Enterprise leaders don't need to build AI systems. They need to understand them well enough to make good decisions about them. This series strips away the jargon and explains every core concept in plain language, from foundational building blocks to the compound systems reshaping how organisations operate.
Start Here
If you're new to AI, start with the glossary. We wrote it because every second meeting in 2023 stalled on terminology. LLM, RAG, fine-tuning, hallucination, embedding: these words get thrown around without shared definitions. The glossary fixes that.
The glossary - May 2023
Generative AI Glossary: The Terms Enterprise Leaders Actually Need
Glossary·8 min read
The Leadership Requirement
Before diving into technical concepts, a framing piece. AI literacy isn't optional for leaders anymore. The gap between leaders who understand AI and those who don't is already visible in decision quality. This post maps the failure modes and the fastest path to literacy.
Why this matters - Jun 2023
AI Literacy Is Now a Leadership Requirement
Article·8 min read
The Foundations
Three concepts that underpin everything else. LLMs are the engine. RAG is the pattern that connects them to your data. Together, they're the starting point for 80% of enterprise AI applications.
The engine - Nov 2023
What Is an LLM? A Plain-English Guide for Enterprise Leaders
Glossary·7 min read
The connection pattern - Aug 2023
What Is RAG? The Pattern Behind Most Enterprise AI
Glossary·7 min read
The search layer - Aug 2024
What Is Vector Search? The Engine Behind Enterprise AI Retrieval
Glossary·5 min read
Going Deeper
Once you understand the basics, three concepts extend them. Fine-tuning customises a model's behaviour. Advanced RAG handles the complexity that basic RAG can't. Together, they take enterprise AI from prototype to production.
Customisation - Mar 2024
What Is Fine-Tuning? (And When You Don't Need It)
Glossary·5 min read
Production patterns - Apr 2024
Advanced RAG Patterns for Enterprise
Guide·7 min read
The New Capabilities
AI is evolving fast. These four concepts represent the current frontier: models that see and hear, systems that use computers like humans do, AI that takes actions autonomously, and orchestration that coordinates it all.
Beyond text - Feb 2025
What Is Multimodal AI? A Guide for Enterprise Leaders
Glossary·5 min read
AI that acts - Jun 2024
What Is Agentic AI? The Next Enterprise Capability
Glossary·5 min read
The last mile - Aug 2025
What Is Computer Use AI?
Glossary·6 min read
The coordination layer - May 2025
What Is AI Orchestration?
Glossary·5 min read
The Big Picture
Two posts that tie it all together. Compound AI is the principle: systems that chain multiple models, tools, and reasoning steps outperform single-model approaches by 2-5x. An AI Foundation is the strategy: shared infrastructure that makes every new capability cheaper and faster to deploy.
The principle - Mar 2025
What Is Compound AI?
Glossary·6 min read
The strategy - Jul 2024
What Is an AI Foundation?
Glossary·5 min read
Why This Series Exists
We write these because our clients ask. Not in sales meetings, but in the quiet moments after a workshop when someone says: "Can you explain that again, without the acronyms?" Every post in this series is the answer to a question a real enterprise leader asked us.
If you're evaluating AI for your organisation, read the foundations first, then jump to whatever concept matters most to your context. If you're building an AI team, share the whole series. A shared vocabulary is the fastest path to better decisions.
The biggest barrier to enterprise AI adoption isn't technology. Every post in this series is an attempt to close that gap, one concept at a time.
Mak Khan
Chief AI Officer