Your data platform used to serve people. Now it has to serve agents too, and that changes what you build and who you hire.
Two people ask an AI agent the same question and get two different numbers back, and neither can explain how their agent got there. That's the moment a data leader realises the platform wasn't built for this world.
Ross Katz, principal and data science lead at CorrDyn, works with data teams every day as they rebuild their platforms for a world where agents, not dashboards, are the main consumer of data.
You'll get a clear framework for what actually changes on a data team when agents become primary consumers, the warning signs that tell you it's time to invest in your data foundation, and a practical way to think through build versus buy versus hire. Ross also makes the case for why judgment, not production, is now the scarce resource on any data team.
Ross covers the new org chart split between platform and distribution work for humans and for agents, why judgment has become the bottleneck, and how tacit knowledge gets written into semantic layers and tools like MotherDuck Guides. This is for data and analytics leaders deciding how to structure their teams around agentic AI, not for anyone after a hype pitch on AI replacing analysts.
Key Takeaways
- The data team's job hasn't changed: curating knowledge and adding context, but who's consuming it has, and that reshapes the platform you need to build.
- One specific failure mode is coming for every data team running agents at scale, and it involves two conflicting numbers that nobody can explain.
- There are three real reasons to bring in an external team instead of building in-house, and only one of them is about missing skills.
- AI should raise your standard for "done", not lower it, but only if you're using it the way Ross argues you should.
Chapter Markers
00:00 - Introduction: agents as the new data consumer
00:49 - How the data team's role has evolved with AI
05:11 - Why context now flows to agents, not dashboards
09:43 - Warning signs it's time to invest in your data foundation
16:11 - Build vs buy vs hire: the real decision drivers
21:38 - Designing the org chart for platform and distribution
29:22 - Why judgment is the bottleneck, not production
34:01 - Which data roles disappear, and which get created
36:29 - Turning tacit knowledge into documented context
43:22 - What We're Watching: who AI actually helps
48:09 - Recap and key takeaways
Useful Links & Resources
- CorrDyn: corrdyn.com
- Katie Bauer's platform vs distribution framework, referenced from her work at Hex: https://hex.tech/blog/data-teams-in-ai-era/
- Otis et al. research on AI and Kenyan business owners, discussed in the What We're Watching segment: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4671369
- MotherDuck Guides, for organisation-level data documentation: https://motherduck.com/docs/category/guides/
- Previous Eventual Consistency episode with Dave Yaffe on AI governance: https://www.corrdyn.com/podcasts/eventual-consistency/ep-27-prefect-dagster-orchestration/
Connect With the Show
- Ross Katz on LinkedIn: https://www.linkedin.com/in/b-ross-katz/
- Ross Katz on X: https://x.com/brosskatz
- CorrDyn on LinkedIn: https://www.linkedin.com/company/corrdyn/
- Website: corrdyn.com
Where does your team stand right now: are you still building platforms purely for human consumers, or have agents already started showing up in your query logs? Tell us what you're seeing.
If you want to talk about your data challenges, or you think we got something wrong, find us at corrdyn.com.
