source-driven-development

Source-Driven Development

AI agents can confidently generate outdated or deprecated framework code. Source-driven development replaces memory-based implementation with a repeatable loop: detect the version, fetch the official source, implement from that source, then capture the reference in durable notes.

When to Use

• Writing framework-specific code you have not touched recently
• Using a library that changed versions since the last time you used it
• Implementing middleware, routing, configuration, hooks, or SDK integration
• Seeing deprecation warnings or suspecting API drift
• Asking an AI agent to write code where stale training data could mislead it

When NOT to Use

Instead of source-driven-development	Use
Writing pure business logic with no framework dependency	spec-driven-development
Reusing a stable internal utility with known behavior	implement directly
Looking up tool setup for MCP servers	mcp-ecosystem

Prerequisites

• You know which library, framework, or SDK is involved
• You can determine the exact version used in the project
• You have access to official docs, release notes, or migration guides

Workflow

1. Detect the exact version

Do not look up docs before you know what version the project actually uses.

Check package manifests, lockfiles, or module metadata first.
Examples:
- package.json / package-lock.json
- pyproject.toml / requirements.txt
- go.mod

2. Fetch the official source

Use this priority order:

1. Official documentation site
2. Official GitHub repository changelog or migration guide
3. Official release notes or blog posts
4. MDN for web platform APIs

Avoid secondary tutorials as your primary authority.

3. Extract the exact pattern you need

Write down the specific API shape before coding:

• function or hook name
• required arguments
• return shape
• error handling behavior
• version-specific caveats

4. Implement to match the source