No hype. Just what works in production.
The long-form home of @dataeng.ai. Carousels and reels compress ideas; this is where they get the full breakdown, the code, and the evidence.
Research to Production
Research results translated into production defaults. The papers, the benchmarks, and what to actually change on Monday.
2 POSTS
PILLAR 02Failure Modes / 2 AM Pager
What breaks at 2 AM and why. Incident-shaped lessons from production AI systems.
3 POSTS
PILLAR 03Tool Verdicts
Verdicts on the tools touching your data. What changed, what it costs, who owns the toggle.
1 POST
Your pipeline samples 2%. Judge all of them.
MotherDuck ran the numbers on judging all 100,000 rows: 89% accuracy, 40 seconds, fifty cents. The blocker was never accuracy. It was price.
Airflow 3.3.2 shipped an upgrade trap, and the error message lies.
pandas 3 renames the DataFrame class path and XComs record the old one. Upgrade Airflow on every worker first, or the error message will send you chasing your config.
dbt turned its AI on by default. Check the toggle.
From September 1, Wizard and Copilot ship enabled and every future dbt AI feature auto-enables. The meter is running, and the pool is shared.
Your demo worked. Your AI product won't.
Your demo ran on ten hand-picked examples. Production is the long tail of real inputs. Four things break, and none of them are the model.
Your support bot is hallucinating. Blame the dumpster, not the model.
2:14 AM. The bot is inventing refund policies. The retriever is fine and the prompt is fine. The problem is the fourteen thousand tokens of dumpster you fed it.