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When AI fails to meet our expectations, we often blame it for being "buggy" or "unreliable". But perhaps the problem isn't with AI - it's with our mental model. We keep trying to use AI like software, when it behaves much more like a human colleague.

After five months of building production systems with AI coding tools, I've identified three core problems that actually matter. This post focuses on ensuring quality and building effective human/LLM hybrid teams.

AI gets tired. Not physically, but functionally. Understanding this burnout effect is key to working effectively with LLMs.

As an AI coding enthusiast, I've noticed many smart people spending time on pseudo-problems. Here's what actually matters.