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12 hand-written guides covering Claude, ChatGPT, Cursor and the image-gen ecosystem. Every guide built on a real workflow with the actual prompt suite we used — no AI-written tutorials, no copy-pasted dashboards. Kept current; this space moves fast.
A five-step walkthrough that takes you from empty conversation to a working artifact-based mini-app. Uses the system prompt template we use ourselves for real client work. Walked on the actual model.
Prerequisites: Claude.ai account (free tier OK).
Start the guide →Five questions, one answer — the AI model that actually fits your workflow.
Find your AI match →No AI background needed. Walks you through your first useful output — not a “Hello World” demo. If you’ve only chatted, start here.
You’ve used the API or built a custom GPT before. Comfortable with JSON, env files, and async patterns. Most readers spend the most time here.
SDK-level work, MCP servers, eval pipelines. Built for the readers who already run AI in production.
Multi-file refactor workflows · safe rollback patterns · eval criteria for trusting agent output.
The 6-section template we use for production prompts · with eval rubric to catch drift early.
From zero to a citing, source-grounded research assistant. Includes the file-upload + retrieval config.
Build a custom MCP server, plug it into Claude/Cursor, ship a tool that does real work. Includes example repo.
4 questions to answer before you pay for a subscription. Includes the decision tree we use ourselves.
Concrete patterns that cut fact errors by ~70% on our eval suite. Works on every model we tested.
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