10 AI Prompts Every Developer Should Save Right Now (Production-Grade)

dramaland777 — Sun, 08 Mar 2026 22:18:27 +0000

Most AI prompts for developers are terrible.

"Write me a REST API" returns hello-world code.
"Add authentication" returns tutorial-quality output.

The difference? Specificity.

Here are 10 production-grade prompts I use on every project.

1. REST API Endpoint

❌ Bad: "write a POST endpoint"

✅ Good:
Generate a production-ready POST endpoint in [framework].
Include: input validation with field-level errors, JWT auth
with RBAC, business logic separated from controller,
transaction handling with rollback, correct HTTP status
codes, request logging with correlation ID.

2. JWT Authentication

❌ Bad: "add JWT auth"

✅ Good:
Create a JWT system with: access token 15min in memory,
refresh token 30 days in httpOnly cookie, refresh token
rotation with reuse attack detection, rate limiting 5
attempts/15min, 2FA with TOTP and 10 backup codes.

3. Production Dockerfile

❌ Bad: "write a Dockerfile"

✅ Good:
Multi-stage build, SHA256 pinned base image, non-root user,
layer caching optimization, production-only dependencies,
HEALTHCHECK instruction, target under 100MB final image.

4. Unit Test Suite

❌ Bad: "write tests for this"

✅ Good:
100% branch coverage. Include: happy path, boundary
conditions, null/undefined edge cases, all error paths,
mocked dependencies, spy assertions. Each test name
reads as a specification sentence.

5. Security Audit

❌ Bad: "check my code for security issues"

✅ Good:
OWASP Top 10 audit. For each finding: vulnerability name,
severity with CVSS estimate, exact vulnerable line,
proof of concept attack, business impact, remediation
code, test to verify the fix.

6. Redis Caching

❌ Bad: "add caching with Redis"

✅ Good:
Cache-aside pattern, sliding window TTL strategy,
stampede prevention with SETNX lock, tag-based
invalidation, hit/miss rate metrics, L1 in-memory
cache in front of Redis for ultra-hot data.

7. GitHub Actions Pipeline

❌ Bad: "write a CI/CD pipeline"

✅ Good:
Parallelized jobs: lint, type check, unit tests with
coverage threshold, integration tests with service
containers, Docker build, security scan with Trivy,
deploy to staging with smoke tests, manual approval
gate before production.

8. Rate Limiting

❌ Bad: "add rate limiting to my API"

✅ Good:
Sliding window algorithm in Redis, per-IP AND per-user
limits separately, stricter limits on auth endpoints,
custom 429 response with Retry-After header, graceful
degradation if Redis goes down, bypass header for CI/CD.

9. Database Schema

❌ Bad: "design a database schema for my app"

✅ Good:
UUID primary keys, all foreign keys with ON DELETE
behavior, created_at/updated_at with auto-update,
soft delete with deleted_at, indexes for all FK and
query patterns, CHECK constraints for enums, complete
migration file, seed data, ASCII ER diagram.

10. Client Project Proposal

❌ Bad: "write a project proposal"

✅ Good:
Executive summary 3 sentences max, explicit scope +
out-of-scope list, week-by-week timeline with 20%
buffer, line-item pricing, risk mitigation section,
two package options (MVP vs Full), clear next steps
with deadline.

The pattern is always the same:

Vague prompt = vague output
Specific prompt = production output

I documented 150+ prompts like these across 10
categories. If you want the full pack:

→ dramaland7777.github.io/devprompts

What's your most-used AI prompt?
Drop it in the comments 👇

DEV Community: dramaland777