AI Tool Recipes
Browse 813+ ready-to-use AI tool recipes. Find the perfect workflow automation template by category, tool, or difficulty level.
GitHub Issues → GPT-4 Triage → Linear Tasks → Discord Alert
Automatically triage GitHub issues using GPT-4, create prioritized Linear tasks, and notify the dev team via Discord with smart categorization.
AI Code Generation → Testing → Deployment Pipeline
Create a complete CI/CD pipeline that uses AI to generate code, run automated tests, and deploy to production with approval workflows.
Monitor TPU Availability → Auto-Deploy Models → Track ROI
Automatically monitor Google Cloud TPU availability across regions, deploy ML models when resources become available, and track return on investment from the new hardware.
Compare TPU vs GPU Performance → Generate Cost Report → Update Infrastructure
Benchmark your ML workloads across Google's TPUs and Nvidia GPUs, generate detailed cost-performance reports, and automatically update your infrastructure recommendations.
Auto-Scale ML Models → Monitor Performance → Optimize Costs
Automatically scale machine learning workloads on Google Cloud TPUs based on demand, monitor performance metrics, and optimize costs by switching between TPU types.
Track App Usage → Generate AI Training Data → Build Custom Automations
Monitor your computer interactions across apps to create training datasets that help build personalized AI automations for your specific workflows.
Real-Time Code Review → Slack Notification → GitHub PR Update
Automatically analyze code changes, notify team members instantly, and update pull request status using WebSocket connections for faster feedback loops.
Auto-Generate Code Documentation from GitHub → Review in ChatGPT → Update Confluence
Automatically extract code changes from GitHub repositories, generate comprehensive documentation using ChatGPT workspace agents, and publish to your team's Confluence wiki.
Monitor ML Intern Code → Generate Review Comments → Create Improvement Tasks
Automatically review ML intern code submissions, provide detailed feedback using AI, and create actionable improvement tasks in project management tools.
Create ML Learning Path → Generate Practice Problems → Track Progress
Build a personalized machine learning curriculum for interns, automatically generate coding exercises, and monitor their learning progress with automated feedback.
Robot Path Planning → Safety Check → Deploy Commands
Plan optimal robot navigation paths using world model simulations, validate safety constraints, and deploy movement commands to physical robots.
Simulate Product Testing → Generate Reports → Update Design Docs
Use AI world models to simulate physical product testing scenarios, automatically generate test reports, and update design documentation based on simulation results.