Sam Ferguson, staff product designer at dbt Labs, joins Faith, Paige, and Ric to talk about what AI is actually changing in the day-to-day work of data practitioners and designers alike.

From inline code comments as agent context to the collapse of build costs in product design, Sam shares how constraints that have long defined both design and data work are starting to reorganize. The group also gets into collaboration, governance, and why a lot of the hardest questions AI is surfacing are ones the data industry has been asking for years.

In this episode:

• Why inline code comments could become one of the most valuable inputs for AI agents working in your dbt project

• The typist analogy: how constraints disappear and roles reorganize around new ones

• What outcome-driven workflows actually mean for data practitioners and how it connects to state-aware orchestration

• Why human attention is becoming the real constraint in a world of infinite answers and infinite features

• How to think about delegating the parts of your job you like least to AI, and protecting the parts that matter most

• Why governance and coherence at scale are the next big challenges as agentic workflows become the norm

In this episode of The View on Data, Faith, Ric, and Jerrie discuss their intentions for the new year, focusing on what is in and out in the data world. They emphasize the importance of simplification in data processes, the need for strong documentation, and the value of making learning engaging. The conversation also touches on the pitfalls of over-engineering and the importance of embracing technical challenges.

Takeaways:

• Simplification is key in data work.
• Strong documentation enhances understanding and collaboration.
• Learning should be engaging and relatable.
• Over-engineering complicates processes unnecessarily.
• Embracing technical challenges is essential for growth.
• Curiosity and the willingness to learn are vital in the workplace.
• Making work fun can improve productivity and morale.
• Frameworks help in organizing and simplifying workflows.
• AI tools should assist, not replace human thought.
• It's important to communicate clearly and avoid jargon.

Finding your people in data can change everything. Not just for your career, but for your confidence, your learning, and your sense of belonging in the work.

In this episode of The View on Data, Jerrie, Faith, and Ric talk about what community has looked like for them across the data space, from Coalesce and local meetups to Slack groups, mentorship networks, and the (now legendary) era of Data Twitter.

They talk about:
• What "community" actually means in the data world, beyond networking
• Where to find your people, from conferences and meetups to online spaces
• Why mentorship is often "piecemeal" and skills-based, not one perfect guide
• How to ask for advice in a way that's specific, respectful, and effective
• How community ebbs and flows over time, and why that's normal
• The long-term value of relationships for thought partnership, support, and growth