Hi Tip-Sheeters,

Let me be one of the first to tell you 🎉 Happy New Year! 🎆

I hope you're excited about 2026 and the new skills in data science and tech that you'll be picking up. This week, I was able to put my finger on a concept that had been bouncing around in my head for a while: building a career that benefits from rapid changes.

An antifragile career

I enjoy reading the Incerto Series of books from Nassim Nicholas Taleb. He has a writing style that is challenging and entertaining, and mixes a lot of probability in, which is in my swimlane as a data scientist. One of his most sticky ideas is the concept of Antifragility, which he defines as the quality that allows something to benefit from change and turmoil.

He means it as a step beyond resiliency, as explained on the publisher website for his book Antifragile: "The antifragile is beyond the resilient or robust. The resilient resists shocks and stays the same; the antifragile gets better and better."

Applying this to your career in tech and data science: what would it look like if you didn't just "survive" rapid turmoil in your industry or career field, but benefited from it? The current AI impact on the data and IT industry is a great example, but not the first or last.

The Brazil Nut effect

The mental image I always have when thinking about this topic is that our career is a marble in a jar that is being rapidly shaken. And when that shaking happens, our career rises up and ends up floating at the top of the jar.

This week I found a good video that describes this effect in Physics as the "Brazil Nut effect" (because Brazil nuts end up at the top of a can of mixed nuts).

According to this video, there are complicated forces at work that cause this:

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What is the quality you need?

So what is the secret sauce that makes your career benefit from turmoil? I can think of a few qualities that could have this impact -- some that you can control and others you can't.

But the one that is most interesting to me is the refined ability to learn quickly and strategically. This goes beyond being a "quick learner" to developing tools, frameworks, and systems to repeatedly grow your skills through each phase of change and turmoil so that your career steadily rises over time.

Here's where antifragile is a better term than resilient for what I'm trying to communicate: I don't only mean that you make it through and maintain your same level of stability. I mean that through each of these convulsions that economies and industries go through, it benefits you, especially in relation to how you have previously done.

Developing that ability is something that fascinates me, and a lot of what I write in this newsletter is in pursuit of that goal.

Some interesting reads to start the year

Here are a few interesting articles and videos I've come across recently:

​Top 5 Data Science Career Lessons in 2025 (Andres Vourakis) - Quick tips from Andres, who has a really good newsletter. Five things 2025 taught him about his career. Also check out his AI Data Scientist Handbook repo with resources.

​Soccer Analytics 2025 Review (Jan Van Haaren) - Sports analytics is a lot of fun and a great way to implement data science techniques. This list includes a lot of research papers for the more academic reader out there, along with various articles.

​The economics of technical speaking (Gregor Hohpe) - Gregor is an active speaker at conferences I have attended. He gives an interesting discussion of the financial side of speaking at conferences.

Personal brand is something that can sound strange or inauthentic to some people, or flash over substance. But being intentional about what skills you bring to the table is worthwhile. Here are a couple of resources on the topic: an article in English and a short video en español.

​Meta Data Scientist Yan LeCun's career advice for students going into AI (Business Insider) - LeCun's advice includes studying things with a "long shelf life" and focusing on the fundamentals.

Keep coding and Happy New Year!

Ryan Day

👉 https://tips.handsonapibook.com/ -- no spam, just a short email every week.