Ep45: Starting a Podcast: What We Got Wrong, What We Learned, and What’s Next

Join Our Upcoming AI Evals Cohort! https://maven.com/dataneighbor/ai-evalsSubscribe to our newsletter: https://dataneighbor.substack.com/DNP Swag Store: https://shop.dataneighbor.com/In this episode of the Data Neighbor Podcast, we do something different. No guest. Just the three of us reflecting on what we learned after a year of running the show.We talk honestly about what surprised us most, what turned out to be harder than expected, and why the “real work” of podcasting is everything around the recording: editing, publishing, distribution, and yes, thumbnails.We also dig into what hosting a podcast has done for our careers: better communication reps, more surface area in the industry, and a faster growing network than we expected.Finally, we share a preview of what we are building in 2026, including two big themes we keep seeing across the industry: AI product evaluation and AI powered analytics.If you are thinking about starting a podcast, already building one, or just want a candid behind the scenes look at what it takes to stay consistent for a full year, this episode is for you.Connect with the team (tell us which platform sent you!):Shane Butler: https://linkedin.openinapp.co/b02feSravya Madipalli: https://linkedin.openinapp.co/9be8cHai Guan: https://linkedin.openinapp.co/4qi1rIn this episode, you’ll learn:- What nobody tells you about the time investment behind a podcast- Why consistency is the hardest part, and how to design for it- How having multiple co hosts reduces burnout and improves the show- How podcasting can expand your network and professional opportunities- What we learned from a year of interviewing builders and operators- What we are focusing on in 2026: AI evaluation and AI powered analytics#podcasting #podcast #creator #contentcreation #careergrowth #networking #aiproduct #aievaluation #analytics #datascience #dataneighbor

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