Practical views on applied AI
Short, honest points of view on building AI that ships and holds up. No hype, no jargon for its own sake.
Own your AI, do not rent it
If you cannot inspect the code, the prompts and the data, you do not really control the system running your business.
Read → 19 June 2026What the first week of an AI rollout looks like
On day one we install one controlled workflow. By day seven you can see it working and see the exceptions.
Read → 19 June 2026Name the workflow, not the technology
Scope an AI project by naming the job it removes, costing the manual version, and measuring the governed replacement against that number.
Read → 19 June 2026Why we build the exception queue first
A reliable automation routes anything it is unsure about to a person, with the context attached. That queue is where trust in the system is built.
Read → 19 June 2026Build, buy, or automate: a simple test
Before paying for another tool or a custom build, decide which of the three your problem actually needs.
Read → 18 June 2026What AI governance actually means for a board
The real test of AI governance is whether you can reconstruct what a system did and why, months later, for someone with the power to penalise you.
Read → 18 June 2026Why we measure every AI build against one number
Most AI programmes stall on the choice of first project. Scoring every candidate on monthly payback settles the choice with arithmetic instead of opinion.
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