Building Effective AI Agents: Patterns That Actually Work in Production
· 9 min read
Most AI agent projects fail not because the models aren't capable enough — but because the engineers building them reach for complexity before they've earned it. After studying dozens of production deployments, a clear pattern emerges: the teams shipping reliable agents start with the simplest possible system and add complexity only when metrics demand it.
This is a guide to the mental models, patterns, and practical techniques that separate robust agentic systems from ones that hallucinate, loop, and fall apart under real workloads.
