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Tool and license map

Generative AI changes fast. That's why we're not going to memorize names: we're going to learn how to choose tools by control, license, cost, privacy, and the ability to reproduce results.

  • Choose a stack for image, voice, and video without getting lost among models.
  • Distinguish open models, commercial use, and cloud services.
  • Keep a record of which model, license, and parameters you used.

Aulafy base stack

  • ComfyUI: visual node-based interface for images, video, audio, and reproducible workflows.
  • Diffusers: Python code to generate, compare, and automate images with versionable pipelines.
  • FLUX: powerful family for images; review each variant because they don't all share the same license.
  • Whisper: local transcription and subtitles.
  • Piper: local text-to-speech with lightweight models.
  • Wan: video generation for short clips, usually with higher VRAM requirements.

Record sheet you should keep for each resource

Terminal
recurso:
  tipo: modelo | lora | voz | workflow | dataset
  nombre:
  version_o_commit:
  fuente:
  licencia:
  uso_permitido: personal | comercial | investigacion | revisar
  restricciones:
  parametros_clave:
  fecha_revision: 2026-07-02

Quick decision

  • I want an image now: ComfyUI with a simple workflow.
  • I want to repeat a hundred variations: Diffusers with seed, prompt, and manifest.
  • I want voice for a lesson: Whisper to transcribe and Piper to narrate.
  • I want video: start with 3 to 5 second clips and a single scene.
  • I want to sell it: check the license before generating, not after.
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.

  1. 1Understand
  2. 2Apply or build
  3. 3Operate with confidence
01

Choose an application

Turn the foundation into a visible outcome: a website, a business improvement, media, or an interactive experience.

Continue into the technical branch when you need to maintain code, data, or infrastructure.

02

Build with code

Prepare your environment, work with coding agents, and run models while keeping control of your projects.

This branch prepares you to design and operate reliable AI systems.

03

Take systems to production

Combine retrieval, agents, evaluation, security, deployment, and model adaptation when the problem requires it.

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

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