Writing
Notes from the transformation layer.
Short essays on analytics engineering, data hygiene, and the awkward place where clean data has to meet the AI that everyone wants to put on top of it.
- Analytics Engineering·September 29, 2026·8 min read
Should I use dbt or write my own SQL pipelines?
A candid, practitioner take on when dbt is the right call, when hand-rolled SQL pipelines are, and what happens when a homegrown stack outgrows the one person who built it. Includes a decision framework for the actual fork in the road.
Read → - Agency Ops·September 22, 2026·6 min read
The three-day question
You emailed the account team a quick question on Monday. It is Wednesday. The three-day question is not a capacity problem. It is a structural one, and it is quietly the most expensive thing on the retainer.
Read → - AI Engineering·September 15, 2026·6 min read
Retrieval on dirty data is a distribution problem
Every RAG post is about chunking, embeddings, and rerankers. Almost none are about the corpus. If your warehouse or your docs disagree with themselves, retrieval just distributes the disagreement, and a smarter model gives you the same wrong answer with better prose.
Read → - AI Engineering·September 1, 2026·6 min read
The semantic layer nobody owns
Between dbt and your dashboards there is supposed to be a place where 'active user' gets defined once. In most stacks it does not exist, and no one has been given the job of making it exist. AI on top of that gap just distributes the disagreement faster.
Read → - AI Engineering·May 4, 2026·5 min read
"We're using Claude for our data" is not a plan
Four different jobs get hidden inside that sentence, and most of them end in wrong answers or wrong data. Map the stack first, then give the model a specific job with a review gate.
Read → - AI Engineering·April 6, 2026·5 min read
What is data hygiene, and why does it matter for AI
Data hygiene means your data is accurate, consistent, and documented. Most data stacks are one of those three things. Here's where the gaps live and why they hit harder once AI is in the loop.
Read → - AI Engineering·March 30, 2026·4 min read
dbt vs natural language: do you still need to write SQL?
The transformation layer isn't going anywhere. The question is who gets to interact with it. Right now the answer is whoever knows SQL. That's a small group.
Read → - AI Engineering·March 23, 2026·4 min read
Why your AI chatbot keeps giving wrong answers
The chatbot isn't broken. It's working exactly as designed on bad inputs. Here's what's actually happening and where the real fix lives.
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