Head of Data Management at a European bank — an engineer who now rebuilds how organizations work with AI.
Focus areas
Mined 150k tasks across agile teams to see where work actually goes — and where AI agents remove the most toil.
Impact: The agentization roadmap got re-prioritized by that evidence, not by opinions.
Mined 40k data-team tasks to locate the real bottlenecks in data preparation — then held every standard against that map.
Impact: Standards that removed no bottleneck were killed; governance investment moved to where work stalls.
10+ products built end to end by one person on autonomous agentic pipelines — research tools, data platforms, this site.
Impact: Public proof of the leverage: github.com/pogorelov-labs, 8 open repositories and counting.
Note · Jul 12, 2026
A standard that doesn't remove a bottleneck isn't governance — it's a tax. We wanted to know where our data teams actually lose time, so instead of running a m…
Note · Jul 11, 2026
Short form notes live here now — quick thoughts, links worth keeping, and things I'm reading on data and AI, in between the longer posts. Expect these more oft…
Jan 5, 2025
How to translate data investments into confident, repeatable decisions at the leadership level.
Nov 15, 2024
Lessons from rebuilding analytics stacks to hit reliability, speed, and trust goals.