Lesson
Frequently Asked Questions
The questions almost everyone has when getting started with Claude Code, answered straight to the point.
Complete Aulafy mapSee how this lesson fits without leaving your path.
Complete Aulafy map
How all courses connect
This is not a checklist. Start with the foundation, choose an outcome, and go deeper only when your project needs more control.
- 1Understand
- 2Apply or build
- 3Operate with confidence
Choose an application
Turn the foundation into a visible outcome: a website, a business improvement, media, or an interactive experience.
AI for small businesses and freelancersUse AI where it improves real work.View course Generative AI: image, voice and videoCreate production-ready media with AI pipelines.View course Games, 3D and simulations with AIPrototype interactive worlds with AI-assisted tools.View course
Continue into the technical branch when you need to maintain code, data, or infrastructure.
Build with code
Prepare your environment, work with coding agents, and run models while keeping control of your projects.
Aulafy foundationsPython, Git, terminal, and Docker for learning AI smoothly.View course Codex for programmersBuild, test, and ship changes with OpenAI Codex.View course Claude Code, from zero to proYou are hereBuild real software by talking to AI in your terminal.View course Claude Code + Local AIPrivate AI tools that run on your machine.View course
This branch prepares you to design and operate reliable AI systems.
Take systems to production
Combine retrieval, agents, evaluation, security, deployment, and model adaptation when the problem requires it.
Advanced and secure RAGBuild retrieval systems that answer better and leak less.View course Agents and automationDesign agents that can work, recover and stay under control.View course Production agents with LangGraph and n8nTake agent prototypes into reliable operations.View course Self-hosted AI automation for small businessesRun AI workflows on your own infrastructure.View course AI Router and content systemRoute local and frontier models with quality, cost, and privacy controls.View course AI security and evaluationMeasure, test and harden AI systems before trusting them.View course Local MLOps and model deploymentServe, monitor and operate models from your own stack.View course Fine-tuning and post-training for LLMsTrain useful adapters without losing control.View course
You do not need every course: choose the component your system needs and return as it grows.