Better Models: Worse Tools
The paradox nobody's talking about: as AI models get smarter, the tools built on top of them are getting worse.
Why it matters
As frontier models improve in raw capability, the ecosystem of AI-powered applications may be regressing in usability and reliability. This raises critical questions for CTOs and product leaders about whether model improvements automatically translate to better end-user experiences—and what gets lost in the race for capability.
The key facts
5 to knowAnalysis from Simon Willison (Datasette creator, respected AI observer)
Published July 4, 2026 — recent commentary on active debate
Challenges assumption that model scaling = product improvement
Suggests potential misalignment between model benchmarks and real-world tool quality
Relevant to product strategy and deployment decisions in AI economy
Go to the source
Simon Willisonsimonwillison.net