Fundamentals Are Gravity
Joe's Nerdy Rants #66 - Weekend reads, podcasts, and other stuff
People ask me whether data engineering is going away, what tech or data stack they should adopt, or who I think the hot vendors are. While I’m usually happy to answer these questions (it depends who’s asking), the answers will always change. Trends in our field change at light speed. The title and work of a data engineer might change, but the data engineering lifecycle will take far longer to evolve. Tech stacks come and go. Hot vendors one minute are auctioned for parts the next minute. I stay on top of the tool and tech space, but I approach it with a mix of curiosity and detachment because titles, tools, and vendors come and go in the blink of an eye. As much as I can, I avoid getting religiously tied to fleeting things.
A couple of months ago, while spending time with my close friend and mentor Bill Inmon, he said three words that stuck with me: “Fundamentals are gravity.” Everything eventually reverts to the fundamentals. He told me there are two types of personas in the tech and data industry - fundamentalists and technologists. Fundamentalists believe in the fundamentals of their craft and approach things from first principles. Technologists attach themselves to specific technologies. Most people fall into one of these camps, with most people (in my experience at least) gravitating toward technologists. Sometimes, a person can be both, but that’s rare. I think of myself as a fundamentalist who stays on top of the tech/data/AI landscape but doesn’t have a hard affiliation with a particular technology.
When I think of fundamentals, a big one that stands out is how Jeff Bezos describes things that won’t change.
“I very frequently get the question: 'What's going to change in the next 10 years?' And that is a very interesting question; it's a very common one. I almost never get the question: 'What's not going to change in the next 10 years?' And I submit to you that that second question is actually the more important of the two -- because you can build a business strategy around the things that are stable in time. ... [I]n our retail business, we know that customers want low prices, and I know that's going to be true 10 years from now. They want fast delivery; they want vast selection. It's impossible to imagine a future 10 years from now where a customer comes up and says, 'Jeff I love Amazon; I just wish the prices were a little higher,' [or] 'I love Amazon; I just wish you'd deliver a little more slowly.' Impossible. And so the effort we put into those things, spinning those things up, we know the energy we put into it today will still be paying off dividends for our customers 10 years from now. When you have something that you know is true, even over the long term, you can afford to put a lot of energy into it.” - Jeff Bezos
When thinking in fundamentals, you must consider the relative rates of change among things in your field. Some things move fast (noise), and others are almost ground truths (fundamentals). Inevitably, things revert to ground truth. In data, Bill says that he’s always been driven by delivering believable data that adds business value. Hard to argue with that. When you think of this through the lens of things that won’t change, it’s difficult to imagine a scenario where people demand data that’s late, hard to consume, and not believable and fosters poor decision-making. Or training an AI model on data that’s very biased and full of inaccuracies.
I try to put my energy into understanding the things that won’t change as much. Most of my time is spent studying technologies and practices at an atomic level. It’s an insane amount of work and passion that I don’t recommend to most people. But this makes life a lot easier when evaluating the answers to the types of questions at the start of this article. In most cases, you realize things matter far less than you think and that most things don’t require an answer. Sometimes, “I don’t know” or “it doesn’t matter” are good enough. The hot technology or research paper of today quickly becomes yesterday’s news. Developing a filter for noise and bullshit is one of the best investments you can make if you want longevity in this field. As Bill says, fundamentals are gravity. And in the end, gravity wins.
Next week, I’ll be publishing some new articles, podcasts, and draft sections of the book.
Have a wonderful weekend,
Joe
Cool Weekend Reads & Listens
Tech, Data, and AI
My Approach to Building Large Technical Projects – Mitchell Hashimoto
To avoid being replaced by LLMs, do what they can't | sean goedecke
AI And The Limits Of Language | NOEMA (2022)
Where will the AI Horde strike next? AI video, social media, and Hollywood
A year of uv: pros, cons, and should you migrate
OpenAI Uncovers Evidence of A.I.-Powered Chinese Surveillance Tool - The New York Times
Biz & Culture
Venture debt hits all-time high as startups diverge from VC expectations
The AI Moment for College Students - by Jacob Miller
Debt Has Always Been the Ruin of Great Powers. Is the U.S. Next? - WSJ
Podcast
Freestyle Friday - The Great Pacific Garbage Patch of AI Data Slop (Spotify)
Eric Broda - AI Agent Ecoysystems, the Death of Consulting, and More (Spotify, YouTube)
Hugo Bowne-Anderson - Exploring the Future of AI and Automation (Spotify, YouTube)
Ghalib Suleiman & Kevin Connolly - Data Team "What Ifs" (Spotify, YouTube)
Anne-Claire Baschet & Yoann Benoit - Unifying AI and Product Development - (Spotify, YouTube)
David Jayatillake - Semantic Layers, Proving Value in Data Work, and More - (Spotify, YouTube)
Freestyle Fridays - Old School vs New School Data Modeling (Spotify)
Evan Wimpey - On Being a Data Comedian, a Bayesian, and Other Priors (Spotify)
Data Day Texas Recap w/ Tony Baer, Matt Housley, and Juan Sequeda (Spotify)
Freestyle Fridays - Unhinged Rants w/ Carly Taylor (Spotify)
Remco Broekmans - Data Modeling, Data Vault, and More (Spotify)
Freestyle Fridays - Bridge Skills w/ Eevamaija Virtanen (Spotify)
Chip Huyen - AI Engineering, Agents, and More (Spotify)
Jamie Davidson - Modern Data Modeling (Spotify)
Way more episodes over at the Joe Reis Show, available on Spotify, Apple Podcasts, or wherever you get your podcasts. It will soon be available on YouTube.
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Thanks for sharing the links!