Notes on data, AI, IT
and security
No marketing fog. The way I think about real problems with founders and managers.
AI does not fix bad data
A short note on why an AI rollout in a company starts not with the model, but with the quality of the data underneath.
What data engineering is, and why business needs it before AI
Why companies have to gather and structure data before talking about models and agents.
Excel in a company is not a shame, it is a symptom of growth
Why a company being held together by Excel is not embarrassing, but a signal of which processes have outgrown their tools.
How to tell when your vendor is making the project more complicated than it needs to be
Signals that an executive can pick up early, before the project's problems become impossible to ignore.
Data, IT, and security cannot be separated
Why splitting these three areas across different teams turns any technology project into a quiet source of hidden risk.
How I look at a new technology project
The set of questions I run any new request through, from an AI assistant to industrial analytics.
Simple architecture often beats trendy
How the urge to use the right stack and draw beautiful diagrams quietly breaks projects that could have been running calmly for years.