Scaffolding & Automated Delivery
Script your common dev/release tasks, then combine AI to generate and maintain scaffolding. It cuts repetitive work dramatically.
Generating CLI / Script Skeletons
Generate a bash script `scripts/check.sh`:
- Run lint, typecheck, test in sequence
- Exit immediately on any failure and print the error
- Print elapsed time at the end
Have AI give you the structure first, then swap in your project-specific commands.
Code Templates & Scaffolding
- Have AI generate templates for "new page / component / endpoint" (including tests, styles, types).
- Put templates in
scripts/generate-*and wire them up withnpm runfor quick creation.
CI/CD Integration
- Ask AI for CI config snippets (e.g. GitHub Actions) covering caching, parallelism, and failure strategies.
- Have it write "manual fallback steps" -- like a pre-release verification checklist.
Keeping Scripts Maintainable
- Have AI add comments and usage docs inside scripts to avoid "black box" tooling.
- Centralize important commands in
package.jsonscripts or aMakefilefor consistent access.
Exercise
Ask AI to generate a "new API module" scaffold for your project: controller / service / dto / tests / README. Then have it output a single npm command that generates the entire skeleton.
📚 Related resources
❓ Common questions
Open a question to review the practical answer.
What must a `scripts/check.sh` written by AI include?
The template requires: (1) run lint, typecheck, test in order; (2) exit immediately on any failure with the error printed; (3) emit a timing summary at the end. Have AI scaffold the structure first, then swap in your project's actual commands — `npm run lint` vs `pnpm run lint`. Get the skeleton right, then swap commands — safer than letting AI guess the whole thing.
How do I use AI to scaffold “new page/component/endpoint” templates?
Have AI emit the whole template in one go — tests + styles + types together, not separately. Drop them into `scripts/generate-*` and wire to `npm run` so a single command creates the set. New teammates don't hand-type 8 files per feature, and tests don't get skipped — baking scaffolding into tools beats relying on wiki + goodwill.
What must AI-generated CI config cover to be considered complete?
Four pieces: caching, parallelism, failure policy, plus a manual fallback step (e.g. pre-release verification checklist). The first three are engineering efficiency; the last is the safety net for critical releases — AI-generated CI often skips a human gate, and full automation pushes errors straight to production.
How do I keep AI-written scripts from becoming black boxes?
Two habits: (1) have AI embed comments and usage docs in the script — minimum a `# Usage:` header; (2) centralize key commands in `package.json` scripts or a `Makefile` so the team has one entry point instead of memorizing shell commands. With both, your own scripts are still readable in 3 months and onboarding is faster.
What does the “new API module scaffold” exercise need to deliver?
The exercise lists five deliverables: controller + service + dto + tests + README. End with a single `npm` command that generates the whole skeleton. Acceptance: the command must run on a clean repo and produce a startable module — no missing files, no import errors.