Launching today
CodeBurn
See where your AI coding spend actually goes
46 followers
See where your AI coding spend actually goes
46 followers
CodeBurn is a free, open-source tracker for AI coding costs. It reads the session files your tools already write - Claude Code, Cursor, Codex, Copilot, 40 in all, and shows every token and dollar by the task, model, project, and pull request that used it. The Optimize tab finds waste like cache bloat or retry tax, applies the fix, and tracks what it actually saved. Everything runs on your machine: no account, no uploads. MIT-licensed and genuinely free, used by 150k+ developers across the world.
@iamtoruk this is actually so necessary
CodeBurn
I came to CodeBurn from a somewhat unusual direction.
I spent years in strategy and venture investing looking at companies deploying AI, and later moved into an operating role partly because I wanted to understand the problem from inside an enterprise.
Then I started building with coding agents all day myself, and one thing became very obvious: provider dashboards are good at telling us what we consumed. They are much worse at telling us what the consumption actually accomplished.
Resham had already been attacking that problem with CodeBurn. What immediately interested me was how much ground-truth information was sitting locally in agent sessions and git history.
Which project used the money?
What was the agent actually doing?
How many times did it retry?
What did it reread?
Did any of that work become a commit or PR?
That is the layer we're building out.
The longer-term question we're particularly interested in is cost per useful unit of AI work, rather than cost per token.
For this launch, I’d especially love feedback from people who use multiple coding agents heavily:
What do you still feel blind to? What metric would actually make you change how you use your agents?
I’ll be around here all day. Looking forward to your inputs.