Department series
Workshop
Things to try — copy-paste procedures, MCP setup, prompts.
Instruments
Reading the gauges — before you trust an agent, you need instruments that show you when it's lying.
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Build Your Own Coding Agent
A step-by-step tutorial for building an AI coding assistant from scratch. Bootstrap it with an existing agent, then use it to improve itself.
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The Smallest Coding Agent
A complete agentic coding loop in 25 lines of Bun. No frameworks, no dependencies, just bash and a model.
The Console
Moving into the terminal — the agents live where the work lives, and code becomes disposable material.
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Using repomix to give llm full context
How to use repomix to package your entire codebase into a single file for LLM context, with tips for managing token counts and mise integration.
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context7-mcp
Learn how to integrate Context7 MCP server to get up-to-date code documentation for LLMs and AI code editors, enabling real-time access to the latest library and framework documentation.
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use playwright mcp to get high fidelity designs
Learn how to integrate Playwright MCP server to enable AI coding agents to interact with web browsers, take screenshots, and validate designs with high fidelity for accurate web development and testing.
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Single file swift mini-apps
swift files can be run directly without compiling and without XCode, making it easy to create native UI elements and access all of macOS's APIs. Once you see Swift as a scripting language rather than just an app language, you start wondering what other capabilities are hiding in plain sight.
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Dagger and Container Use
Unlock the power of isolated development with Dagger and Container Use—no more worrying about missing dependencies or system conflicts.
Field Trials
Take the tools outside and see what breaks — agents become products, and products can be raced.
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Use Cursor in Slack
Learn how to integrate Cursor with Slack for seamless code review and collaboration, including setup tips and workflow enhancements.
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Content Finder
Ever had a movie stuck on the tip of your tongue or wanted more like your family's favorite? Explore how AI-powered content discovery can help you make your next pick.
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Geolocation Prompt
This post introduces a prompt for high-precision, image-based geolocation analysis, guiding AI to deduce where a photo was taken using expertise in visual, cultural, and environmental cues. The prompt provides a step-by-step framework for analyzing images and generating confident, reasoned location guesses—even suggesting what extra information would help if uncertain.
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Iterating designs with Chat GPT 4o
Discover how to leverage Chrome's hidden command palette and ChatGPT to transform your website screenshots into sophisticated wireframes. Learn a clever workflow that combines Chrome's full-page screenshot capability with ChatGPT's AI-powered design suggestions to create professional 16:9 ratio mockups for your next project.
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Use the llm cli for quick prototyping
Transform your workflow with a command-line tool that brings AI capabilities directly to your terminal, no complex setup required. See how to parse websites, analyze transcripts, and extract meaningful data using the llm CLI with popular models like Gemini and Claude.
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Lift and shift
Master the art of learning from existing projects by using this structured approach to extracting and documenting requirements and insights. With simple command-line tools and clear documentation practices, you'll be able to turn any existing implementation into a wealth of reusable knowledge.
Blueprints
Drawing up the system — memory, MCP, structured output: the quarter the chat window stopped being the product.
- Give a model tools and it composes them unprompted — MCP turned our services into things you talk to. — Exposing Services with MCP · Mar 15
- Structure is the interface — constrain output to a schema and a chat window becomes a data pipeline. — Schema-Driven AI · Mar 30
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Claude to write midjourney prompts
Transform your written content into compelling visual concepts by using Claude as an intelligent intermediary for Midjourney prompt creation. See how combining prompt libraries with AI analysis can help you explore multiple creative directions before settling on the perfect visual representation.
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Schema-Driven AI: Better User Experiences with Structured Output
Transforms chatting from simple text generators into powerful data processing engines, enabling extraction of organized information from PDFs, audio files, and more. Here are some practical techniques for building, including audio analysis, pdf data extraction and conversation state management, showcasing how constraint-driven outputs can power rich user experiences.
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Make it run tests
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Image Gen on Apple Silicon
We've got the apple silicon, lets download some models and make some pictures
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Adding Memory to Cursor
Transform your Cursor IDE into a more intelligent assistant by implementing a sophisticated memory system adapted from cline-memory-bank. This enhanced version includes TDD principles and integrates seamlessly with your prompt library, allowing your AI assistant to maintain context and remember important details across multiple coding sessions.
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Planning, brainstorming and idea development
Transform your rough concepts into detailed project specifications with this powerful prompting technique that guides you through an in-depth development process. By asking just one thoughtful question at a time, AI helps you create comprehensive, developer-ready plans that cover every essential detail.
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Make it easy to load and update your prompt library
Never lose track of your valuable AI prompts again with this elegant solution for maintaining a personal prompt library. The system provides simple commands to list, load, and save prompts, making it effortless to reuse and iterate on your most effective conversation starters.
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Superwhisper for input
Imagine talking to your computer and having it type for you—Superwhisper makes it real. Check out how this tool speeds up input and even lets you tweak the output.
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Talking to the models in the car
Discover how voice-activated assistants like Google and ChatGPT can transform your car rides into interactive conversations. Learn tips like using search and prompts to dive deeper into news or ideas while on the go.
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Extracting requirements
Need to understand all the requirements hidden in a codebase? This technique shows how to use LLMs to compile comprehensive specifications from repository analysis for immediate development use.
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Exposing Services with MCP
Model Context Protocol bridges the gap between AI models and your applications. Learn how defining simple tools with descriptions and parameters lets Claude intelligently combine services without explicit instructions.
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Write git-commit-messages
Learn how to automate Git commit message generation with this simple but powerful prompt for Claude. The template enforces conventional commit format with appropriate type prefixes and detailed descriptions, making your repository history more professional and useful.
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Making Meta Data
Generating metadata doesn't have to be a manual process when you can leverage AI prompts to produce multiple options quickly. Discover how to implement command-line tools that streamline metadata creation while maintaining your role as the final decision-maker.
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Fetch and Brave Search in Claude Desktop
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Copy a podcast into notebookllm
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Using repomix to give llm full context (original)
The post focuses on how to give LLMs full visibility into a codebase to improve their understanding and responses.
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Understanding a code base
Explore three complementary approaches to rapidly comprehend any codebase using the latest AI assistants and developer tools. Follow along with practical examples showing how to extract key information about memory systems and other complex functionality with minimal effort.
Sketches
The notebook opens — eighteen months of prehistory behind it, and one question: what can these things actually make?
- The tools have character: three coders given the same Figma file produce three different buildings. Someone still has to say which one is right. — Slicing a Design from Figma · Nov 27