The AI Automators®
  • Community & Courses
  • Contact
  • Login

Included with The AI Automators membership

The AI Builders
Course

Design and build expert-level AI systems from the ground up.

Over 50 lessons pairing concepts with hands-on implementation, plus the full codebase we build in the course. It goes way beyond slides.

Get the course with membershipSee the curriculum
  • Over 50 lessonsConcepts paired with hands-on implementation
  • 16+ hours of footageThe key concepts, implemented in a real system
  • The full codebaseThe AI agent platform built in the course
  • Updated regularlyNew and updated lessons as models, patterns and tools move
  • Curriculum
  • The stack
  • What you build
  • Who it is for
  • FAQ
  • Membership

Four modules, from first principles to production

Learn the key concepts, then see each one implemented in a real system, with every decision and tradeoff explained.

  1. 01What Are Agentic Systems?
  2. 02How LLMs Work
  3. 03Tokens and Context Windows
  4. 04LLM Model Landscape
  5. 05Prompt Engineering
  6. 06Structured Outputs
  7. 07Context Engineering
  8. 08What is an AI agent?
  9. 09The Agentic Loop (ReAct Pattern)
  10. 10Tool Calling
  11. 11Model Context Protocol (MCP)
  12. 12Interfaces
  13. 13Fine-Tuning
  14. 14The Architecture of an AI System
  15. 15System 1 vs System 2 Models

  1. 01Intro to AI Coding
  2. 02AI Coding Agents
  3. 03AI Coding Core Concepts
  4. 04Learning the Tools
  5. 05Metaprompting Frameworks
  6. 06Outer Harnesses
  7. 07Agent Frameworks & Platforms

  1. 01Introduction to Agentic Retrieval
  2. 02Vector RAG (Ingestion): Document Ingestion
  3. 03Vector RAG (Ingestion): Chunking
  4. 04Vector RAG (Ingestion): Metadata Extraction & Enrichment
  5. 05Vector RAG (Ingestion): Dense Embeddings
  6. 06Vector RAG (Ingestion): Sparse Embeddings & Keyword Indexing
  7. 07Vector RAG (Ingestion): The Storage Layer
  8. 08Vector RAG (Query): Query Embedding & Similarity Search
  9. 09Vector RAG (Query): Hybrid Search
  10. 10Vector RAG (Query): Re-ranking
  11. 11From Naive to Agentic Retrieval
  12. 12Knowledge Base Exploration
  13. 13Document Navigation
  14. 14Text-to-SQL for Database Retrieval
  15. 15Text-to-Cypher for Knowledge Graph Retrieval
  16. 16GraphRAG
  17. 17Compiled Knowledge

  1. 01Introduction to Harness Engineering
  2. 02Harness Architectures
  3. 03Instructions, Skills, and Dynamic Capability Loading
  4. 04Workspaces, Sandboxes and Planning
  5. 05Context Management and Delegation
  6. 06State and Memory
  7. 07Guides, Sensors and Feedback Loops
  8. 08Multi-Agent Systems

An evolving course. AI moves fast, and so does this course: we add and update lessons regularly to keep pace with the latest models, patterns and tools.

Deep on the concepts. Hands-on with today’s stack.

Platforms, tools and frameworks

  • LangGraph
  • n8n
  • Pydantic AI
  • Docker
  • Python
  • Supabase

IDEs and terminals

  • Claude Code
  • opencode
  • Codex
  • Google Antigravity
  • Cursor

Models

  • Claude
  • OpenAI
  • Gemini
  • Qwen
  • DeepSeek
  • Mistral AI

A real system, not a demo

You see the concepts implemented in the Full Stack AI Agent Platform, and you get its full codebase to run as it is or extend with Claude Code.

  • A full RAG pipeline: Docling, pgvector, hybrid search, reranking
  • Citations checked against their exact source
  • Skills the agent loads on demand
  • Sub-agents with isolated context
  • Harnesses for long-running, multi-phase tasks
  • A unified tool registry and an MCP client

Python · FastAPI · React · Supabase

Explore the Full Stack AI Agent Platform

For builders who want to go beyond demos

Most resources stop where the real work begins. We don’t teach you how to build demos. We teach you how to build real systems.

  • Developers and builders

    Build production-ready AI agents with reliable, grounded responses at scale.

  • Entrepreneurs

    Optimize your business processes and scale efficiently with automation.

  • Consultants

    Deliver top-notch AI solutions and streamline client operations.

Before you start

Can I buy the course on its own?

No. The AI Builders Course is part of The AI Automators membership, together with all of our other courses, the starter apps, the live workshops and the community.

Do I need to know how to code?

No. Many of our members use Claude Code or similar AI coding agents to build full systems, and the AI Coding module shows you how to work with them the way professional builders do.

What is the codebase I get?

The Full Stack AI Agent Platform, the codebase built in the course: Python, FastAPI, React and Supabase. Members can run it as it is, or fork and extend it with Claude Code.

How much time do I need?

As much or as little as you want. The course is self-paced, and the live workshops are optional, so you can dip in and out based on what you are working on.

Is the course kept up to date?

Yes. AI moves fast, so we add and update lessons regularly to keep pace with the latest models, patterns and tools.

Is there a money-back guarantee?

Yes. All plans come with a 7-day money-back guarantee, no questions asked.

Get the course with membership

The course is part of The AI Automators membership. Every member gets:

  • The AI Builders Course
  • The Claude Code & Codex Course and our other courses
  • The starter apps, including the Full Stack AI Agent Platform
  • Live workshops every week
  • A global community of AI builders
  • Direct access to us on the boards and live calls
Get the course with membership

Backed by our 7-day money-back guarantee.

The AI Automators®
Community Contact Blog Member login

© 2026 - The AI Automators® is a registered business name of LogicLabs Digital Limited | Privacy Policy

Not ready to join?
Let's stay in touch.

Hi, we're Daniel and Alan Walsh. Our newsletter is where we send practical guides, tips and the latest AI news. If you'd like them, pop your email in below.

We won't send you spam. Unsubscribe at any time.

You're in

Thanks. Your newsletter signup has been received

Talk soon, Daniel and Alan