01Module 04: Coding AgentsCoding agents are the most commercially successful form of agentic AI. Learn how GitHub Copilot, Cursor, Devin, and Claude Code work under the hood.02How Coding Agents WorkDeep dive into coding agent architecture: how agents navigate codebases, plan edits, execute changes, and iterate using test feedback.03SWE-bench and EvaluationHow to evaluate coding agents: SWE-bench, SWE-bench Verified, SOTA numbers, failure modes, and building your own evaluation harness.04Agentic Code EditingHow coding agents read, navigate, and surgically modify existing codebases: edit strategies, minimal diffs, regression prevention, and multi-file coordination.05Tool Use for CodingComplete coding agent tool set: file operations, bash execution, search, git integration, LSP queries - full implementations with safety and error handling.06Test-Driven Agent LoopsThe most powerful technique for coding agents: use test output as the ground truth feedback signal. TDD loops, pytest integration, output parsing, and backtracking.07Building Your Own Coding AgentBuild a complete, functional coding agent from scratch in Python. Architecture decisions, repo maps, context management, system prompts, safety, and the full 500-line agent.
