Free · 98 Episodes · 14 Modules · Production-Grade

Build AI Systems. Not AI Demos.

The Complete Engineering
Field Manual for Modern AI

98 episodes. 14 modules. From tokens and transformers to RAG, agents, model serving, deployment, scaling and AI SaaS architecture. Written for engineers who want to ship real systems.

Start Episode 1 → Explore 98 Episodes ↓
98
Episodes
14
Modules
Ship
Production Ready
Free
Forever
Learning Journey

14 Modules. One Complete Roadmap.

Each module is a focused block of 7 episodes — building your skills systematically from inference fundamentals to production MLOps.

Why This Exists

Most people learn prompts. Engineers learn systems.

The goal isn't to use AI. The goal is to understand inference, embeddings, retrieval, agents, serving, deployment, and production architecture — so you can build real AI products.

This is the handbook for engineers and founders who want to stop being users and start being builders.

Begin Episode 1 →
⚙️
Production-Grade Knowledge
No toy examples. Every concept taught the way it works in real deployed systems.
🔬
First Principles, Not Tutorials
Understand WHY things work — not just how to copy-paste code from StackOverflow.
🚀
Engineer's Perspective
Written for people who ship. From tokens all the way to scaling infrastructure under load.
🆓
Free. Forever.
All 98 episodes, all 14 modules. No paywall. No waitlist. No credit card.
Episode Explorer

All 98 Episodes.
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98 episodes
Architecture Showcase

From Theory to Production

The six systems every production AI engineer must understand.

🗂️
RAG Systems
Retrieval-Augmented Generation — how to give your LLM access to your entire knowledge base without fine-tuning. Parsing, chunking, vector retrieval, reranking, context stuffing.
Module 3Module 414 Episodes
🤖
AI Agents
Tool calling, ReAct loops, multi-agent coordination, memory architectures, failure modes. Build agents that don't just answer — they act, observe, and iterate.
Module 57 Episodes
🗄️
Vector Databases
HNSW indexing, approximate nearest neighbors, Pinecone vs Weaviate vs pgvector, hybrid search, scaling to billions of embeddings in production.
Module 37 Episodes
⚡
Model Serving
vLLM, TGI, Ollama, OpenAI API spec, streaming, prompt caching, rate limiting, load balancing. Serve AI to thousands of users without melting your infra.
Module 67 Episodes
🎯
Fine Tuning
LoRA, QLoRA, when to fine-tune vs RAG, training data quality, evaluation frameworks, model merging, RLHF, DPO. Make the model yours — without a supercomputer.
Module 77 Episodes
🏗️
AI SaaS Infrastructure
How ChatGPT, Cursor, Perplexity, and Midjourney actually work end-to-end. Build your own production AI SaaS with real architecture, not demos.
Module 147 Episodes
Learning Outcomes

By Episode 98 You Will Understand

Not at a surface level. At the level of someone who has shipped AI to production, debugged inference latency at 3am, and explained it to a CTO.

Start the Journey →
🧠
M1–M2 · Episodes 1–14
LLM Internals & Local Inference
Tokens, transformers, parameters, inference, context windows, KV cache, quantization, speculative decoding.
🔍
M3–M4 · Episodes 15–28
RAG & Vector Architecture
Embeddings, HNSW, hybrid search, chunking, retrieval strategies, and end-to-end RAG deployment.
🤖
M5–M6 · Episodes 29–42
AI Agents & Model APIs
Tool calling, ReAct, multi-agent systems, streaming, prompt caching, and production serving.
🎯
M7–M8 · Episodes 43–56
Fine-Tuning, Security & Alignment
LoRA, QLoRA, guardrails, prompt injection, privacy, cost optimization, and observability.
🚀
M9–M10 · Episodes 57–70
Frontier Models & GPU Infrastructure
MoE, multimodal, diffusion, test-time compute, VRAM math, multi-GPU, FlashAttention.
🔤
M11–M12 · Episodes 71–84
Tokenizers, Formats & Protocols
BPE, GGUF, SafeTensors, MCP, A2A, function calling, structured output, semantic caching.
⚙️
M13–M14 · Episodes 85–98
MLOps & Production AI SaaS
Model registries, CI/CD for AI, scaling laws, evals — and how ChatGPT, Cursor, Perplexity are built.
Start Now

Stop Using AI.
Start Building With It.

98 episodes. 14 modules. One complete AI engineering roadmap.
Free. Forever. Starts with Token #1.

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