# Fractal AI Accelerator: guides for AI agents

Reference guides for the course's system maps, for AI agents and the people they work with. Each guide is a text version of one interactive map, and each stands alone: read the one that matches the topic at hand.

## Guides

- [Fractal AI Accelerator: Mastering AI Agents](fractal-ai-accelerator/agent.md): using AI agents on your own work, the whole course on one page: sources, prompting, memory, the design loop, and the better work agents make possible.
- [Fractal AI Accelerator: Prompt Engineering](prompt-engineering/agent.md): getting what you want from an AI agent: knowing what you want, borrowing specificity, the seven parts of a great prompt, steering what comes back, and long runs.
- [Fractal AI Accelerator: Graphic Design](graphic-design/agent.md): the principles of graphic and interface design, with their research basis: research, composition, representation, style, interaction, and critique, including an audit for AI-default design conventions.
- [Practical SWE 101: Finishing Your Prototype](finishing-your-prototypes/agent.md): taking a prototype live as a real product (hosting, domain, accounts, payments, email, monitoring, launch). The broadest guide.
- [Practical SWE 101: Organizing Your Data](organizing-your-data/agent.md): organizing an app's data: where it comes from, which system owns each fact, syncs, analytics pipelines, speed, protection, backups.
- [AI Engineering 101: Supporting AI Features in Your App](supporting-ai-features/agent.md): adding AI features to an app: prompts, retrieval, tools, guardrails, evals, monitoring, cost.
- [AI Engineering 101: Training Your Own Model](training-your-own-model/agent.md): how a language model is trained, for understanding.
- [AI Engineering 101: Inside the Transformer](inside-the-transformer/agent.md) (draft): how a transformer works inside, for understanding.