Practical writing on agentic infrastructure, evaluations, governance, observability, and production AI systems.
Why the next bottleneck is control, not model access. The gap between an impressive agent demo and a reliable production system is not about capability — it is about orchestration, policy, and operational accountability.
How teams should test agents before letting them touch production workflows. Evaluation is not a step you add after the agent is built — it is a discipline you build into the agent from the start.
Prompts, tools, memory, retrieval, costs, approvals, and outcomes all become part of the trace. Traditional software observability was built for deterministic systems — agents require a different mental model.