Breaking Vibe
Tutorials
Hands-on walkthroughs for using AI models, tools, APIs, agents, and workflows.
How to Parse AI Responses in CI/CD with Structured Outputs
Learn how to define a JSON schema, enforce AI output with structured outputs, and validate it in your CI/CD pipeline to automate code review summaries and PR descriptions reliably.
Supercharge Your AI Coding Assistant with Custom Rules Files
Learn how to create scoped, effective rules files for AI coding tools like Cursor and Copilot to get consistent, context-aware code generation in minutes.
Structure Your AI Code Reviews: A JSON-Powered CI/CD Pipeline
Learn to build a GitHub Action that uses OpenAI's structured outputs to generate and post machine-readable code review comments on every pull request.
Automate PR Descriptions with AI Agents: A Step-by-Step Workflow
Build a GitHub Action that uses an AI agent to analyze your code changes and automatically writes a clear, context-rich PR description.
Automate PR Descriptions with an AI Agent in GitHub Actions
Learn how to generate clear, context-aware pull request descriptions automatically using a simple AI agent script hooked into GitHub Actions.
Create a Project Rules File That Makes AI Coding Agents Actually Useful
Learn how to write a rules file (AGENTS.md) that gives AI coding tools the context they need to generate code matching your project's conventions.
Automate PR Descriptions with AI Agents: A Practical CI Workflow
Learn how to build a GitHub Actions workflow that uses an AI agent to generate accurate, structured pull request descriptions from your diff — automatically.
How to Create Custom Rules Files That Actually Control Your AI Coding Agent
A practical guide to writing rules files that force AI coding agents to follow your project's conventions, architecture, and style.
Using Structured Outputs to Parse AI Responses in CI/CD
Learn how to enforce JSON schema on AI responses and wire them into your pipeline for automated code review.
5 Prompt Engineering Patterns That Unlock AI Coding Agents
Learn five practical prompt patterns—role anchoring, few-shot examples, structured outputs, chain-of-thought, and self-review—to make your AI coding agents more reliable and immediately useful.
How to Create Custom Rules Files for AI Coding Tools
Learn how to write rules files that guide AI coding assistants to follow your project's conventions and standards.
Tame AI Chaos in CI/CD with Structured Outputs
Learn how to use structured outputs to reliably parse AI model responses in your CI/CD pipeline, turning free-text into actionable, machine-readable data.
Automate PR Descriptions with AI in 10 Minutes
Learn how to automatically generate pull request descriptions from git diffs using OpenAI and GitHub Actions.
Using Structured Outputs to Parse AI Responses in CI/CD
Learn how to enforce structured JSON responses from LLMs and integrate them into your CI/CD pipeline for automated, reliable code review and changelog generation.
Parsing AI Responses in CI/CD with Structured Outputs
Learn how to enforce JSON schemas for AI models to automate code reviews and generate structured reports in your CI/CD pipeline.
Set Up a Multi-Agent AI Code Review Pipeline for Pull Requests
Learn to build a multi-agent code review system using GitHub Actions and LangChain to automatically review pull requests with multiple AI agents specializing in different aspects.
Creating Custom Rules Files for AI Coding Tools
Learn how to create custom rules files (e.g., .clinerules for Cline or .cursorrules for Cursor) to guide AI coding agents to follow your team's conventions, architecture, and best practices.
Parse AI Code Reviews in CI with Structured Outputs
Learn how to enforce JSON schema on AI responses to automatically parse code review comments in your CI pipeline.
Using Structured Outputs to Parse AI Responses in CI/CD
Learn how to enforce JSON schema in AI API calls and integrate them into your CI/CD pipeline for reliable automated code reviews.
Using Structured Outputs to Parse AI Responses in CI/CD
Learn how to force AI models to return JSON with a defined schema so your CI/CD pipelines can reliably parse and act on AI-generated code reviews, summaries, or tests.
Build a Custom MCP Server to Supercharge Your AI Coding Assistant
Create a custom Model Context Protocol (MCP) server that gives your AI coding assistant real-time access to your project's Git history and code search, making it smarter about your codebase.
