Notes on data, AI, IT
and security
No marketing fog. The way I think about real problems with founders and managers.
From hype to inference cost: why AI must be measured as a production function
How to move from evaluating AI by its demo effect to evaluating it by the real economics of running a model in production.
Breaking up a monolith: why sequence matters more than speed
How to plan a migration away from a monolithic architecture without halting operations - on sequencing, risks, and rollback points.
Kubernetes operators: what the model is and why it matters now
What the operator pattern in Kubernetes is, why it has become the central way to manage complex applications in a cluster, and what that means for architecture.
API versioning is contract management, not a technical formality
Why every API needs a versioning policy, and what happens to integrations when there is none.
An ETL pipeline is a production line - monitor it accordingly
Why ETL failures are an operational incident, not a technical glitch, and how to build visibility into data flows.
Why AI projects die before they produce results: five recurring patterns
An analysis of the typical reasons AI initiatives stall or fail to deliver their promised impact - and what to do about it.
ML in production demands process before MLOps has a name
Why companies that are serious about machine learning inevitably reach the need to version not just code, but data, models, and experiments.
Why IT project estimates are almost always wrong - and what to do about it
The gap between estimated and actual delivery time in IT projects is a known and persistent problem. A look at the structural reasons it keeps happening and the practices that reduce it.
Data breach: what to do in the first 72 hours
A practical breakdown of how companies respond to personal data incidents - and why most of them get it wrong.
API-first for internal systems: why it matters before you have many of them
Building internal tools and systems with an API-first approach is not extra work. It is the discipline that prevents the integration mess most companies spend years untangling.
Cloud vendor lock-in: how to make a conscious decision
When vendor lock-in in the cloud is a reasonable trade-off, and when it is a risk worth assessing upfront.
RPA: what it actually solves and where it hits a wall
Robotic process automation is useful in a specific set of circumstances and fragile outside them. A plain account of what to expect before committing to an RPA project.