Pheebs

Measure how engineers and teams actually work with AI

Artificial IntelligenceGitHubData & AnalyticsOpen Source

▲ 75 votes2 commentsLaunched Oct 6, 2026

Daily #1Weekly #29Monthly #1352

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.

AI Analysis

📝 Summary

Pheebs is an open-source AI telemetry tool that measures how engineers and teams actually work with AI coding agents like Claude Code, Cursor, and Codex. It uses hooks to quietly capture lightweight interaction signals focused on session shape rather than content, preserving privacy. It solves key pain points around lacking visibility into real AI adoption, usage patterns, and productivity impact without invasive monitoring. The value proposition is delivering actionable, data-driven insights for teams to optimize AI workflows, measure ROI, and improve engineering practices.

📈 Market Timing

In 2025-2026, explosive growth in AI coding agents and dev tool adoption creates strong demand for measurement solutions. AI technology is maturing rapidly, user needs are shifting toward quantifying productivity gains, and economic pressures favor efficiency tools. Policy support for AI innovation is positive. This is an ideal window for privacy-focused telemetry. Excellent Timing.

✅ Feasibility

Technically straightforward with lightweight hooks into existing tools; low development and operation costs as an open-source project. Minimal compliance risks due to no content capture. Strong scalability for telemetry aggregation. Fits small teams well with high potential to expand. Overall High.

🎯 Target Market

Primary segments: Engineering managers, CTOs, and dev teams (ages 25-45) in software/tech companies adopting AI tools. Industries: IT and software development. Geographic: Global with concentration in US/Europe. TAM for dev productivity tools ~$10B+, SAM for AI analytics ~$500M, SOM ~$30M for this niche. Core pains: Opaque AI impact on output and best practices. Medium-high willingness to pay for enterprise analytics.

⚔️ Competition

Competition level: Medium. Direct competitors: 1. Helicone (helicone.ai), 2. LangSmith (smith.langchain.com), 3. Arize Phoenix (arize.com/phoenix), 4. PromptLayer (promptlayer.com). Advantages: Open-source, IDE-specific hooks for coding agents (Claude/Cursor), strict privacy (shape not content). Disadvantages: Earlier stage with potentially simpler analytics dashboards and less enterprise polish compared to established LLM observability platforms.

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