Structured AI Outputs in CI/CD: Automate PR Summaries with JSON
Learn how to enforce JSON-structured responses from AI models and integrate them into your CI/CD pipeline to automatically generate pull request descriptions and code review checklists.
Build a Custom MCP Server to Supercharge Your AI Coding Workflow
Learn how to create a Model Context Protocol server that gives your AI coding tools real-time access to your project's context, documentation, and internal APIs.
Automate Code Review with Structured AI Responses in CI/CD
Learn how to use OpenAI's structured outputs to parse AI-generated code review comments in your CI/CD pipeline, turning free-form text into actionable data.
How to Create Custom Rules Files for AI Coding Tools
Learn how to write .cursorrules and similar files to guide AI coding assistants to follow your project's conventions, style, and security practices.
Setting Up a Multi-Agent Code Review Pipeline with GitHub Actions
Learn how to build a multi-agent code review pipeline using GitHub Actions, where specialized AI agents review different aspects of your code (security, style, logic) and provide structured feedback.
Validate AI Responses in CI/CD with Structured Outputs
Learn how to enforce structured JSON outputs from LLM API calls in your CI pipeline using Pydantic models to catch hallucinations and format errors before they break your codebase.
Automating PR Descriptions with AI Agents: A Step-by-Step Workflow
Learn how to automate pull request descriptions using an AI agent that analyzes code changes and generates concise, structured summaries.
Building a Multi-Agent Code Review Pipeline with GitHub Actions
Learn how to set up a CI/CD pipeline where multiple AI agents perform specialized code reviews (linting, tests, security) and provide a consolidated report.
Automate PR Descriptions with AI Agents in GitHub Actions
Learn how to build a GitHub Actions workflow that automatically generates clear, actionable pull request descriptions using AI agents.
Automating PR Descriptions with AI Agents: A Step-by-Step Guide
Learn how to set up an automated pipeline that uses AI agents to generate detailed, structured pull request descriptions directly from your git diffs.
Building a Custom MCP Server for Your Codebase
Learn to create a custom MCP (Model Context Protocol) server that lets AI coding agents query your project's specific metadata, making them far more context-aware.
Using Structured Outputs to Parse AI Responses in CI/CD
Learn how to enforce JSON schemas on AI model outputs in your CI/CD pipeline to reliably automate code review comments, PR summaries, and changelog generation.
Build a Custom MCP Server for Your Codebase
Learn to build a Model Context Protocol (MCP) server that gives AI coding agents direct access to your project's files, enabling context-aware code generation and analysis.
Parsing AI Responses in CI/CD with Structured Outputs
Learn how to enforce JSON schemas on AI model outputs to automate code reviews, changelogs, and PR checks directly in your CI pipeline.
Build a Custom MCP Server to Supercharge Your AI Coding Workflow
Learn to create a Model Context Protocol server that gives AI agents direct access to your codebase, enabling smarter code generation and refactoring.
Automate Pull Request Descriptions with an AI Agent
Learn to automatically generate PR descriptions from code diffs using OpenAI and GitHub Actions, saving developers time and ensuring consistency.
Build a Custom MCP Server to Give AI Agents Read Access to Your Codebase
Learn how to create a minimal MCP server that lets AI coding agents read files and search your repository, enabling smarter context-aware assistance.
Automate Pull Request Descriptions with AI Agents in 15 Minutes
Learn how to set up an AI agent that automatically generates meaningful pull request descriptions from your code changes using GitHub Actions and OpenAI.
Automate PR Descriptions with AI Agents Using GitHub Actions
Learn to automatically generate concise, accurate PR descriptions from code diffs using an AI agent in a GitHub Action.
Automate Test Repairs with Claude Code /goal
A hands-on tutorial showing how to use Claude Code's /goal command to automatically fix failing tests across your codebase without per-step prompting.
Build a simple AI research workflow
A starter tutorial for turning AI news into structured notes and follow-up actions.