The Dawn of Agentic Data Workflows
Around 2021, if you wanted AI in a data workflow, you picked a vertical. Coding assistance. Data validation. Each was isolated. That constraint is gone now — and it changes everything.
Real-world insights for data engineers navigating the shift — written by a practitioner, not generated by a machine. Career advice, technical depth, and consulting when you need it.
Practical advice on staying relevant and growing your career as gen AI reshapes the data engineering landscape.
Governance, metadata management, data quality, responsible AI — the durable skills that matter most right now.
Need expert eyes on your data architecture? Reach out for direct consulting on your specific challenges.
Around 2021, if you wanted AI in a data workflow, you picked a vertical. Coding assistance. Data validation. Each was isolated. That constraint is gone now — and it changes everything.
Code comments, unit tests, documentation, diagrams — the stuff that chronically didn't get done. Gen AI changed that completely, and the impact on data teams is bigger than most realize.
I spent years building OLAP cubes. Carefully maintained conformed dimensions, aggregation tables, multidimensional models. That infrastructure was real work. Today, it's increasingly obsolete.