13. Exporting From AI Studio to a Codebase

What this section is for

Exporting is the moment you turn a successful AI Studio run into a real codebase: a repo with files, tests, and a repeatable run loop.

This section teaches you how to export correctly—so you don’t end up with a fragile prototype that only works in the playground.

The deliverables (what “exported” means)

By the end of this section you should have:

• A repo: clear file structure, README, run commands.
• A repeatable environment: local dev setup, env var patterns, secrets hygiene.
• A model-call boundary: a request/response wrapper architecture that isolates LLM calls.
• Operational basics: logging + error handling for LLM calls.
• Prompt artifacts: prompts stored as files and versioned like code.

A practical export workflow

Use this workflow every time you export from AI Studio:

1. Freeze the prototype: capture the final prompt(s), model, and settings that produced the working output.
2. Create the repo skeleton: file tree, README, tests folder, configs.
3. Paste generated code into files: exactly, without “improving” yet.
4. Make it runnable: one command to run, one command to test.
5. Add a wrapper boundary: isolate model calls behind a small interface.
6. Add minimal ops: timeouts, retries, logging, error categories.
7. Commit at ship points: make progress reversible and reviewable.

The theme: keep the loop reality-based. Run it locally early and often.

Rules that prevent prototype-only traps

• Never trust “it ran in the playground” as proof your app works.
• Export early (as soon as you have a walking skeleton).
• Prefer diff-only changes once the repo exists.
• Keep credentials out of prompts and code (env vars + secret management).
• Write tests or at least repeatable checks for each ship point.
• Version prompts and log prompt versions in your app.

Section 13 map (13.1–13.5)

• 13.1 Turning a prototype into a repo
• 13.2 Environment setup: local dev, env vars, secrets
• 13.3 Basic request/response wrapper architecture
• 13.4 Logging and error handling patterns for LLM calls
• 13.5 Versioning prompts (treat prompts like code)

Where to go next

• Start with 13.1
• Then build Project 1 (Part 14)