Drop-point copy loop
Let analytics find the exact moment users give up, then rewrite the words on that one screen.
/loop cadence: weekly. Using the PostHog MCP (read), find the funnel step with the steepest drop-off. Append (step, drop rate, hypotheses) to state-file drop-points.md. Each round, draft rewritten copy/microcopy for the single worst drop screen — draft only, ship nothing to production. Stop after one screen; log analytics errors and stop. Budget: cap $[X]/run. Hard cap: stop after 1 iteration per run.
claude-code
Implementation note
ADAPTED, not verbatim. Yellow loop: reads analytics + drafts copy for approval; no production edits.
More product loops
Review-mine to roadmap
Compile app-store reviews and support into a roadmap ranked by how much pain each issue causes.
/loop cadence: weekly. Using the app store review APIs [STORES], pull new reviews + support exports. Append (issue, frequency, severity, star-impact) to state-file review-roadmap.md. Each round, re-rank the backlog by pain and draft a one-paragraph problem statement for the top unaddressed item. Write to the file only; change no roadmap tool live. Stop after one; log errors and stop. Budget: cap $[X]/run. Hard cap: stop after 1 iteration per run.
productlow risk
Brand-mention feature radar
Sweep where people talk about you each week, cluster the complaints and asks, and deliver the loudest one as a drafted implementation plan.
/loop cadence: weekly. Using the Reddit API, HN Algolia, and Exa, sweep mentions of [BRAND / PRODUCT]. Append (source, mention, sentiment, feature ask/complaint) to state-file mention-radar.md. Each round, cluster and surface the single loudest theme, then draft an implementation plan for it — plan only, build nothing. Stop after one plan; log source errors and stop. Budget: cap $[X]/run. Hard cap: stop after 1 iteration per run.
productlow risk