I built a Python script that runs Claude Code CLI every 3 hours via launchd. Each run:

  1. Searches Product Hunt, HN, Reddit, GitHub Trending, TechCrunch for new AI
  products
  2. Picks one it hasn't covered (checked against a JSON memory file)
  3. Researches it with web search
  4. Writes a ~300 word article
  5. Publishes to WordPress via REST API
  6. Updates its own memory

  No human editing or approval. 210+ articles published so far.

  The architecture is dead simple — subprocess.run() calling `claude -p` with
  different prompts. A JSON memory system tracks covered products and effective
  search methods. Claude reads its own past notes before each run, so it
  gradually learns which sources and keywords work best.

  Interesting observations after weeks of running:

  - Quality is ~7/10 on average. Some articles are genuinely good, some are
  mediocre. The consistency is the real value.
  - The biggest failure mode is picking products that aren't actually new,
  despite explicit instructions.
  - Token cost is the main expense. Each run makes ~7 CLI calls.
  - It has never missed a scheduled run.

  Site: https://topaiproduct.com

  Code is a single Python file orchestrating Claude Code — no LangChain, no
  frameworks.

Any suggestion on how should i improve it?