Half Stack Data Science

In this episode, we tackle the question of learning in the age of AI.Among other things, we talked about:whether worrying about AI is the same as worrying about calculatorswhy David gets all his students to turn AI features off while learningwhy rising token prices might end up being a great thingwhether AI slop is worse than human slopwhat we can learn from sailing as we think about our future in an AI world---A reminder that David’s book, The Well-Grounded Data Analyst is out! ⁠⁠https://www.manning.com/books/the-well-grounded-data-analyst⁠⁠If you want to find out more, we have a whole episode about it: ⁠https://halfstackdatascience.com/s3-finale-the-well-grounded-data-analyst-with-david-asboth

In this episode, we discuss:- Will people really just write all their own software instead of buying it?- Is the change management around GenAI projects any different from other technologies?- What is the right approach when giving people freedom to vibe code internal tools?- Is there room for a new role to emerge as a bridge between vibe coding and useful internal tools, a technical connector of AI capability and business value?Things we mention in the episode:- Matthew Yglesias's tweet about vibe coding: https://x.com/mattyglesias/status/2049105745132585161- Vicki's post on BlueSky about software libraries: https://bsky.app/profile/vickiboykis.com/post/3mkpmimhnls2q- That paper about fake GitHub stars: https://awesomeagents.ai/news/github-fake-stars-investigation/- The reverse centaur article: https://pluralistic.net/2025/12/05/pop-that-bubble/#u-washington---David’s book, The Well-Grounded Data Analyst is out! ⁠https://www.manning.com/books/the-well-grounded-data-analyst⁠If you want to find out more, we have a whole episode about it: https://halfstackdatascience.com/s3-finale-the-well-grounded-data-analyst-with-david-asboth

In the first episode of the new season, we discuss:whether it's a good thing that we can produce more with GenAI,how GenAI will force us to consider the purpose of education,how we are supposed to develop wisdom if GenAI can just build everything for us,how AI-written code introduces "cognitive debt",and in a roundabout way we discuss whether GenAI will kill software companies---David’s book, The Well-Grounded Data Analyst is out! ⁠https://www.manning.com/books/the-well-grounded-data-analyst⁠If you want to find out more, we have a whole episode about it: https://halfstackdatascience.com/s3-finale-the-well-grounded-data-analyst-with-david-asboth

In this episode, we wrapped up 2025 by reflecting on what we talked about on the podcast, where AI is and where it's heading, and looked ahead to 2026. We also discussed some of our favourite sci-fi books we read last year!Links from the show:- that YouTube video Shaun mentioned, "Are we stuck with the same Desktop UX forever?": https://www.youtube.com/watch?v=1fZTOjd_bOQ- our interview with Scott Hanselman whose blog post about Dark Matter Developers is always on our mind: https://halfstackdatascience.com/s4e1-meaningful-uses-of-ai-with-scott-hanselman- our interview with Kirsten Hill who's empowered by AI to build the survey platform of her dreams: https://halfstackdatascience.com/s4e4-better-survey-design-with-ai-with-kirsten-hillThe sci-fi books we mentioned (and loved):- The Three-Body Problem (book 1 of the Remembrance of Earth's Past trilogy): https://www.goodreads.com/book/show/20518872-the-three-body-problem- Children of Time: https://www.goodreads.com/book/show/25499718-children-of-time- Sea of Tranquility: https://www.goodreads.com/book/show/58446227-sea-of-tranquility- Sleeping Giants (book 1 of The Themis Files trilogy): https://www.goodreads.com/book/show/25733990-sleeping-giants---David’s book, The Well-Grounded Data Analyst is out! ⁠https://www.manning.com/books/the-well-grounded-data-analyst⁠If you want to find out more, we have a whole episode about it: https://halfstackdatascience.com/s3-finale-the-well-grounded-data-analyst-with-david-asboth

In this episode, we spoke to Kirsten Hill.Dr Kirsten Hill is a researcher, writer, and the founder of bisque — a survey platform that actually cares if you get good data. She has a Ph.D. from the University of Pennsylvania, has led research for the Bill & Melinda Gates Foundation, and has worked with over 100 mission-driven teams on measurement & evaluation. This past year, she authored her first book, Ask Better Questions, a top release on survey design — and realized that writing the book wasn’t enough. If she really wanted to change how people do research, she had to build the tools that would make it easier to do it right. With real-time AI feedback, intuitive design, and built-in best practices, bisque makes it easy to create surveys that get you the answers you actually need.We spoke to Kirsten about how and why surveys are often bad, why she believes the major survey platforms aren't fit for purpose, why she's building her own survey platform "bisque", how she's using Large Language Models to develop a working prototype, and what advice she has for other non-programmers who want to build things with AI.You can find her on:LinkedIn @kirstenleehillTikTok @kirstenleehillSubstack kirstenleehill.substack.com---David’s book, The Well-Grounded Data Analyst is out! ⁠https://www.manning.com/books/the-well-grounded-data-analyst⁠If you want to find out more, we have a whole episode about it: ⁠https://open.spotify.com/episode/5D0iDtQRh3tWiIhokrjz3x?si=AiX6YyRET16lnzXDlvdcfw

