AI Fundamentals Cheat Sheet for SDETs with Amit Tripathi

AI is becoming part of software testing — but understanding AI terminology shouldn't require a data science degree.

I created this AI Fundamentals Cheat Sheet for SDETs to help Software Testers, QA Engineers, Automation Engineers and SDETs build a practical understanding of modern AI concepts.

This is not a random AI glossary.

The concepts are arranged in a logical learning order, so you understand how everything connects:

AI → Machine Learning → Deep Learning → Generative AI → Foundation Models → LLMs → Tokens → Embeddings → Vector Databases → RAG → AI Agents → Tools → MCP → AI for Testing → Testing AI → AI Quality → AI Security → AI Test Automation

What's inside?

✓ AI & Machine Learning fundamentals

✓ Generative AI & Foundation Models

✓ LLMs and Tokens

✓ Embeddings, Vectors & Vector Databases

✓ RAG

✓ AI Agents & Tools

✓ MCP

✓ Prompt Engineering

✓ AI for Testing

✓ Testing AI systems

✓ AI Quality & Evaluation

✓ AI Security

✓ AI Test Automation

✓ Quick Reference for revision

Every concept is explained from an SDET's perspective

For most topics, you'll get:

What is it?

Think of it as…

Real-world examples

SDET example

Why should an SDET care?

Remember this

So instead of just learning definitions, you'll understand where these concepts appear in real testing work and why they matter.

Who is this for?

• Software Testers

• QA Engineers

• Automation Test Engineers

• SDETs

• Senior SDETs

• QA Leads

• Test Managers

No maths, data science or machine learning background required.

If you're a tester trying to understand AI beyond the buzzwords, this is a practical place to start.

Created by Amit Tripathi — automatewithamit