Technical notes
Insights, guides, and solutions from our team.
AI today rarely gets it wrong, and that's the problem
Models now fail a few times in a hundred, which is exactly why nobody checks them anymore. Where the errors actually cluster, and how to move your verification instead of dropping it.
Three questions to ask an AI vendor
During the demo you only think about price. But three other questions tell you who you are really dealing with, and what happens the day the system breaks.
Vertical AI Projects: Stop Starting From Scratch
Every new chat forces you to re-explain who you are, what you do and what must never be said. Vertical projects fix the problem at the root: one workspace per activity, with permanent instructions that build up one corre
Where the Data You Give AI Really Ends Up
You paste client emails, quotes and staff data into AI without a second thought. But where does it actually go? It's not the tool that decides, it's the plan you use - here's what changes and how to lock it down in minut
AI at Work: Assistant or Actual Colleague?
Most companies use AI as an improved search engine. The real value comes when you treat it like a colleague.
Which Tasks Are Actually Worth Automating?
The most common advice about AI in business is "automate everything you can". Field experience tells a different story.