#howtobuildaiagents

I build first AI agents as narrow, controlled tool-use loops: the model proposes actions while my code enforces permissions, state, timeouts, logs, and

Most "AI consultants" ship demos, not systems that survive a 3 a.m. incident with retries, evals, cost caps, and observability. I help founders and teams

I ship AI agents to production weekly and pick from three stacks: a ~150-line DIY loop for simple linear tools, LangGraph when I need typed state

I run Claude Code as the execution layer for autonomous systems like BizFlowAI ContentStudio, and reliability came from workflow design, not smarter

I strip frameworks like LangChain and LangGraph out of production because an agent is really just a while-loop around an LLM call with tools, a hard step

I build unattended systems that replace recurring manual work—mapping the real process, automating deterministic parts with code and judgment calls with