API

An AI agent is a system that uses a language model to perceive its environment, make decisions, and take actions to reach a goal. Unlike a simple chatbot that only responds to prompts, an agent can loop: observe state, plan next steps, call tools, review results, and adapt until the task is done. Agents are built from several components. A planner breaks a goal into subtasks. A memory module stores conversation history and working context. A tool interface lets the agent call APIs, run code, query databases, or interact with other systems. A feedback loop checks whether each step moved the agent closer to the goal. Simple agents might answer a question by searching the web. Complex agents can write and test code, file pull requests, or coordinate with other agents. The more autonomy an agent has, the more important safety guardrails become, such as human approval for destructive actions and clear logging for every decision.

Generates complete technical documentation including API docs, architecture decisions, runbooks, and user guides from code and context.

Build Model Context Protocol clients to connect AI assistants with external tools and data sources. Master the protocol for seamless AI-tool integration.

Repository management, file operations, and GitHub API integration

A system where multiple agents collaborate, compete, or delegate tasks to achieve complex goals.