Since graduating last June, one question has kept returning to me: how do I build a long term career in an industry that keeps reinventing itself?
The longer I sit with that question, the more I feel how difficult it is to think clearly about work in tech. The discourse is often toxic and reactive. Even as someone who is naturally optimistic, I still find myself wondering whether I chose the right path.
That is why I was surprised to find myself thinking about all of this through the movie Moneyball. A random clip led me back to a movie I have seen countless times, then to a video essay that helped me see the part of the story I had been missing.
Moneyball is based on a true story about the Oakland A’s during the 2002 MLB season. At a high level, the team faced a simple problem: they did not have enough money to build a roster the way richer teams could.
Note
In baseball, established star players usually cost much more money. That means richer teams can often afford better talent, which makes a limited budget a real competitive disadvantage.
So instead of trying to outspend teams like the New York Yankees, they leveraged data and analytics to identify overlooked players and built an advantage from that constraint.
Evolution
Once the Oakland A’s showed that this approach could work, the rest of the teams in the MLB adapted. Teams built analytics departments, invested in better data, and developed more algorithmic ways of evaluating talent. For a while, it was easy to imagine that traditional scouting would become less important, or even obsolete. If teams had enough numbers and strong enough models, what role would be left for the human scouts?
But the deeper problem of scouting never changed. Whether in the draft, free agency, or trades, teams are still trying to answer the same basic question: what will this player become? The methodology has evolved over time, from gut feel, to analytics, to a blend of both, but the task itself remains fundamentally uncertain. Better tools can’t guarantee the future.
That’s why there are more scouts now than ever before. Teams still need people who can gather information, interpret edge cases, and make judgments where the data remains incomplete. The real edge is knowing how to combine those numbers with experience, context, and player development to make better bets on an uncertain future.
Parallels
When watching the video essay, my mind immediately thought of how the situation with scouts sounds exactly like how knowledge work is being transformed today by AI. The tools have improved dramatically, and code can be produced faster than ever before. On the surface, it makes it easy to assume that the underlying work is becoming less valuable.
But I do not think the core problems of knowledge work have changed. In the same way baseball never solved the problem of identifying talent, knowledge work has not solved the problem of creating something genuinely useful for others. Building reliable systems, communicating clearly, thinking carefully about security, and making good decisions under uncertainty are not new problems, and they have not disappeared. If anything, faster output has amplified them. We still see bad products, security vulnerabilities, bugs, and slop everywhere.
To answer the question I started with, I think the best response is not a fixed plan but a way of thinking. The advice that I find most compelling isn’t step by step. It’s always advice that pushes you to think more deeply about what matters, what is within our control, and how we want to approach our life. I feel the same way about my career. I do not have a concept of a “dream” job or any grand career outcome goals. What feels more durable is staying adaptable, deepening my understanding of how systems work, and using the tools available to make those systems more useful for others. The form of this work will no doubt change, but how I approach this will always be the same.
Interesting Ideas
- Draymond Green reflects on Warriors’ 2025-26 season after play-in loss to Suns: I initially watched this because I was curious about what he’d say after he got ejected in that same game. After watching, I do respect how Draymond reflected on his year: he was healthy, took care of his family, and had immense gratitude for the Warriors staff. I also liked how he framed his motivation for winning which is to provide certainty and help those who help him (e.g. coaching, strength + conditioning, nutrition, etc.). It really does take a village and I liked the perspective he shared.
- I Worked a $1 vs $1000 Restaurant: This video reminds me of the quote “Don’t judge a man until you have walked a mile in his shoes”. As someone who hasn’t worked in the service industry before, this video was quite eye-opening and especially after doing my cooking class, I have a huge respect for those in the service industry.
- Did Canada’s Mark Carney just ‘manipulate’ his way to a Liberal majority?: I mainly stay up to date with the news through Andrew Chang’s segments. I admire how he always presents a holistic view no matter the topic and it’s very refreshing to see. Love this content from the CBC!