Blume.codes

Here's the thing about the AI coding agent boom: everyone's racing to ship more code faster, but almost nobody is capturing the *wisdom* generated in those sessions. Blume.codes is attacking that exact blind spot. The pitch — "turns coding agent sessions into better rules and skills" — signals a shift from treating AI agents as stateless executors to treating them as a knowledge layer that compounds. That's the kind of thinking that separates tools from infrastructure. The timing is impeccable. We're seeing a wave of AI-native dev tools flood the market, but the differentiation is getting brutal. The winners won't be the ones with the flashiest autocomplete — they'll be the ones that make your entire engineering org smarter with every interaction. Blume.codes is positioning itself squarely in that camp. If it can reliably extract transferable skills from messy, real-world sessions, it becomes less of a nice-to-have and more of a core part of the stack. What I find most intriguing is the implied workflow: it's not just a logging tool, it's a *curation* engine. Turning a session into a "rule" or "skill" requires judgment — deciding what's reusable, what's context-specific, and what's noise. That's a hard AI problem, and it's the kind of problem that, if solved well, creates serious lock-in. Teams won't just use Blume.codes; they'll build their institutional knowledge on top of it. The risk, of course, is that the output is only as good as the input. If the rules generated are too rigid or too generic, developers will ignore them. But if Blume.codes nails the balance between automation and human review, this could be the quiet backbone of the next generation of dev teams. Early days, but the signal is strong. Source: https://www.producthunt.com/products/blume-codes