Coding Agent Stack

A coding agent reads a repository, plans a change, edits files, runs tests and iterates until the task passes — instead of just suggesting snippets.

AI software engineering is the practice of building software where agents write most of the code and humans own architecture, review and verification.

Context engineering is the discipline of deciding exactly what information enters a model's context window, in what order and at what cost.

Give an agent write access without letting it wreck main.

Catch what agents get wrong before a human reads the PR.

This stack details the components necessary to leverage Anthropic's Claude Code capabilities for software development, focusing on integration into common programming workflows. It combines the LLM API with development tools.

This stack outlines the essential components for building and operating an AI coding agent directly within a terminal environment. It combines an LLM API with development tools and execution environments.

Test deterministic code and probabilistic AI output in one pipeline.

The minimum tooling to design, run and observe a production agent.

Writes the task brief that keeps a coding agent inside scope.

A reviewer prompt that finds real defects instead of style opinions.

Coding agents plus a hard verification gate replaced three planned hires.

Copilots accelerate typing; coding agents complete tasks. Different unit of work, different review burden.

Terminal-native agent vs IDE-native pair programmer — different jobs, both worth using.