Writing on company intelligence.
Enterprise AI, institutional knowledge, and what it takes to make agents actually work.
AI Agents for Regulatory Compliance: Why Context Is the Bottleneck
AI agents are being deployed across compliance functions at speed. The bottleneck is not model quality — it is the institutional context that makes the difference between a generic compliance tool and one that reflects how your organisation actually operates.
Why Basic RAG Fails Enterprise Workloads
Retrieval-augmented generation works well in demos. In production enterprise environments, basic RAG fails in predictable ways that more sophisticated document intelligence solves. Here is what those failure modes look like.
What Are AI Agent Skills? The Missing Layer in Enterprise AI
AI agents can answer questions and generate content. Skills are what let them execute work — following the specific procedures, decision rules, and methods your organisation actually uses. Here is what they are and why they matter.
How to Measure Enterprise AI ROI Before You've Scaled Anything
Most enterprise AI ROI calculations are built on demo performance, not production reality. Here is a framework for measuring what AI actually delivers — including the costs most calculations ignore.
The Consulting Firm's Guide to AI That Actually Compounds
Most consulting firms are using AI as a productivity tool. The firms pulling ahead are using it as a knowledge infrastructure. Here is what the difference looks like — and why it matters more every month.
Why Your Company Knowledge Base Is Failing Your AI Agents
A knowledge base built for human search does not work for AI agents. Here is what needs to change — and why most companies discover this too late.
AI Agents in Financial Services: The Knowledge Problem No One Is Solving
Financial services firms are deploying AI agents without solving the underlying knowledge problem. Here is why that creates regulatory risk — and what the alternative looks like.
How to Capture Institutional Knowledge Before It Walks Out the Door
Most companies lose institutional knowledge faster than they capture it. Here is a practical framework for extracting what experienced people know — and making it available to AI agents and the teams that follow them.
Why Your AI Agents Have No Memory — and Why That's Costing You
Every time your AI agent starts a new session, it forgets everything it knew about your company, your clients, and your decisions. Here is why that is a structural problem — and what fixing it actually looks like.
What Enterprise AI Knowledge Management Actually Means
Enterprise AI knowledge management is not a search engine or a chatbot. It is the system that decides how much of your company's intelligence your AI agents can actually access and act on.
Why Big Four Firms Need a Company Brain Before Their Competitors Build One
95% of enterprise AI pilots fail because AI doesn't know how the company works. Here's why Big Four firms are uniquely exposed — and what the fix looks like.
Why 95% of Enterprise AI Pilots Fail — And the One Fix That Actually Works
MIT's 2025 research confirms 95% of enterprise AI pilots fail to scale. The primary cause isn't the technology. It's the missing knowledge layer between raw company data and reliable AI automation.