Notes on data, AI, IT
and security
No marketing fog. The way I think about real problems with founders and managers.
Event-driven architecture: what decoupling services actually buys you
A plain explanation of event-driven patterns for owners and managers - what problems they solve, what new problems they introduce, and when the tradeoff makes sense.
Lakehouse: a storage architecture without choosing the lesser evil
What the lakehouse approach is and when it solves the real problem of choosing between a data warehouse and a data lake.
Zero trust architecture: what it means in practice for a growing company
A clear explanation of zero trust as an operational security model - what changes, what stays the same, and how to approach adoption without a rewrite of everything.
Multimodal models: what is actually useful for business right now
A practical look at AI models that work with text and images together - without the marketing fog.
Observability for product teams: what logs, metrics, and traces actually give you
A plain walkthrough of the three observability pillars and why the combination matters - written for technical owners who want to understand what they are paying for.
NIS2: the directive starts living in practice, not just in PDFs
What NIS2 enforcement means for companies operating in the European market: who is covered, what is required, and where to start.
OpenAI DevDay 2024: what the announcements mean for product teams
A short reading of the October DevDay announcements - real-time API, prompt caching, fine-tuned evals - focused on what changes for teams building on top of OpenAI.
Vector databases: what they actually store and when you need one
A plain explanation of what vector embeddings are, what vector databases do differently from relational or document stores, and when the technology is worth adding to your stack.
Data transformation in SQL: why it belongs in a repository
How moving from scattered scripts to versioned transformations changes the maturity of an analytics team.
Feature flags: how incremental delivery reduces release risk
What feature flags are, why teams that use them release faster and break things less, and what an owner or manager needs to know before adopting them.
Agentic AI: the first questions a manager should ask
What AI agents are, how they differ from standard LLM tools, and which questions to ask before deploying them.
LLM hallucinations: why they happen and what it costs the business
A practical explanation of why language models confidently state things that are not true - and how to decide whether that risk is acceptable in your case.