In this article, you will learn the architectural and operational anti-patterns that cause AI agent projects to fail, and how to avoid each one.
Topics we will cover include:
Why agent failures compound differently than failures in simpler, single-response AI systems.
The architectural anti-patterns — from premature multi-agent systems to tool sprawl, hardcoded logic, and missing memory design — that make agents brittle as they scale.
The operational anti-patterns — including missing observability, ungoverned write access, context drift, and skipped evaluation — that only surface once an agent reaches production.
