Behind The Product

SEP has been building software products for over 30 years, but data as a dedicated practice is newer. In this episode, Zac Darnell sits down with SEP's Director of Data, Jason LaJeunesse, and Solution Architect Jason Dossett to unpack how SEP thinks about data: what it is, why it matters now more than ever, and what companies get wrong when trying to move fast on AI without the right foundation underneath it.
The conversation moves from definitions (what "data as a product" actually means versus the operational databases most software shops have always built) to the real-world patterns SEP has seen work (and fail) inside energy, aerospace, and other complex organizations.
We dig into how modern data platforms have shifted from a single analyst's concern to a strategic business asset, why the rise of agentic AI has made governance non-negotiable, and what an incremental goal-oriented approach to data strategy actually looks like in practice. The Jasons also make the case that the biggest gap inside most organizations isn't technology. It's enablement.
Takeaways from this episode:
Data as a service isn't about operational databases powering apps. It's about centralized, strategic platforms with downstream use cases across the business
Analytics engineering applies software engineering disciplines (version control, DevOps, automated documentation) to data work, and it's a natural fit for SEP's background
LLMs don't have your business context. Without good data grounding, governance, and role-based access controls, agentic systems can't operate safely
The "big bang" approach to governance almost always fails. Start goal-oriented, slice vertically, and let governance mature incrementally
Many organizations are missing an enablement layer, someone who bridges the platform team and the people trying to use it
Platform engineering is becoming a more critical discipline as AI commoditizes work below the platform level

We'd love to hear from you! Reach out to podcast@sep.com to share your feedback on this show.
You can find more information about this podcast at sep.com/podcast and subscribe wherever you get your podcasts. Thanks for listening!

In this episode, host Zac Darnell and co-host Raman Ohri sit down with The Purdue Data Mine's, Executive Director, Mark Daniel Ward and COO, Katie Sanders. Mark and Katie walk us through how they’ve built a program where students from every major, not just data science, tackle real data problems for industry partners, and why that intentional cross-disciplinary design is exactly the point.
We dig into what it means to build a data-ready workforce at scale, how the explosion of AI has reshaped project demand (53 of 92 active projects now involve AI), and what companies actually get out of partnering with The Data Mine. From getting backlogged projects off the shelf to building a recruiting pipeline with early-career talent that’s already been road-tested on their real problems, along with what they're seeing from their industry partners.
Takeaways
The Data Mine’s model is built on real-world work, not simulated problems; students are solving the same issues that industry partners face today.
Cross-disciplinary teams produce stronger outcomes because different majors bring different lenses to the same data problem.
Companies engage The Data Mine for two distinct reasons: recruiting pipeline and getting internal projects done.
AI has rapidly reshaped project scope, over half of active engagements now include an AI component, up significantly from just a few years ago.
Students are early enough in their careers that they aren’t locked into habits, making them unusually open to adopting new tools and approaches.
The program is a low-friction entry point to a deeper university research relationship, some engagements evolve into sponsored research agreements.

We'd love to hear from you! Reach out to podcast@sep.com to share your feedback on this show.
You can find more information about this podcast at sep.com/podcast and subscribe wherever you get your podcasts. Thanks for listening!

In this episode of Behind the Product, host Zac Darnell and co-host Raman Ohri sit down with Karen Hyman, VP of Data Governance at Rolls-Royce. Karen shares her journey from software engineer to leading data governance across a highly regulated, global enterprise and what it really means to balance compliance with innovation at scale. We dig into the nuances of managing data across multiple business units and international regulatory frameworks, and explore how AI is quietly reshaping the conversation around data quality and governance. This episode also kicks off a new series on the show focused on data and we think it's a great one to start with.
Takeaways:
Data governance is not merely a barrier; it should facilitate compliance while fostering innovation.
Karen Hyman's journey from software engineer to VP of Data Governance illustrates the importance of foundational technical knowledge.
Effective data governance requires a nuanced understanding of compliance across various global regulations and standards.
The integration of legacy systems into modern data governance strategies presents unique challenges for organizations like Rolls-Royce.
To successfully transition into data governance, professionals must cultivate a comprehensive understanding of data processes and compliance requirements.
AI advancements underscore the necessity for high-quality data, emphasizing that data governance frameworks must continuously evolve.

We'd love to hear from you! Reach out to podcast@sep.com to share your feedback on this show.
You can find more information about this podcast at sep.com/podcast and subscribe wherever you get your podcasts. Thanks for listening!

In this episode of Behind the Product, host Zac Darnell and co-host Lauren Lecoffre sit down with Sentry's Director of Engineering, Indragie Karunaratne. He shares how Sentry transformed from error monitoring into a multi-product observability platform. We discuss the hard-won lessons of product expansion, balancing AI experimentation with focused execution, and maintaining developer experience across 100+ platforms. Our conversation was a wonderfully candid and real discussion on what it can look like to navigate challenges teams face in these areas.
Key Takeaways
Multi-product strategy needs a clear rubric
Protect capacity for long-term bets
Multi-product expansion multiplies SDK complexity
Session Replay eliminates debugging guesswork
Fair Source balances openness with business protection

In this episode of Behind the Product, host Zac Darnell and co-host Raman Ohri sit down with AI strategist Angie Carel for a refreshingly candid conversation about the human side of AI adoption. From why skipping AI literacy is a guaranteed misstep, to how “corporate recess” can spark innovation. Angie brings clarity, empathy, and a touch of urgency to a rapidly evolving space. Whether you're a seasoned leader or just dipping your toes into the AI space, this one’s packed with insight and inspiration.
3 Key Takeaways:
AI Literacy is Non-Negotiable: Organizations fail when they skip foundational education. Without a baseline understanding, fear and misuse take hold.
Adoption Starts with Play: Introducing “corporate recess” gives employees a low-risk space to experiment, share, and discover meaningful use cases.
Experience Still Matters: Great outputs from GenAI come when real-world knowledge meets strong prompting—tools don’t replace wisdom.

We'd love to hear from you! Reach out to podcast@sep.com to share your feedback on this show.
You can find more information about this podcast at sep.com/podcast and subscribe wherever you get your podcasts. Thanks for listening!