Agentic Coding

An agentic coding tool follows a plan-act-observe loop. You provide a high-level goal like "add input validation to the signup form." The agent reads your project structure, identifies the relevant files, writes the implementation, runs tests, reads failures, fixes them, and repeats until the task is complete. The human sets the direction; the agent handles execution.

Traditional chat-based AI tools require developers to copy-paste code snippets and manually iterate on errors. Agentic coding eliminates that friction. The AI operates directly on your filesystem, shell, and git history, turning multi-step tasks that took hours of back-and-forth into single-prompt workflows. Developers report 3-10x speedups on routine tasks like refactoring, test writing, and bug fixing.

# Example: one prompt, multiple autonomous actions
$ claude
> "Find all API endpoints without rate limiting,
   add rate limiting middleware, and write tests"

# The agent reads routes, writes middleware,
# updates each endpoint, runs tests, fixes failures.

Start with tasks you already know how to do manually. This lets you verify the agent's work against your own expertise before trusting it with larger changes.