Stay ConnectedI’m Joe Reis, co-author of Fundamentals of Data Engineering, creator of Mixed Model Arts, international speaker, and long-time observer of the tech industry’s favorite recurring mistakes.
Weekly broadcasts from somewhere on the road. Expect raw solo rants and long-form conversations with the engineers and leaders actually building things. I dive into data, AI, architecture, and career survival.
This podcast is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
Copyright: © Joe Reis
My semi-regular co-host and bestie Carly Taylor joins me once again. This time we chat about the true cost of replacing engineers with AI. We explore the implications of mass layoffs, the importance of company culture, and the potential for burnout among tech workers.
It seems like quite a few data practitioners I talk with are miserable. Forced to deliver things ever faster, there's not enough time to THINK. Instead, the pressure is to deliver "stuff" in two-week sprints. In this episode, I rant about why not everything needs to be a sprint, and why we need to treat Deep Work versus Delivery Work differently.
John Thompson joins me to chat about his upcoming book, The Path to AGI, his book writing process, and much more.
John Thompson LinkedIn: https://www.linkedin.com/in/johnkthompson/
Things aren't great in the world of data practitioners. Lots of technical debt and lack of pride in one's craft. The pressure to do more with less only compounds this problem. And AI will make it far worse.
If you think the amount of poorly made data architecture and models is bad now, I think we're in for another level very soon. With AI CoPilot on the rise, right as data skills and knowledge decline, I'm increasingly worried we'll offload our critical thinking and skills to AI. The outcome will be an ever expanding Great Pacific Garbage Patch of AI Data Slop.
Join Eric Broda and me for a fascinating discussion on the cutting edge of AI! We chat about the rapidly evolving world of AI agent ecosystems, exploring their potential to transform industries and reshape the future of work.Eric shares his hard won perspective on the challenges and opportunities facing consultancies in the age of AI, and why he believes AI agents could signal a significant shift in the consulting landscape. We also discuss the ins and outs of running a successful consultancy in today's dynamic market.Key topics covered:-The rise of AI agent ecosystems and their implications-How AI is disrupting the traditional consulting model-The future of consultancies in an AI-driven world-Insights into building and managing a successful consultancy-Whether you're an AI enthusiast, a consultant, or simply curious about the future of agents, this conversation with Eric Broda offers valuable insights and thought-provoking perspectives.#AIAgents#ArtificialIntelligence#Consulting#FutureOfWork#AI#Business#Innovation#Technology
Hugo Bowne-Anderson and I chat about the future of AI and automation, agents, and much more.
Ghalib Suleiman, Kevin Connolly, and I have all run data teams. In this episode, we chat about a bunch of data team "what ifs" - running a data team, hiring and firing, and executive commitments
With AI becoming engrained in nearly every product, there's still a BIG problem - AI and product teams have trouble working together. Whether it's different communication and working styles, or lack of a common language, AI teams stall because they can't align with Product.
Anne-Claire Baschet & Yoann Benoit join me to chat about unifying AI and Product Development.
Article: AI & Product: Two Development Cycles to Unify
https://craftingdataproducts.substack.com/p/ai-and-product-two-development-cycles
David Jayatillake joins me to chat about semantic layers, assessing value in data work, AI, and much more.
David's LinkedIn: https://www.linkedin.com/in/david-jayatillake/
In data modeling - and pretty much anything else - do you choose "old school" or "new school"? In other words, do you move slow and methodically or fast?
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