In this episode, we spoke to Richard Makara and Niko Korvenlaita who are CEO and CTO of reconfigured.reconfigured is a journal app that makes it incredibly easy to capture and retrieve on-going notes, thoughts & insights. Richard is the CEO and he has led growth and built go-to-market data systems in high-growth scale-ups. Niko is a second time founder and the CTO. He has been building end-to-end machine learning applications since 2014 and has worked with Natural Language Processing since 2017.We spoke to Richard and Niko about the common problems data professionals face, how data people create knowledge faster than they can capture it and what challenges that creates, why reducing the cost of note-taking to zero is so important for data work, how AI can help with the retrieval and structuring of ideas, and how to use AI in a product in a thoughtful and meaningful way.Please enjoy our conversation with the team behind reconfigured!Find out more about reconfigured here: https://reconfigured.ioYou can also find Richard and Niko on LinkedIn.—David’s book, The Well-Grounded Data Analyst is out! ⁠https://www.manning.com/books/the-well-grounded-data-analyst⁠If you want to find out more, we have a whole episode about it: ⁠https://open.spotify.com/episode/5D0iDtQRh3tWiIhokrjz3x?si=AiX6YyRET16lnzXDlvdcfw

In this episode we talked to Simon Willison. Simon is the creator of Datasette, an open source tool for exploring and publishing data. He currently works full-time building open source tools for data journalism, built around Datasette and SQLite.Prior to becoming an independent open source developer, Simon was an engineering director at Eventbrite. Simon joined Eventbrite through their acquisition of Lanyrd, a Y Combinator funded company he co-founded in 2010.He is a co-creator of the Django Web Framework, and has been blogging about web development and programming since 2002 at simonwillison.netWe talked to Simon about his goal of building tools for data journalists, what he's learned about tinkering with, and writing about, AI models for years, his excitement about their code-generating capabilities, how to get the most out of all of these tools, and what generative AI tools have to do with pelicans.You can find Simon at https://simonwillison.netPlease enjoy our conversation with Simon Willison!--David's book, The Well-Grounded Data Analyst is out! ⁠https://www.manning.com/books/the-well-grounded-data-analyst⁠If you want to find out more, we have a whole episode about it: ⁠https://open.spotify.com/episode/5D0iDtQRh3tWiIhokrjz3x?si=AiX6YyRET16lnzXDlvdcfw

Season 4, all about AI, has launched! In the first episode of the new season we talked to Scott Hanselman.Scott is a programmer, teacher, and speaker. He works out of his home office in Portland, Oregon for Microsoft as the Vice President of Developer Community. He works on .NET, Open Source, and the Azure Cloud Developer Experience, but he also blogs about technology, culture, gadgets, inclusion, code, the web, where we're going and where we've been, and has a number of podcasts and a YouTube channel.We talked to Scott about his role at Microsoft and how he still loves to build things. We talked about AI as a brand, the risks of relying too much on tools like ChatGPT, and how developers can use these technologies meaningfully. We also discussed one of our favourite topics on the podcast, dark matter developers, a term we originally learned from a blog post by Scott himself. See episode 4, Getting Data in our first season for even more about this term.Please enjoy our conversation with Scott Hanselman!You can find Scott at https://www.hanselman.com--David's book, The Well-Grounded Data Analyst is out! https://www.manning.com/books/the-well-grounded-data-analystIf you want to find out more, we have a whole episode about it: https://open.spotify.com/episode/5D0iDtQRh3tWiIhokrjz3x?si=AiX6YyRET16lnzXDlvdcfw

In this episode, Shaun interviews David about his new book, The Well-Grounded Data Analyst.We talk about the data skill gap between the classroom and the real world that made David want to write this book, the importance of tackling real-world projects for further learning, and the underlying methodology of the book that helps you learn to solve any data problem.If you listen to the end, we also tease our upcoming Season 4 of the podcast.Get your copy here: https://www.manning.com/books/the-well-grounded-data-analystRead more about David's work here: https://davidasboth.com/

If you're an aspiring analyst and want to test your existing data skills on real-world problems while learning both new skills and a framework you can apply to any problem, David's book Solve Any Data Analysis Problem is available on the Manning website through the Early Access Program and it's out in print later this year. Find it at https://www.manning.com/books/solve-any-data-analysis-problem In this episode, we welcome back a former guest, Andrea Jones-Rooy, Ph.D. Andrea is the founder of Data Thinking, an organization dedicated to promoting worldwide data literacy and public involvement in data science. Previously, she was the Director of Undergraduate Studies and Visiting Associate Professor at the NYU Center for Data Science, where she developed and taught their flagship course, Data Science for Everyone, as well as advanced courses on Natural Language Processing. Dr. Jones-Rooy believes everyone has a role to play in data science, and you (yes, you!) can get involved at DataScienceNeedsYou.com! We spoke to Andrea about how to teach people the scientific method and to deal with uncertainty, the impact of generative AI on teaching these topics, whether these skills should be called "data thinking" instead of "data science", and how you even convince people these are the skills worth learning. Find Andrea at https://datascienceneedsyou.com or on social media platforms as @jonesrooy