writing-agents

To create specialized AI agents, define their personas, establish scope boundaries, and outline coordination protocols to ensure they execute autonomous tasks effectively within a project context.

Test-driven development for AI agents uses a RED-GREEN-REFACTOR cycle to iteratively refine agent personas, test their responses against expected behaviors, and improve their overall task execution accuracy.

Defining scope boundaries and anti-patterns involves explicitly listing behaviors the agent should avoid, ensuring the agent stays aligned with project goals and operates within its intended functional limits.

Yes, you can develop an AI agent for code review by defining its persona, specifying the types of code it should review, listing anti-patterns to avoid, and outlining coordination protocols with other agents.

Agent coordination protocols work by defining structured interactions and boundaries between multiple specialized agents, allowing them to execute complex, multi-turn tasks autonomously without overlapping or conflicting actions.