Start Here
Most people approach AI like this:
- Write a prompt
- Hope it works
- Tweak wording
That works… until it doesn’t.
This series is about a different approach:
Treat AI systems like engineered systems, not magic boxes.
What This Covers
This is a connected series on how modern AI systems actually work:
- Prompt behavior and failure modes
- Structured workflows and chaining
- Agent loops (ReAct)
- Tool calling and execution boundaries
- Planning and decomposition
- Memory and state
- Reliability and guardrails
- When NOT to use agents
Recommended Path
1. Foundations
- Prompt Engineering Is Not About Prompts
- Why Prompts Fail (And How to Debug Them)
- Prompt Engineering Techniques That Actually Work
2. From Prompts to Systems
3. Core Agent Mechanics
4. Building Real Systems
5. System Design Decisions
How to Read This
This is not a set of independent posts.
Each one builds on the previous.
If something feels unclear:
- Go back one step
- Revisit the mental model
- Then continue
Final Thought
AI is not about getting the model to say the right thing.
It’s about designing systems where:
The model has no choice but to behave correctly.