Model and dataset supply chain

Your AI app inherits trust from everything it downloads: model, tokenizer, dataset, LoRA, npm package, Docker image, workflow, script, and extension.

Create a provenance record for models and datasets.
Avoid uncontrolled weights, scripts, and dependencies.
Treat license, security, and quality as separate decisions.

Provenance record

Terminal

modelo:
  nombre: "qwen3-8b"
  fuente: "official repository"
  version_o_commit: "..."
  licencia: "reviewed"
  formato: "gguf | safetensors | onnx"
  hash: "sha256:..."
  requiere_trust_remote_code: false
  datos_entrenamiento_conocidos: partial
  uso_permitido: "educational | commercial | review"
  fecha_revision: "2026-07-03"

Simple rules

Prefer formats that do not execute code when loading weights.
Avoid trust_remote_code unless you review exactly what it executes.
Store hashes of weights used in production.
Do not mix private and public datasets without logging.
Review model, dataset, and adapter licenses separately.

Terminal

sha256sum modelo.gguf > checksums.txt
pip freeze > requirements.lock.txt
npm ls --depth=0 > npm-deps.txt
docker image inspect qdrant/qdrant:latest > docker-qdrant.json

Privacy, Logs, and Sensitive Data Project: AI App Audit

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.Beginner to intermediate · 20 lessonsView course Generative AI: image, voice and videoCreate production-ready media with AI pipelines.Beginner to intermediate · 7 lessonsView course Games, 3D and simulations with AIPrototype interactive worlds with AI-assisted tools.Beginner to intermediate · 6 lessonsView 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.Beginner · 6 lessonsView course Codex for programmersBuild, test, and ship changes with OpenAI Codex.Beginner to advanced · 10 lessonsView course Claude Code, from zero to proBuild real software by talking to AI in your terminal.Beginner to advanced · 24 lessonsView course Claude Code + Local AIPrivate AI tools that run on your machine.Intermediate · 34 lessonsView 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.Intermediate · 14 lessonsView course Agents and automationDesign agents that can work, recover and stay under control.Intermediate to advanced · 20 lessonsView course Production agents with LangGraph and n8nTake agent prototypes into reliable operations.Intermediate to advanced · 9 lessonsView course Self-hosted AI automation for small businessesRun AI workflows on your own infrastructure.Intermediate · 10 lessonsView course AI Router and content systemRoute local and frontier models with quality, cost, and privacy controls.Intermediate to advanced · 6 lessonsView course AI security and evaluationYou are hereMeasure, test and harden AI systems before trusting them.Intermediate · 7 lessonsView course Local MLOps and model deploymentServe, monitor and operate models from your own stack.Intermediate to advanced · 10 lessonsView course Fine-tuning and post-training for LLMsTrain useful adapters without losing control.Intermediate to advanced · 8 lessonsView course

You do not need every course: choose the component your system needs and return as it grows.

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