Advanced Track
6 lessons for those ready to go deep — prompt chaining, evaluation frameworks, tree of thought, and techniques used by AI engineers building real products.
- 1
Prompt Chaining: Build Multi-Step AI Workflows
Learn how to break complex tasks into a sequence of focused prompts where each output feeds the next — unlocking tasks that a single prompt can't reliably handle.
5 min read - 2
Prompt Evaluation: How to Test and Improve Prompts Scientifically
Move beyond 'this looks good' — learn how to build evaluation frameworks that measure prompt performance with real metrics, A/B testing, and golden datasets.
5 min read - 3
Tree of Thought: Multi-Path Reasoning for Complex Problems
Tree of Thought prompting extends Chain of Thought by exploring multiple reasoning paths simultaneously — dramatically improving performance on complex planning, creative, and decision-making tasks.
5 min read - 4
Meta-Prompting: Using AI to Write Better Prompts
One of the most powerful techniques at the advanced level is turning AI on itself — using it to generate, critique, and optimize your prompts. Here's how meta-prompting works and when to use it.
7 min read - 5
Adversarial Prompting and Red-Teaming Your AI Systems
If you're building anything with AI — a chatbot, a workflow, an automated system — you need to know how it fails under adversarial conditions. Here's how to think about it and what to do about it.
7 min read - 6
Fine-Tuning vs Prompting: When to Use Which
Prompt engineering and fine-tuning are both tools for getting AI to behave a specific way. Understanding when each makes sense — and the real trade-offs — helps you avoid expensive mistakes.
7 min read
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