Scaling Agents in Production

The AI agent hype cycle has produced impressive demos. But the real challenge lies in deploying agent systems at enterprise scale.

Our experience across Fortune 500 companies has revealed consistent failure modes. The most common: agents that work flawlessly in isolation but fail when they need to coordinate.

The solution starts with treating agents as distributed systems. Every principle from microservices architecture applies.

Observability is the second critical pillar. In production, you need to trace every step of an agent’s reasoning chain.

Cost management is often overlooked. Prompt caching and strategic model routing have reduced inference costs by 60-80%.

The organizations that will win are the ones with the most disciplined engineering practices.