source repos with low-quality pull requests, data from OpenClaw shows
OpenClaw became the fastest-growing repo in GitHub history almost overnight. The PR data offers a preview of what the future of open source
Developer builds AI spec-review tool after his own project spiraled into technical debt
A software developer shared how his excitement-driven approach to building a multiplayer guitar tab app led to significant technical debt de
ProgramBench: New Benchmark Reveals Language Models Struggle to Build Complete Software Projects From Scratch
Turning ideas into full software projects from scratch has become a popular use case for language models. Agents are being deployed to seed,
Show HN: Statewright – Visual state machines that make AI agents reliable
Agentic problem solving in its current state is very brittle. I fell in love with it, but it creates as many problems as it solves. I'm Ben

The real value of AI coding models isn't speed — it's lowering the barrier to doing things you'd otherwise skip
Everyone talking about coding models fixates on the same number: how fast the thing generates code. This misses the point by a lot. The stor

Comments
Sign in to join the conversation.
No comments yet. Be the first.