This. I think we’ve about reached the limit of the usefulness of anecdata “hey I asked an LLM this this and this” blog posts. We really need more systematic large scale data and studies on the latest models and tools - the recent one on cursor (which had mixed results) was a good start but it was carried out before Claude Code was even released, i.e. prehistoric times in terms of AI coding progress.

For my part I don’t really have a lot of doubts that coding agents can be a useful productivity boost on real-world tasks. Setting aside personal experience, I’ve talked to enough developers at my company using them for a range of tickets on a large codebase to know that they are. The question is more, how much: are we talking a 20% boost, or something larger, and also, what are the specific tasks they’re most useful on. I do hope in the next few years we can get some systematic answers to that as an industry, that go beyond people asking LLMs random things and trying to reason about AI capabilities from first principles.