Blume watches your coding agent sessions locally and turns what it learns into better agent context. Repeated corrections become rules, workflows become skills, and your agents stop making the same mistakes. Claude code, Codex and Cursor.
We built Blume after our previous startup suffered severely from agent drift. Duplicated functions, incoherent architecture and sneaky production bugs.
We tried to control it with all the best practices: proper rules, skills, docs, self-verification. But when our repo grew, the setup rotted fast. Manual maintenance is too time consuming and asking the agent to maintain it lead to context drift and bloat.
Believing the true context signals lie in human intent, we had the idea to extract human intention and corrections from sessions and use them to improve the repo context. After initial testing, we were sure we were onto something, so we pivoted the entire company and built Blume.
Blume is a desktop app that sits next to Claude Code, Codex and Cursor and learns from your sessions. Correction, nudges, frustrated ALL CAPS messages: Blume picks up on them and clusters them thematically. If a pain threshold or recurrence is reached, it suggests a concrete update to your setup. That can be updating a stale rule, patching a hook or skill, or creating an entirely new one. You review and apply it, improving the agent for the next run.
It is free to use, and uses your local harness for extracting and improving the setup. So no chats or code ever leaves your machine.
Try it now for macOS, Linux or Windows! And happy to answer any questions today on how it works or discussing approaches to giving agents proper up-to-date context
This is exactly the failure mode I've hit with my own skill setups - one off feedback getting hardened into a permanent rule too early. How many repeats does Blume wait for before it turns something into a rule?
frustrated ALL CAPS messages getting clustered into a rule, ok that made me laugh. how do u separate a keeper rule from me just being annoyed at one file once
Stop making the same mistakes is exactly what I want from agent memory. Very cool concept.
This solves a problem I think a lot of solo builders are starting to run into. AI can move incredibly fast, but maintaining context, across dozens of sessions become its own job.
About Blume.codes on Product Hunt
“Turns coding agent sessions into better rules and skills”
Blume.codes launched on Product Hunt on September 3rd, 2026 and earned 105 upvotes and 10 comments, placing #11 on the daily leaderboard. Blume watches your coding agent sessions locally and turns what it learns into better agent context. Repeated corrections become rules, workflows become skills, and your agents stop making the same mistakes. Claude code, Codex and Cursor.
Blume.codes was featured in Development (6.2k followers) on Product Hunt. Together, these topics include over 3.6k products, making this a competitive space to launch in.
Who hunted Blume.codes?
Blume.codes was hunted by Peder Aaby. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Peder Aaby
Hey Hunters, Peder here👋
We built Blume after our previous startup suffered severely from agent drift. Duplicated functions, incoherent architecture and sneaky production bugs.
We tried to control it with all the best practices: proper rules, skills, docs, self-verification. But when our repo grew, the setup rotted fast. Manual maintenance is too time consuming and asking the agent to maintain it lead to context drift and bloat.
Believing the true context signals lie in human intent, we had the idea to extract human intention and corrections from sessions and use them to improve the repo context. After initial testing, we were sure we were onto something, so we pivoted the entire company and built Blume.
Blume is a desktop app that sits next to Claude Code, Codex and Cursor and learns from your sessions. Correction, nudges, frustrated ALL CAPS messages: Blume picks up on them and clusters them thematically. If a pain threshold or recurrence is reached, it suggests a concrete update to your setup. That can be updating a stale rule, patching a hook or skill, or creating an entirely new one. You review and apply it, improving the agent for the next run.
It is free to use, and uses your local harness for extracting and improving the setup. So no chats or code ever leaves your machine.
Try it now for macOS, Linux or Windows! And happy to answer any questions today on how it works or discussing approaches to giving agents proper up-to-date context