Ai

201 posts filed under Ai.

A fintech founder asked me to sanity-check their data stack three weeks before a raise. It wouldn't have survived the investor's technical …

Three in four Belgian SMEs now use AI daily or weekly. Most are running it on data they wouldn't trust for a board report.

Your Databricks bill is mostly DBUs. A lot of those DBUs run ETL that never needed Spark in the first place.

Praising the engineer who fixes everything at 2am rewards the exact dependency that eventually takes the platform down with them.

Streaming has a cost nobody puts in the business case: the weekly tax of running it after the demo works.

Investor technical due diligence has one real question: will this stack survive the growth the round is funding?

You bought a semantic layer to end the "which number is right" argument. Eighteen months later you have 200 metrics and the same argument, …

The 2026 data tooling is the best it's ever been. The bottleneck in most teams I see is still a leader who can't say, in two sentences, what …

Run your AI feature twice on the same input. If a different answer would be a problem, you've found a deterministic requirement.

Most teams collect everything "just in case," then try to add privacy when an audit looms. By then it's in 40 tables.

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