The gap between a $500/month AI coding stack and a $0 one isn't capability. It's the execution layer. Free tools handle completions well. What they still can't do: run your code, see what breaks, reason about the failure, and fix it autonomously. That loop is the moat.

Hot take on MCP servers: Everyone demos the happy path. Nobody demos what happens when: - auth expires mid-session - the tool returns a partial result - state gets corrupted between calls Production readiness is about the failure modes, not the demo.

Most tech Twitter underestimates how much of building AI products is just boring engineering: caching, rate limits, error handling, retries. The model is 10% of the work.

We started Metageeks with one belief: software development is too slow and too expensive for most teams. AI changes that.