AI workflows for software engineers. Code generation, debugging, documentation, and development automation.
Automate the process of verifying and patching security bugs found by an AI agent. This workflow uses a verifier sub-agent and a patching agent to propose and test fixes, with a human expert in the final review loop.
Create an LLM-powered 'judge' to score and prioritize files in a large codebase for security analysis. This workflow helps focus expensive bug-hunting efforts on the most high-risk areas.
Create a custom AI agent that relentlessly hunts for security vulnerabilities in your codebase. This system uses a large language model with specific tools to find, test, and prove the existence of bugs.
Use a Codex Automation to create a 'meta-agent' that analyzes your codebase, identifies opportunities for new reusable agent skills, and then spawns sub-agents to automatically test and validate those new skills.
Create an AI agent in Claude Code to automatically review aging pull requests, prompt your team for action via Slack, and even fix issues autonomously. This routine helps engineering teams ship code faster and reduce manual follow-up.
Leverage powerful AI coding agents to perform deep, exhaustive benchmarking on complex infrastructure problems. This workflow automates the process of testing numerous solutions, like different database engines or index types, to find the optimal configuration without manual effort.
Use a large language model like Claude to guide you through the complex, technical process of App Store submission. This workflow is for non-technical creators who want to publish their app without hiring an engineer.
Use Claude Opus 4.8's powerful one-shot coding ability to generate a complete, functional feature from a single detailed prompt. Ideal for quickly building new prototypes from scratch.
Use Claude Opus 4.8's one-shot coding capabilities to build an entire functional feature from scratch. This workflow is ideal for quickly creating new prototypes but requires caution for iterative development and bug fixing.
Bridge the digital and physical worlds by creating a custom hardware device that acts as a physical approval button for Claude. Use AI to write the low-level code and connect it to the Claude desktop app for a more tangible AI interaction.
Struggling to edit complex rules or tables in an HTML plan? Prompt an AI to build a temporary, custom user interface (a 'micro-app') for that specific editing task, streamlining your workflow.
Shift from writing implementation code to writing human-readable specifications. Write a detailed spec in a markdown file, and let an AI agent handle the entire process of coding, testing, and verification, using the spec as the single source of truth.
Implement bug fixes and small features rapidly by creating a detailed task in Notion and @mentioning a coding agent. The agent reads the task, writes the code, and submits a complete pull request with a live preview link, drastically reducing friction.
Save 20+ minutes daily by creating a custom Notion agent that automatically gathers updates from Slack, GitHub, and Honeycomb to generate a comprehensive standup pre-read document. This keeps your team aligned and focused on problem-solving, not reporting.
Overcome generic AI-generated designs by building a custom prototyping environment. This workflow connects your company's design system to an AI code editor, ensuring all prototypes are on-brand and high-fidelity.
Delegate a complex, multi-format data migration to an AI agent. The model will build the migration script, create a scalable testing system to validate its own work, and repair issues in a self-sustaining loop.
Use an advanced AI model like GPT-5.5 Pro in Codex to automatically analyze a CSV list of security vulnerabilities, group them thematically, propose architectural changes, and implement the necessary code fixes.
Go beyond simple scripts by building a sophisticated AI agent that learns from every fix. This workflow shows how to create an agent that not only resolves a flaky test but also updates its own logic and proactively clears similar issues from your tech debt backlog.
Tired of lazy AI-generated PR descriptions? Learn Intercom's method to enforce high-quality, intent-driven descriptions by building a custom skill that intercepts PR creation and applies your standards automatically.
Learn how Stripe's engineering team turns a simple Slack message into a complete pull request using AI agents. This workflow automates environment setup, coding, and testing, triggered by a simple emoji reaction, dramatically reducing the friction to start new development work.
Bypass the complex Azure web portal and manage user permissions in seconds. Use natural language prompts in the Warp terminal to assign multiple roles to users instantly, saving significant time on cloud administration.
Turn your team's standard operating procedure for shipping code into an executable AI skill. Automate running tests, fixing lint, pushing to the repo, and monitoring CI, saving significant engineering time and reducing friction.
Create an automated system that captures live audio feedback, uses an LLM to transcribe and summarize it, creates a ticket in Linear, and then triggers a pull request via a custom Slack bot.
Use Cursor's AI to analyze your engineering team's usage data from a CSV. Automatically create user cohorts and generate a gamified playbook to help everyone become an AI power user.
Partner with an AI coding agent to build and deploy a custom TV application from scratch, even with zero prior coding knowledge. This workflow allows you to create a safe, curated content environment for your family by pulling from approved sources.
Create an automated system that uses an AI agent to convert Figma designs into Next.js code. The agent then verifies its output against the original design and iteratively corrects its own mistakes.
Supercharge your engineering velocity by using Claude Opus 4.6 to rapidly build features and then leveraging GPT-5.3 Codex to perform a rigorous, principal-level code review for production hardening.
Follow a step-by-step process to build a custom Chrome extension that summarizes links in Slack using Claude Code, from voice-dictated PRD to a fully debugged, accessible tool.
Use a second, more rigorous AI model like GPT-5.2 Codex to act as a critical 'staff engineer' that reviews code written by your primary, more creative AI like Claude. This multi-model approach ensures high velocity without sacrificing code quality or accumulating technical debt.
Build a custom visual dev tool to create interactive UI mockups and flowcharts. Use these visual artifacts to guide an AI model like Claude Code to build software features with greater accuracy and less ambiguity, bridging the gap between human intuition and AI understanding.
Go beyond simple UI and learn a process for building complex applications like a 3D AI chess game. This advanced workflow covers generating 3D code, streaming AI thoughts, and a unique meta-workflow for debugging AI-generated code.
