Series · Part 15 of 21
Practice
How Do You Know AI Is Actually Working?
Demos always look good. Production AI degrades silently. Here's the evaluation framework — from exact match to human review — and how to catch hallucinations.
Every AI demo looks impressive. The demo was designed to. The real question is whether it works reliably across all inputs, over time — and for that you need evals.
Start at the bottom of the pyramid (exact match) and work up only as needed. 50 carefully chosen test cases run on every deploy beat 5,000 examples run once.
Next up: Part 16 starts the Hands-On track — set up your Python environment and run real AI code from scratch.
AI Demystified · 16 of 21 published
- 0 Grounding 5 Mental Models You Need Before Diving Into AI
- 1 Foundation What Happens When You Ask AI Something?
- 2 Foundation Transformers — The Architecture That Changed Everything
- 3 Foundation How AI Learns, Thinks, and Decides
- 4 Foundation How AI Reads Your Words
- 5 Foundation Why AI Forgets
- 6 Foundation Why AI Lies (And Doesn't Know It)
- 7 Foundation What AI Cannot Do
- 8 Foundation How AI Reasons (And Why It Sometimes Breaks)
- 9 Practice Prompt Engineering — How to Talk to AI
- 10 Practice Embeddings & Vector Databases — The Memory Layer of AI
- 11 Practice RAG Explained — How AI Knows What You Didn't Train It On
- 12 Practice Fine-tuning vs. Prompting — When to Use Which
- 13 Practice Do You Really Need GPT-4?
- 14 Practice Latency, Tokens, and Cost — The Physics of AI Products
- 15 Practice How Do You Know AI Is Actually Working?
- 16 Hands-On Coding Setup — Your AI Development Environment soon
- 17 Hands-On MCP Tool Calling — How AI Uses Tools soon
- 18 Hands-On AI Agents — Beyond Chatbots soon
- 19 Hands-On Build Your First Real AI App soon
- 20 Hands-On Token Optimization — Spend Less, Get More soon
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