Research Reddit customer pain points with a skill
The author replaced a Reddit research agent with a Codex skill that finds pain points, verifies communities, collects evidence, clusters problems, and analyzes commercial signals.
Done withCodex
- What they did
- The author rebuilt a Reddit customer-research workflow as a Codex skill instead of a separate agent stack. Codex handled the reasoning, web access, tool execution, filesystem access, and chat flow; the skill defined the methodology, included a human approval checkpoint before main research, and used small Python helpers only for deterministic tasks like validation, scoring, canonical URLs, deduplication, and artifact generation.
- How it went
- It produced the same kind of structured research flow the earlier agent aimed for: finding pain points, verifying communities, collecting evidence, clustering problems, and analyzing commercial signals. The post gives no benchmark numbers or side-by-side performance results, so the claimed win is simpler architecture and continued follow-up in the same conversation.
- Worth knowing
- The main catch is that this was built as a demonstration and depends on Codex as the harness, rather than a portable standalone agent runtime.
Try it yourself with Codex
Research customer pain points about [topic or product category] on Reddit. Find relevant subreddits, check they're active and on-topic, collect quotes with links as evidence, cluster the complaints into themes, and note any signs people would pay for a solution. Save the findings as a report in [file path], ranking the themes by strength of evidence.
Want help getting this working? Join the Vibe Coding Academy ↗ Run by Alex Finn, who also runs this site.
Source: Reddit · Undated
Related use cases
Turn tickets into merged pull requests
Pulls tasks from GitHub Issues or Linear, then runs Claude Code or Codex in isolated Kubernetes pods to carry each one through to a PR.
Email scheduled project summaries with Codex
A guide sets up a Codex automation that reads project files on a schedule and emails a weekly summary via the Gmail plugin.
Repair formal proofs for a verified garbage collector
Codex edited files and ran builds to repair CertiGC proofs; it handled local repair well, but humans had to check that its invariants preserved the specification.
Find connections across 100 non-fiction books
Claude Code browses a personal library with CLI tools and surfaces trails of related excerpts across books.
Find Reddit threads on reader pain points
A newsletter writer had Comet find Reddit threads on reader pain points, finding extra sources in about 15 minutes without intervention.
Produce cited research briefs with simulated peer review
Feynman multi-agent system searches papers and the web, synthesizes findings, runs simulated peer review, verifies citations, and outputs a cited brief.
Custom agent
Get 5 like this every morning
The best things people got an AI agent to do, each with the prompt to try it.