Would you like to see all of your AI initiatives, their workflows, and their tools under one fully auditable and traceable view? Every AI initiative in your organisation, the workflows your domain experts build, the coding and reasoning agents your engineers rely on, the external systems each one touches, can live under a single view […]
Category: Artificial Intelligence
The Bill Nobody Modelled
“The future of enterprise AI will not belong to the smartest agents running the most expensive loops, but to the systems disciplined enough to know when to stop thinking and start executing.” Somewhere in a mid-sized software company this quarter, a finance leader is looking at a cloud invoice that has grown faster than revenue, […]
Everybody Has an Agent Now: The Architecture, Economics, and Confusion of Agentic AI
“A word that names everything from a chatbot reply to a swarm of self-directing systems has stopped naming anything at all, and the cost of that vagueness lands on whoever signs the contract.” When a Word Means Everything, It Means Nothing Walk through a week of industry announcements and the word “agent” arrives wearing […]
Demystifying the AI Umbrella: What You Are Actually Buying, Renting, and Building
“The most expensive mistake in enterprise AI is not choosing the wrong model, it is misunderstanding which game you are playing.” What is our AI strategy? The pressure to adopt Artificial Intelligence is immense, and the penalties for inaction feel existential. Yet for many executives, stepping into the AI landscape feels less like strategic planning […]
Why Your AI Agents Are One Update Away from Breaking
An organisation that cannot remember what it decided, or why, is condemned to decide the same things over and over again, each time believing it is the first.
Where Emotions Lie Inside a Neural Network: A CT Scan of LLM Hidden States
Large language models respond to emotionally charged inputs with contextually appropriate outputs, but the mechanism by which they represent, propagate, and modulate emotional tone through their internal layers remains poorly understood. Do emotions “live” in specific layers? Is the signal carried by the attention mechanism, the MLP, or the residual stream itself? And when a model is instructed to be a “helpful assistant,” does its internal representation remain emotionally neutral, or does it mirror the user’s emotional state?
The Memory That Stays. Part 2
The tool is never the bottleneck. The bottleneck is everything the tool cannot see, cannot access, and does not know it should ask about. The Illusion of the Ready-Made Agent In the past months Anthropic’s Cowork graduated from research preview to general availability across all paid plans, bringing desktop-native agentic capabilities to marketing, finance, legal, […]
The Memory That Stays. Part 1
An organisation that cannot remember what it decided, or why, is condemned to decide the same things over and over again, each time believing it is the first.
Small LLM Performance Benchmark – Research Report
This report presents the results of a systematic evaluation of 22 quantized open-source language models across description generation tasks, measuring quality, JSON reliability, and inference efficiency.
The Planning Tax: Why Your AI Agent Feature Might Be Your Worst Investment
Your best feature may be destroying your margins, and your engineering team has no idea. This article isn’t about AI as a productivity tool. It’s about AI as a cost structure, embedded in your product, triggered by your users, and scaling with your revenue. The AI agents embedded in your product are generating a […]