Published in Sep-2026

THE AI EVAL MINDSET

30 Focused Lessons for Testing AI That Works in the Real World

A practical framework for evaluating AI systems end to end.

Buy on Amazon

Who Is This Book For?

From beginners getting started in AI testing to engineering leaders scaling enterprise AI reliability.

For AI & ML Engineers

AI & LLM Developers

Architects and machine learning engineers building generative AI apps who need structured evaluation harnesses, benchmark datasets, and safety filters.

For QA & SDETs

Quality & Test Engineers

Software testers and automation specialists evolving their skill set to lead AI testing, probabilistic quality engineering, and autonomous agent verification.

For Leadership & CTOs

Engineering Leaders & CTOs

Tech leads and executives wanting confidence that AI features deployed to enterprise customers are safe, reliable, and compliant.

All Publications & Upcoming Titles

Explore the expanding library of quality engineering, AI evaluation, and distributed systems books by Millan Kaul.

The AI Eval Mindset
Available Now

THE AI EVAL MINDSET

30 Focused Lessons for Testing AI That Works in the Real World. Practical frameworks for evaluating LLMs, agents, and guardrails.

Next Title
Coming Soon

THE AI GUARDRAILS MINDSET

Reader Feedback & Praise

Early feedback, reviews, and takeaways from engineers and quality leaders reading Millan's books.

A must-read practical guide for every software tester transitioning into AI. Millan breaks down complex evaluation concepts into actionable engineering lessons.

Quality Engineering Practitioner AI & Test Automation Specialist

Finally, a book that moves past the hype to address real-world challenges in AI reliability, guardrails, and probabilistic evaluation.

Engineering Leader Enterprise AI Solutions

Start Building Your AI Eval Mindset Today

Available worldwide on Amazon in Paperback, Hardcover, and Kindle format.

Get Your Copy now
AI Books & Guides Testing AI & LLMs Eval AI Frameworks AI Guardrails & Trust Beginners in Testing AI Scaling AI Evaluation AI & ML Engineers Testing Autonomous Agents
80 Total Articles
17 Categories

blog

My first AI eval was boring - day 02

less than 1 minute read

Setting up a basic LLM evaluation only to find the initial results predictable, but discovering why simple tests are the best place to start.

Why AI Agents Need a Test Harness

4 minute read

AI agents do not become reliable because the model is bigger. They become reliable because the harness around the model is testable, observable, and continuo...

Where MCP Shines

less than 1 minute read

“Single LLMs hallucinate. Multi‑agent systems multiply the problem.”

How MCP Works?

1 minute read

“MCP handshake → tool call → your code runs. 3 minutes to understand.”

Why MCP?

1 minute read

“Last week my LLM swore the 2024 World Cup winner was ‘Moon United FC’. It was confident, detailed, and 100% hallucinated.”

When to Use MCP?

1 minute read

MCP = LLM lifeline when models hallucinate most.

What is MCP?

1 minute read

Model Context Protocol (MCP) = Standardized way for LLMs to discover and call your external tools/data.

Back to top ↑

ai

My first AI eval was boring - day 02

less than 1 minute read

Setting up a basic LLM evaluation only to find the initial results predictable, but discovering why simple tests are the best place to start.

Why AI Agents Need a Test Harness

4 minute read

AI agents do not become reliable because the model is bigger. They become reliable because the harness around the model is testable, observable, and continuo...

Back to top ↑

article

Back to top ↑

llm-foundations

Back to top ↑

ai-tools

Where MCP Shines

less than 1 minute read

“Single LLMs hallucinate. Multi‑agent systems multiply the problem.”

How MCP Works?

1 minute read

“MCP handshake → tool call → your code runs. 3 minutes to understand.”

Why MCP?

1 minute read

“Last week my LLM swore the 2024 World Cup winner was ‘Moon United FC’. It was confident, detailed, and 100% hallucinated.”

When to Use MCP?

1 minute read

MCP = LLM lifeline when models hallucinate most.

What is MCP?

1 minute read

Model Context Protocol (MCP) = Standardized way for LLMs to discover and call your external tools/data.

Back to top ↑

engineering

My first AI eval was boring - day 02

less than 1 minute read

Setting up a basic LLM evaluation only to find the initial results predictable, but discovering why simple tests are the best place to start.

Back to top ↑

mcp

Where MCP Shines

less than 1 minute read

“Single LLMs hallucinate. Multi‑agent systems multiply the problem.”

How MCP Works?

1 minute read

“MCP handshake → tool call → your code runs. 3 minutes to understand.”

Why MCP?

1 minute read

“Last week my LLM swore the 2024 World Cup winner was ‘Moon United FC’. It was confident, detailed, and 100% hallucinated.”

When to Use MCP?

1 minute read

MCP = LLM lifeline when models hallucinate most.

What is MCP?

1 minute read

Model Context Protocol (MCP) = Standardized way for LLMs to discover and call your external tools/data.

Back to top ↑

quality-engineering

Why AI Agents Need a Test Harness

4 minute read

AI agents do not become reliable because the model is bigger. They become reliable because the harness around the model is testable, observable, and continuo...

Back to top ↑

tutorial

Back to top ↑

Leadership

Back to top ↑

tools

Back to top ↑

coding

How MCP Works?

1 minute read

“MCP handshake → tool call → your code runs. 3 minutes to understand.”

Back to top ↑

leadership

Back to top ↑

ai-strategy

Back to top ↑

agents

Where MCP Shines

less than 1 minute read

“Single LLMs hallucinate. Multi‑agent systems multiply the problem.”

Back to top ↑

llm-advanced

Back to top ↑

fintech

Back to top ↑