Most AI tools only tell you what they're good at. That's how you end up discovering the gaps in production. So here's the other half: where our AI agent still misses, specifically, and what we're doing about each one.
What it's genuinely good at
Targeted bug-fixing (~85–90%) — given real broken code, it produces a fix that compiles clean and makes the specific change.
Simple full-stack builds — it scaffolds working SPAs reliably.
Prompt → full-stack app → live deploy with a real database — validated end to end.
