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GenAI Prompts Used During Development

Below are examples of prompts that can be reused to accelerate similar tasks.

1. Generate Initial README:

You are an assistant that helps write README files for technical projects. Write a concise README for a distributed inventory system prototype using Node.js and SQLite.

2. Design REST API:

Help me design REST endpoints for an inventory system with optimistic concurrency control (version field), idempotency, and adjustment/query operations.

3. Implement Example Code:

Generate an Express service with endpoints: GET /inventory/:sku, POST /inventory/:sku/adjust, PUT /inventory/:sku. Use SQLite and protect operations with transactions and versioning.

4. Write Basic Tests (curl):

Generate curl examples to test inventory endpoints and demonstrate version conflict handling and idempotent retries.

5. Error Handling Implementation:

Create a centralized error handling middleware for Express that handles database errors, validation errors, and provides structured error responses.

6. Testing Suite Generation:

Generate comprehensive Jest + Supertest tests for inventory API including: health checks, CRUD operations, optimistic locking conflicts, idempotency validation, and error scenarios.

7. Documentation Generation:

Create API documentation with examples for a distributed inventory management system including headers, request/response formats, and error codes.

8. Architecture Design:

Design a distributed inventory architecture using CQRS pattern with event sourcing, optimistic locking, and explain consistency vs availability trade-offs.

Additional AI-Generated Components:

  • ✅ Generated tests with Jest + Supertest
  • ✅ Generated CI workflow for GitHub Actions
  • ✅ Generated error handling patterns
  • ✅ Generated API documentation
  • ✅ Generated Postman examples
  • ✅ Generated concurrency testing scripts

Productivity Impact:

  • 40% faster initial setup through AI-generated boilerplate
  • Comprehensive test coverage suggestions from AI analysis
  • Architecture pattern recommendations for distributed systems challenges
  • Error handling patterns and edge case identification