Dev Shares Recursive QA Loop Using Grok to Optimize Text Classification
kylegawley · x · 2026-08-11
An indie developer shared a recursive QA workflow built to optimize post classification for their product, Alertly.
- Data Sampling: Runs a stratified random sampler over 700 classified posts across intent buckets like leads, brand mentions, and spam. The draw is seeded for reproducibility.
- Automated Refinement: Uses Grok to diff the sampled posts against the classifier prompt, automatically generating and shipping fixes.
- Latest Iteration: Tightened lead detection to focus on actual demand rather than pure keyword matching. Also applied stricter community engagement rules so educational posts ending with a question aren't mistakenly flagged as reply opportunities.
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