What if your product built itself?

PostHog is developing an automated product improvement pipeline that ingests vast amounts of product data, groups signals into actionable problems, and uses AI agents to propose fixes, resulting in automated pull requests (PRs) ready for review in GitHub. The system addresses the inefficiencies of traditional product improvement loops by employing a classifier to filter out malicious signals and aligning signals with actual problems using a language model (LLM). Once signals are grouped, a research agent analyzes the problems, checks their actionability, and, if actionable, writes and iterates on code solutions. This approach is designed to transform the traditional workflow by reducing manual interventions and enabling automated, data-driven code improvements, ultimately aiming for a self-driving product development process that continuously learns from each outcome.

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