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AI Education

Demystifying enterprise AI. From glossary basics to compound systems - every concept explained for the people making the decisions.

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.

Glossary

The glossary - May 2023

Generative AI Glossary: The Terms Enterprise Leaders Actually Need

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.

Article

Why this matters - Jun 2023

AI Literacy Is Now a Leadership Requirement

7 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.

Glossary

The engine - Nov 2023

What Is an LLM? A Plain-English Guide for Enterprise Leaders

7 min read

Glossary

The connection pattern - Aug 2023

What Is RAG? The Pattern Behind Most Enterprise AI

7 min read

Glossary

The search layer - Aug 2024

What Is Vector Search? The Engine Behind Enterprise AI Retrieval

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.

Glossary

Customisation - Mar 2024

What Is Fine-Tuning? (And When You Don't Need It)

5 min read

Guide

Production patterns - Apr 2024

Advanced RAG Patterns for Enterprise

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.

Glossary

Beyond text - Feb 2025

What Is Multimodal AI? A Guide for Enterprise Leaders

5 min read

Glossary

AI that acts - Jun 2024

What Is Agentic AI? The Next Enterprise Capability

4 min read

Glossary

The last mile - Aug 2025

What Is Computer Use AI?

6 min read

Glossary

The coordination layer - May 2025

What Is AI Orchestration?

5 min read

The Big Picture

The final posts 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.

Glossary

The principle - Mar 2025

What Is Compound AI?

6 min read

Glossary

The strategy - Jul 2024

What Is an AI Foundation?

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.

Kevin FuavaoChief AI Officer
In this series

Read it in order. 17 pieces.

1

LLMs Explained for Business Leaders

Large Language Models without the jargon. What they are, what they can do, what they can't. Written for the leader who needs to understand, not build.

2

Generative AI Glossary: The Terms Enterprise Leaders Actually Need

A no-nonsense guide to the AI terms showing up in every boardroom - what they mean, and what they don't.

3

AI Literacy Is Now a Leadership Requirement

Leaders who don't understand AI basics are making uninformed decisions about their organisation's future. The three literacies framework applied to the AI era.

4

RAG Explained Simply

Retrieval-Augmented Generation: what it is, why it matters, and why every enterprise AI conversation includes it now.

5

What Is RAG? The Pattern Behind Most Enterprise AI

Retrieval-Augmented Generation is how enterprises give AI access to their knowledge without retraining models. How it works and why most production AI systems rely on it.

6

What Is an LLM? A Plain-English Guide for Enterprise Leaders

Large Language Models power ChatGPT, Claude, and enterprise AI. What they do, how they work, and what actually matters for your business.

7

What Is Fine-Tuning? (And When You Don't Need It)

Fine-tuning trains AI models on your data. It's powerful, expensive, and usually not the right first step. When it actually matters, and when RAG or prompt engineering will get you further.

8

Enterprise Vector Databases in Production

Vector databases in production: Pinecone, Weaviate, pgvector. What works, what breaks, and what we actually use for enterprise AI.

9

Advanced RAG Patterns for Enterprise

Basic RAG gets you started. Advanced patterns like hybrid search, re-ranking, and multi-step retrieval get you to production quality.

10

What Is Agentic AI? The Next Enterprise Capability

Agentic AI doesn't just answer questions - it takes actions, makes decisions, and orchestrates workflows. Here's what that means for enterprise.

11

ML Model Evaluation: Beyond Accuracy

Accuracy is the metric everyone measures. It's not the one that matters most. A rigorous guide to model evaluation for enterprise AI.

12

What Is an AI Foundation?

An AI Foundation is a shared layer of AI capabilities that compounds across an organisation. What it includes, why it matters, and how it differs from isolated AI tools.

13

What Is Vector Search? The Engine Behind Enterprise AI Retrieval

Vector search finds meaning, not keywords. It's the core technology that powers RAG, semantic search, and every enterprise AI system that needs to understand your data.

14

What Is Multimodal AI? A Guide for Enterprise Leaders

Multimodal AI processes text, images, audio, and video together. Here's what it means for enterprise - and where it delivers real value.

15

What Is Compound AI?

Compound AI systems chain multiple models, tools, and reasoning steps together. What the term means and why it matters for enterprise.

16

What Is AI Orchestration?

AI orchestration is how multiple AI components, from models to tools to data sources, are coordinated into a system that actually works. And why it matters for enterprise.

17

What Is Computer Use AI?

AI that can see screens, click buttons, and operate software - just like a human user. Here's what computer use means for enterprise and where it fits in the stack.