13th March 2024
The talk track I've been using is that LLMs are easy to take to market, but hard to keep in the market long-term. All the hard stuff comes when you move past the demo and get exposure to real users.
And that's where you find that all the nice little things you got neatly working fall apart. And you need to prompt differently, do different retrieval, consider fine-tuning, redesign interaction, etc. People will treat this stuff differently from "normal" products, creating unique challenges.
Recent articles
- One-shotting a Raccoon Heist game using Claude Fable 5 - 5th August 2026
- New release of LLM adds support for reasoning traces, OpenAI Responses, server-side tools, and smarter logging - 4th August 2026
- Stateless MCP has recaptured my interest (and inspired mcp-explorer and datasette-mcp) - 31st July 2026