Site Map
A complete overview of all pages on this site. Because sometimes you need to see the whole disaster.
Main Pages
3 pagesCourse Modules
23 pages01: Welcome to Hell (Why You Can't Ignore This Anymore)
You think AI is hype. You might be right. But your manager doesn't think so. Learn what AI actually is (not magic), what it's genuinely useful for, and how to survive the FOMO.
02: The Bare Minimum You Need to Know About LLMs
They predict the next word. That's literally it. Learn about tokens, context windows, and parameters so you don't sound like an idiot in meetings.
03: Prompt Engineering (or: Talking to the Intern Who Knows Everything)
The AI is confident, articulate, and frequently wrong. Learn the techniques that actually work: chain of thought, few-shot examples, and when to just give up.
04: Memory and Context (Why It Forgets Everything)
LLMs have amnesia. Learn about context windows, why it can't remember your project structure, and how modern agentic AI can manage its own memory through files.
05: Code Generation Without Shooting Yourself in the Foot
You're using Copilot already. Let's make you good at it. Generating boilerplate without bugs, identifying deprecated suggestions, and avoiding dependency.
07: Building Your First AI Feature (The Portfolio Project)
You need something real to show in interviews. 'I've played with ChatGPT' doesn't count. Build an actual AI-powered feature you can point to without lying.
08: AI Agents: Tools, Loops and Bankruptcy
Agents use tools, make decisions, and cost more money. Learn what they are, how to build a simple one, and enough to lie about it on LinkedIn.
06: Debugging and Learning: Your New Stack Overflow
Paste the error, get an explanation. Ask about that legacy code nobody understands. AI is genuinely good at this.
09: The Ralph Wiggum Technique
When AI agents get lobotomies between sessions and why that's actually a feature. The autonomous loop pattern for multi-session work.
10: Building Your Own Agentic Coding Tool
How Claude Code actually works under the hood. Code indexing, the harness, multi-session memory, and why 90% of the work isn't AI.
11: Cost Control: Don't Blow Your Budget
How to use AI without explaining to Finance why your prototype cost $2,000
12: Exit Strategies: When AI Makes Things Worse
How to recognize failure, remove AI gracefully, and explain it to stakeholders
13: Agentic Workflows with PocketFlow
Build production-ready AI workflows with 100 lines of code instead of 10,000 lines of framework
14: Testing AI Systems: Without Losing Your Mind
How to build evals, measure AI quality, and prove to stakeholders that your system isn't just expensive autocomplete
15: Talking About AI in Interviews: Without Sounding Like an Idiot
How to answer AI questions without sounding like a fanboy, a hater, or someone who read a blog post yesterday
16: Managing AI Expectations: Dealing With Coworkers
How to survive managers who read articles, juniors who think they're 10x, and the general organizational chaos around AI
17: You Made It (Now Get Back to Work)
Congratulations. You now know enough about AI to be dangerous. Time to close this course and actually ship something.
18: The Glossary of AI Nonsense
Terms you'll hear, what they actually mean, and which ones are bullshit
19: Prompt Templates That Actually Work
Copy-paste prompts for common scenarios. No shame in stealing.
20: Tool Recommendations (January 2026)
What's worth paying for, what's free and good enough, and what to avoid
21: Troubleshooting Common Problems
The AI is being stupid. Here's how to fix it.
23: Works Cited (Yes, We Did Our Homework)
The papers, posts, and documentation we actually read so you don't have to. Plus some commentary on what's worth your time.
22: Fun Projects to Try
Small, ridiculous projects that are actually great for learning