Learn how to use Vercel's v0 to add new features to a live application. This workflow covers branching, prompting, iterating, and creating a pull request, all within the v0 interface, streamlining the entire development process from idea to production.
Implement an automated 'fix and commit' loop by configuring an AI stop hook. This hook runs quality checks on AI-generated code and automatically prompts the AI to fix any detected errors.
Speed up your development workflow by creating shortcuts for frequent AI commands using shell aliases and building dedicated command-line tools to script complex, repetitive AI tasks.
Boost your AI coding assistant's performance by preloading your application's architecture using text-based Mermaid diagrams. This gives the AI deep context, resulting in faster, more accurate code-related answers.
Leverage OpenAI Codex for high-level software architecture by using the `Plans.md` technique. This workflow guides the AI to generate a comprehensive, multi-step implementation plan for large projects before writing any code.
Avoid merge conflicts and work on multiple features simultaneously by using OpenAI Codex to manage Git worktrees. This workflow lets you run parallel, isolated development tasks directly from your terminal.
Learn how to use an AI coding assistant like Codex to quickly get a new project running locally and make simple code changes using natural language, perfect for semi-technical roles or exploring unfamiliar repositories.
Follow Sahil Lavingia's method for delegating small but impactful maintenance tasks, like fixing an internal Slack report, to the AI agent Devin. This workflow shows how to use simple, clear prompts to fix code and update system prompts without distracting your engineering team.
Learn Gumroad CEO Sahil Lavingia's process for rapidly prototyping a UI with v0, then using the AI agent Devin to autonomously code, implement, and submit the feature for review, turning a multi-day task into a one-hour workflow.
Go from an empty folder to a playable 3D multiplayer prototype in about 15 minutes. This advanced workflow leverages the Claude command-line interface and parallel development to rapidly build and debug both the frontend and backend of a flight simulator game.
Learn to build a complex 3D multiplayer game, even with no prior game development experience. This workflow guides you through an iterative process of using an AI assistant like Cursor and Claude as a junior developer to go from a simple concept to a functional prototype.
Use Repo Prompt to gain surgical control over your AI's context. This workflow shows you how to manually select specific code files, combine them with a detailed prompt and a persona, and generate a highly-contextualized input for an LLM like Claude or Gemini.
Learn how to configure MCPs in Cursor to control external tools like a headless browser or a database directly from your IDE using natural language commands, effectively reducing context switching and manual work.
Learn how a non-engineer built a custom, high-quality website translation service using an AI-native code editor and GitHub Actions. This workflow replaces expensive localization software and agencies, saving over $140,000 annually while improving translation quality and speed.
Take a detailed product blueprint and use the Replit AI agent to build, iterate, and deploy a complex, database-driven web application. This workflow demonstrates how to guide the AI through conversational prompts to create a functional app without deep coding knowledge.
Adopt a structured, software engineering-inspired approach to iterating on AI designs. Use forking to safely explore new ideas and apply a two-step debugging prompt to reliably fix errors without frustrating back-and-forth.
Use AI to analyze test logs, identify and prioritize technical debt, and generate a task list for AI agents like Cursor or Devin to systematically fix issues. This creates a repeatable process for improving codebase health.
Unify scattered documentation into a single repository directory. This creates a single source of truth, improving consistency and efficiency for both human engineers and AI agents.
A developer-focused guide on creating a new capability for the Goose AI agent. Learn to write a simple Python script, wrap it into a reusable Model Context Protocol (MCP) for sending emails, and integrate it into a larger workflow.
When your engineering team hits a deadlock on a new project, use an AI tool like Rork to build a functional mobile prototype. This provides a concrete vision that can unblock the team and generate new implementation ideas without writing any code.
Integrate Devin AI with your alerting system like PagerDuty to act as a first responder for incidents. Devin automatically investigates issues, analyzes logs, and generates an initial report to accelerate triage and resolution by your engineering team.
Leverage Devin AI as an always-available resource to quickly handle frontend UI adjustments like button styling or spacing. Devin implements the changes and provides before-and-after visuals, drastically speeding up the review and iteration cycle.
Use Devin AI as a junior engineer to integrate a new server into an existing codebase. This workflow combines DeepWiki for codebase analysis and a detailed prompt to guide Devin, which then handles research, coding, and pull request generation asynchronously.
Implement a disciplined, three-phase AI development cycle using Cursor and Xcode to build complex applications. This workflow uses custom rules for creating requirements, reviewing plans, and executing code in small, manageable steps to ensure high quality and maintainability.
Set up a coding environment with 'guardrails' like TypeScript and linters, then use a simple prompt in Cursor to let its AI agent automatically find, analyze, and fix code errors. This workflow streamlines debugging and improves code quality.
A structured, data-driven workflow for improving AI product quality by logging real user traces, manually analyzing errors, creating targeted evaluations (evals), and iterating on prompts or models.
Move your custom Claude Skills from your local development environment to the user-friendly Claude.ai web interface. This guide shows you how to package your skill folder, upload it, and begin using it for daily tasks directly in your browser.
This workflow demonstrates how to use a previously created 'meta-skill' within the Claude Code command-line interface to generate a new, specific skill. You'll learn how to prompt Claude Code to build a skill and then immediately test it.
Learn the author's preferred method for building a powerful 'meta-skill' inside the Cursor editor. This workflow uses Anthropic's official documentation to create a reusable agent that can quickly generate new, well-structured Claude Skills on demand.
Learn to go from an empty folder to a functional Next.js web application. This beginner-friendly guide uses Cursor's AI Agent to scaffold, run, and set up version control for your first project hub.
Learn to 'vibe code' a personalized party hub app using Lovable for the structure, Google Fonts for typography, and Midjourney for custom visuals. This workflow takes you from a generic AI template to a unique, 'farm-to-table' application with custom features like dietary restriction tracking.
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