AI Agents and Agentic Workflows

An AI agent is a system where a model decides what to do next, calls tools or APIs, observes the result, and repeats until a goal is met. That autonomy is what makes agents useful and what makes them fail. Most agent incidents in production trace back to tool execution and orchestration, not to the model.

This is where we spend most of our engineering. The pieces that decide whether an agent ships are unglamorous: retries and fallbacks on every tool call, an evaluation harness that runs before go-live, confidence thresholds that route to a human, and audit trails on every decision. The writing below is what we have learned building and running them.