A practical guide to AI-native software development.

How a team turns a feature, bug, or change into a task a coding agent can finish, including the context to gather and the checks a person still owns.

The day-to-day work of building software with coding agents: task size, feedback loops, parallel work, and how to review the code that comes back.

Using agents to investigate bugs, write tests, and review changes, and the human checks that decide whether a result is acceptable.

How a small team shares agent setup, skills, and review duty, including handoff, access, and what should not be centralized.

Where agent work runs, which repositories and credentials it can reach, and the difference between a local machine and a shared environment.