Summary

In this podcast episode, Wes McKinney co-hosts a conversation with Nell Thomas, VP of Data at Shopify, exploring the modern data stack, organizational culture around data teams, and the impact of AI on data work. Wes draws out discussion on how data organizations have evolved from the early 2010s 'big data' era to today's agent-driven landscape, where every company is effectively a data company. He highlights the tension between AI-powered democratization of data access and the risk of unvetted analyses, noting that agents can stress data platforms like DDoS attacks. The conversation covers the full data value chain from instrumentation to presentation, semantic layer challenges, and the importance of psychological safety in data organizations. Wes shares his excitement about agentic coding while acknowledging the need to channel that enthusiasm productively.

Key Insight

AI agents are simultaneously democratizing data access and threatening data platform stability, as automated query loops replace human rate-limiting and vibe-coded dashboards bypass the carefully curated data pipelines that data teams spent years building.

Spicy Quotes (click to share)

• 5

  I think one of the problems I've been thinking a lot about lately is data teams do all this work to build, to engineer this whole pipeline of data collection, curation, ETL, data cleaning, data quality, and then engineering the data warehouse — and then AI pops up and people using LLMs in all of those different parts of the value chain creates a lot of opportunity, but also in every place there's an opportunity for agents gone wild.

• 7

  It's almost not differentiable from a DDoS attack in some cases, where it's just running SQL queries over and over. I imagine that's going to change the way data platforms are designed, with guardrails to help agents not DDoS the data platform.

• 7

  Code now has much less value. It used to be that code artifacts were the product of human labor, and you could attach a cost to this. The code-counting tools like SLOC and CLOC would be like, oh, this codebase would cost $3 million in three years to build. I built it today with my agent.

• 4

  For me, what's happening right now gives me the same feeling that I got when I started to do Python in the late 2000s — I can just write code and do things. Almost 20 years later, it's that same feeling again of, we can just do things.

• 6

  Who says I have to use Tableau's UI? Just give me the endpoints and I'll use Claude Code or I'll use ChatGPT to vibe code my own custom dashboard. And not knowing that what's inside might be some very large SQL queries that the person building their personalized dashboard — they can't read the SQL.

• 3

  In the past, you would say, well, we can't justify staffing a team to build internal tools for certain types of platform observability. Now, that cost equation has changed.

• 2

  If it saves them an hour a day, they might spend a day building the tool. If it saves them an hour a day going forward, that's material savings that can be directed toward something else.

Tone

conversational, exploratory, cautiously optimistic