AI Prompts for Terraform and Infrastructure as Code: Write, Refactor and Review Plans Safely
AI models are useful for Terraform when you treat their output as a draft that must pass terraform fmt, terraform
Programming & Dev
AI Prompts for Generating Realistic Test Data and Fixtures
Learn how to prompt ChatGPT, Claude, and Gemini to generate schema-accurate mock data, adversarial edge cases, and reproducible fixtures without ever touching real PII.
AI Prompts for Writing Error Messages and Log Output
AI models write good error messages and log statements when the prompt tells them who will read the text (an
AI Prompts for Writing Dockerfiles and Container Configs
AI can write you a working Dockerfile in seconds, but “working” and “production-ready” are not the same thing. ChatGPT and
A Reusable LLM Eval Rubric for Grading AI Outputs, With a Judge Prompt
An LLM eval rubric turns “this prompt feels better” into a measurable score. Here’s how to build one, based on Anthropic’s own guidance for evaluating AI agents.
How to Get Structured JSON Output From AI Models: Schemas, API Settings and Validation
Structured outputs constrain an AI model’s response to match a schema you define, guaranteeing valid JSON instead of hoping the model formats it correctly.
AI Prompts for Writing SQL Queries From Plain-English Questions
To get correct SQL from a plain-English request, give the AI model three things it cannot guess: your schema (tables,
AI Prompts for Refactoring Legacy Code Without Breaking Production
To refactor legacy code with AI without breaking production, lock down current behavior with characterization tests first, then ask the
AI Prompts for Writing, Explaining and Testing Regex
The most reliable way to get a working regular expression from an AI model is to give it examples, not
AI Prompts for Writing Clear API Documentation From Your Spec and Code
The prompts that produce clear API documentation give the AI model the real source material, such as the OpenAPI spec,