4 AI coding agent workflow types, compared
AI coding agents can read your codebase, reason about what needs to change, and act on your behalf. The tricky part is picking the right workflow before you hand over the keys.
Real Python’s video course on AI coding agent workflows maps out the four common interaction modes: IDE, terminal, pull request (PR), and cloud. Each one gives you a different level of visibility and control over what the agent actually does.
The Four Workflow Types
- IDE: The agent works alongside you inside your editor. Tight feedback loop, high visibility.
- Terminal: The agent runs commands directly in your shell. Powerful, but you need to know what it’s allowed to touch.
- Pull request: The agent proposes changes via PR. You review before anything merges.
- Cloud: Whole tasks are handed off to an agent running remotely. Highest autonomy, lowest moment-to-moment control.
The course covers what makes each workflow distinct, which mode fits common development scenarios, and where each one is most likely to trip you up.
Hands-On Option
Real Python also runs a live Codex for Python Developers course where you build a full Python project with Codex, an AI agent that operates inside your codebase. The next session is November 14 and 15.
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