The no-nonsense approach to AI agent development

This post outlines a three-step process for building AI agents: manual prototyping to understand the task and identify automation candidates, automating the execution loop by writing code to collect inputs and structure the agent's process (using plain code for deterministic tasks and LLMs for judgment), and optimizing for reliability through prompt refinement, precise tool calls, and structured evaluations. It provides an example of a stock analysis agent using the AI SDK and emphasizes that reliable agents are built on clear logic, good structure, and tight feedback loops.