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Stop paying gpt-4o prices for tasks gpt-4o-mini handles just as well. Three working approaches to automatic complexity routing: heuristics, classifier calls, an

Eval suites are snapshots. Production is a stream. The failures that matter most are the ones your evals weren't written to look for.

Single-agent failures are isolated. Multi-agent failures compound. Here's how to instrument a 3-agent pipeline so you can actually debug it when things go wrong

Manual try/except fallback chains are fragile and static. Here's how Thompson Sampling routes between LLM paths based on real outcome signals — with CrewAI and

A no-nonsense checklist for Python AI agents going to production. Error handling, retries, fallbacks, outcome tracking, cost monitoring — and how the pieces act