Boilerplate Elimination

Use AI to replace repetitive boilerplate with helpers, generics, or codegen.

Code GenerationIntermediate

Why

GitHub's 2024 Octoverse reported a 59% surge in contributions to generative AI projects and a 98% increase in AI projects overall on the platform. Boilerplate (try/catch wrappers, mappers, config loaders) is where AI shines: it spots the pattern and extracts a helper or generic once, removing the repetition forever.

GitHub's 2024 Octoverse reported a 59% surge in contributions to generative AI projects and a 98% increase in AI projects overall on the platform.

When

Use when you see the same 5+ lines repeated across 3+ places. Skip for one-off repetition.

How

1. Show the AI 2-3 instances of the repeated pattern. 2. Ask: "extract a helper/generic that subsumes these; show the call sites". 3. Review the extracted API; check it covers all instances. 4. Replace each call site; run tests after each. 5. Commit the extraction + call-site changes together.

Example

Before (×8 routes): try { const r = await fn(req); return c.json(r, 200); } catch (e) { return c.json({ error: String(e) }, 500); } Prompt: "extract a withError(handler) wrapper; rewrite all 8 routes to use it." After: each route is one line: export const POST = withError(async (c) => c.json(await fn(c.req), 200));

Common Problems

⚠Generated code fails to compile: "SyntaxError: Unexpected token" → ask the model to output a complete file with correct imports; verify with `npx tsc --noEmit`.
⚠Error: Hallucinated API: model calls a function that doesn't exist → cross-check against the actual library docs and pin the version in package.json.
⚠Error: Cannot find module 'xxx' → `npm install xxx`; generated code often imports packages not yet in the project.

Best Practices

✓Find all instances before extracting so the helper covers them.
✓Keep the helper's parameter list to the real variation, not every hypothetical.
✓Measure the outcome with a concrete metric (time saved, defect rate, test coverage) so the practice can be justified and improved.

FAQ

What is Boilerplate Elimination?

Use AI to replace repetitive boilerplate with helpers, generics, or codegen. It helps developers quickly grasp the core value and use cases of Boilerplate Elimination.

How do I get started with Boilerplate Elimination?

To get started with Boilerplate Elimination, focus on these points first: Show the AI 2-3 instances of the repeated pattern.

What are common mistakes with Boilerplate Elimination?

Common mistakes when using Boilerplate Elimination include: Generated code fails to compile: "SyntaxError: Unexpected token" → ask the model to output a complete file with correct imports; verify with `npx tsc --noEmit`.; Error: Hallucinated API: model calls a function that doesn't exist → cross-check against the actual library docs and pin the version in package.json.; Error: Cannot find module 'xxx' → `npm install xxx`; generated code often imports packages not yet in the project..

What are the best practices for Boilerplate Elimination?

Best practices for Boilerplate Elimination include: Find all instances before extracting so the helper covers them.; Keep the helper's parameter list to the real variation, not every hypothetical.; Measure the outcome with a concrete metric (time saved, defect rate, test coverage) so the practice can be justified and improved..

How do I learn more about Boilerplate Elimination?

Start with the official docs, then search real-world examples on GitHub. Validate patterns in a small scratch repo before applying them to production code.