Start Here
If you read only one thing on this site, start with the Core System Design section below.
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.
The Core Idea
Real-world AI systems are not just prompts or models.
They are composed systems with interacting layers:
Retrieval → Validation → Planning → Memory → Evaluation
Each layer solves a different problem.
Most failures happen when one of these layers is missing.
Core System Design (Start Here if You Want Depth)
This is the most important part of this site.
- Part 1: Explaining Procurement Decisions with Agentic RAG
- Part 2: Gate Checks in AI Systems
- Part 3: Planning in Agents
- Part 4: Agentic Memory
- Part 5: Learning Agents (Evaluation & Feedback)
Foundations
Start here if you are new to system-level thinking:
- Prompt Engineering Is Not About Prompts
- Why Prompts Fail (And How to Debug Them)
- Prompt Engineering Techniques That Actually Work
From Prompts to Systems
Core Agent Mechanics
Building Real Systems
System Design Decisions
How to Read This
This is not a set of independent posts.
Each layer builds on the previous:
- Learn prompting
- Understand agents
- Learn system design
- Study real implementations
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.