Context Engineering as a Discipline: Building Governed AI Analytics
Data Engineering Podcast
00:00
Nick Schrock's background and Dagster origins
Nick Schrock introduces himself, his work at Facebook, co-creating GraphQL, and founding Dagster Labs.
Play episode from 02:04
Transcript
Transcript
Episode notes
Summary
In this episode of the Data Engineering Podcast, host Tobias Macey welcomes back Nick Schrock, CTO and founder of Dagster Labs, to discuss Compass - a Slack-native, agentic analytics system designed to keep data teams connected with business stakeholders. Nick shares his journey from initial skepticism to embracing agentic AI as model and application advancements made it practical for governed workflows, and explores how Compass redefines the relationship between data teams and stakeholders by shifting analysts into steward roles, capturing and governing context, and integrating with Slack where collaboration already happens. The conversation covers organizational observability through Compass's conversational system of record, cost control strategies, and the implications of agentic collaboration on Conway's Law, as well as what's next for Compass and Nick's optimistic views on AI-accelerated software engineering.
Announcements
Parting Question
In this episode of the Data Engineering Podcast, host Tobias Macey welcomes back Nick Schrock, CTO and founder of Dagster Labs, to discuss Compass - a Slack-native, agentic analytics system designed to keep data teams connected with business stakeholders. Nick shares his journey from initial skepticism to embracing agentic AI as model and application advancements made it practical for governed workflows, and explores how Compass redefines the relationship between data teams and stakeholders by shifting analysts into steward roles, capturing and governing context, and integrating with Slack where collaboration already happens. The conversation covers organizational observability through Compass's conversational system of record, cost control strategies, and the implications of agentic collaboration on Conway's Law, as well as what's next for Compass and Nick's optimistic views on AI-accelerated software engineering.
Announcements
- Hello and welcome to the Data Engineering Podcast, the show about modern data management
- Data teams everywhere face the same problem: they're forcing ML models, streaming data, and real-time processing through orchestration tools built for simple ETL. The result? Inflexible infrastructure that can't adapt to different workloads. That's why Cash App and Cisco rely on Prefect. Cash App's fraud detection team got what they needed - flexible compute options, isolated environments for custom packages, and seamless data exchange between workflows. Each model runs on the right infrastructure, whether that's high-memory machines or distributed compute. Orchestration is the foundation that determines whether your data team ships or struggles. ETL, ML model training, AI Engineering, Streaming - Prefect runs it all from ingestion to activation in one platform. Whoop and 1Password also trust Prefect for their data operations. If these industry leaders use Prefect for critical workflows, see what it can do for you at dataengineeringpodcast.com/prefect.
- Data migrations are brutal. They drag on for months—sometimes years—burning through resources and crushing team morale. Datafold's AI-powered Migration Agent changes all that. Their unique combination of AI code translation and automated data validation has helped companies complete migrations up to 10 times faster than manual approaches. And they're so confident in their solution, they'll actually guarantee your timeline in writing. Ready to turn your year-long migration into weeks? Visit dataengineeringpodcast.com/datafold today for the details.
- Your host is Tobias Macey and today I'm interviewing Nick Schrock about building an AI analyst that keeps data teams in the loop
- Introduction
- How did you get involved in the area of data management?
- Can you describe what Compass is and the story behind it?
- context repository structure
- how to keep it relevant/avoid sprawl/duplication
- providing guardrails
- how does a tool like Compass help provide feedback/insights back to the data teams?
- preparing the data warehouse for effective introspection by the AI
- LLM selection
- cost management
- caching/materializing ad-hoc queries
- Why Slack and enterprise chat are important to b2b software
- How AI is changing stakeholder relationships
- How not to overpromise AI capabilities
- How does Compass relate to BI?
- How does Compass relate to Dagster and Data Infrastructure?
- What are the most interesting, innovative, or unexpected ways that you have seen Compass used?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on Compass?
- When is Compass the wrong choice?
- What do you have planned for the future of Compass?
Parting Question
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
- Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The AI Engineering Podcast is your guide to the fast-moving world of building AI systems.
- Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
- If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com with your story.
- Dagster
- Dagster Labs
- Dagster Plus
- Dagster Compass
- Chris Bergh DataOps Episode
- Rise of Medium Code blog post
- Context Engineering
- Data Steward
- Information Architecture
- Conway's Law
- Temporal durable execution framework
The AI-powered Podcast Player
Save insights by tapping your headphones, chat with episodes, discover the best highlights - and more!
