Measure how engineers and teams actually work with AI
Measure how you and your team actually work with AI coding agents. Pheebs is an open-source AI telemetry tool created by Eversynced. It sits quietly inside Claude Code, Cursor, and Codex via hooks, capturing lightweight interaction signals: the shape of the session, not its contents.
I've spoken to several engineering leaders who want to better understand their team's AI usage, but don't know where to start. I've also spoken to several engineers who are stuck and don't know how to level up. There's a lot of FOMO building up and being vulnerable about your AI skills is not easy.
Adoption metrics like DAU/WAU and token counts tell you who has access and who uses AI tools. While an ok proxy for AI proficiency and productivity, they say very little about what happens inside a session and how engineers and teams actually use AI.
Which models get used and were they the right fit for the work? Are we spending consciously? Do tests run before a commit? Do outputs get questioned or accepted as is? Do outputs need a lot of repair or do they just get refined? Are repos missing out on scaffolding opportunities (skills, context files)? How's my team doing in AI competencies like context management, evals, and orchestration?
Pheebs captures that and more. It records the shape of sessions and gives engineers a private view of their own work, separate from the team reports. To make sense of the data, Pheebs proposes an AI Proficiency Model, which looks at two things:
1- Repertoire: which harness capabilities show up in an engineer's work across six competencies: models, artifacts, MCP, evals, context management, and orchestration.
2- Judgement (inspired by the Discernment competency from Anthropic's AI Fluency Index): what happens to AI output before a PR is created and merged. Does it get verified, challenged, refined? And was the model used appropriate for the task? Most teams run the largest model for everything. Pheebs shows how much they could save by running smaller models where they fit.
Pheebs is open source so give it a try and send us some feedback!
About Pheebs on Product Hunt
“Measure how engineers and teams actually work with AI”
Pheebs launched on Product Hunt on October 6th, 2026 and earned 95 upvotes and 9 comments, placing #15 on the daily leaderboard. Measure how you and your team actually work with AI coding agents. Pheebs is an open-source AI telemetry tool created by Eversynced. It sits quietly inside Claude Code, Cursor, and Codex via hooks, capturing lightweight interaction signals: the shape of the session, not its contents.
On the analytics side, Pheebs competes within Open Source, Artificial Intelligence, GitHub and Data & Analytics — topics that collectively have 597.9k followers on Product Hunt. The dashboard above tracks how Pheebs performed against the three products that launched closest to it on the same day.
Who hunted Pheebs?
Pheebs was hunted by Davi Prates. 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.
For a complete overview of Pheebs including community comment highlights and product details, visit the product overview.
Davi Prates