Coming soon · AI Engineering

The AI Engineering
Blueprint.

Go from "I called an API" to shipping reliable LLM features: retrieval, tools and agents, evaluation, cost and latency, and the system design questions AI-engineering interviews now ask.

One email when it launches, with launch pricing. No spam, ever.

  • How LLMs work, visually
  • RAG end to end
  • Agents & tool use
  • Evals you can trust
  • Cost, latency & safety
Planned contents

What it will cover.

The working outline. Chapters may be added or merged as the book is written and reviewed.

  1. How LLMs work: tokens, attention and context windows, without the maths wall
  2. Prompting you can test and version
  3. Choosing a model: quality, latency and cost
  1. Embeddings and vector search
  2. RAG end to end: chunking, hybrid search and reranking
  3. Evaluating and debugging retrieval
  1. Tool calling and structured output
  2. Agent loops, planning and memory
  3. Integrations with MCP
  4. Guardrails, prompt injection and safety
  1. Evals: test sets, LLM-as-judge and regression checks
  2. Observability and tracing for LLM apps
  3. Cost and latency: caching, batching and model routing
  4. Fine-tuning vs prompting vs RAG
  5. Serving open models
  1. Customer-support assistant
  2. Chat with your documents
  3. AI-powered search
  4. Coding assistant
  5. Voice agent
  6. Content moderation pipeline
  1. AI-engineering interview questions
  2. Architecture cheat sheets
  3. Glossary
Who it's for

Written for you if…

01

Software engineers moving into AI

Use the engineering skills you have, and learn the new pieces properly.

02

Preparing for AI-engineer interviews

The concepts, trade-offs and system designs these roles test.

03

Teams shipping LLM features

A shared vocabulary and checklist for building things that stay reliable.

The HLD Blueprint cover
Available now

Meanwhile, master the system design round.

The HLD Blueprint: Building blocks, the 5S interview method and 25 complete case studies, from URL shorteners to stock exchanges.

FAQ

Questions, answered.

Do I need a machine-learning background?

No. It is written for software engineers. Where a little theory helps, it is explained visually and briefly.

Is it tied to one AI provider?

No. The patterns apply whichever model provider or open model you use; examples point out where providers differ.

When will it be out?

It is being written now, to the same standard as the HLD book. We will not announce a date until it is finished and reviewed. Join the waitlist and you will get one email the day it launches.

What will it cost?

Pricing will be announced at launch. Waitlist members get launch pricing.

More Blueprints

The rest of the library.