Legendary Investor Naval: In the AI Era, Are Traditional Software Engineers No Longer Valuable?

Is Traditional Software Engineering Dead?

"Does this mean traditional software engineering is dead? Absolutely not. Software engineers—even those who aren’t necessarily responsible for tuning or training AI models—are now some of the most leverageable people in the world. Of course, those who train and tune models have even higher leverage because they are building the tools that software engineers use.

But software engineers still have two major advantages over you. First, they think in code, so they truly understand how the underlying systems work. And all abstractions are inherently flawed. Therefore, when computers are programming for you—when Claude Code or similar programs are coding for you—they will inevitably make mistakes.

They will produce bugs, and their architecture won’t be perfect. So it won’t be entirely normal. People who understand the underlying principles can patch these vulnerabilities as they appear.

So, if you want to build a well-architected application, or even just want to be able to accurately specify a well-architected application, if you want it to run at high performance, perform at its best, and catch bugs early, you need a background in software engineering.

Traditional software engineers will be better equipped to leverage these tools. Moreover, many problems in software engineering today are still beyond what AI programs can handle. The simplest way to understand this is that these problems are outside their training data distribution.

For example, if they need to perform binary sorting or reverse a linked list, they’ve seen countless examples and are very good at it. But when you go beyond their domain—when you need to write extremely high-performance code, or code that runs on novel or entirely new architectures, or when you’re truly creating something new or solving new problems—you still need to dive in and write code yourself.

At least until enough examples are accumulated to train new models, or until these models can perform higher-level abstract reasoning and tackle difficult problems independently…

And remember: mediocrity has no market demand. Nobody wants a mediocre application unless it fills a niche that even better applications haven’t covered. Better applications will almost always capture 100% of the market share. There might be a small segment of users who prefer the second-best app because it excels in a niche feature or is cheaper, and so on.

But overall, people only want the best. So the bad news is, being second or third is pointless—like Alec Baldwin’s famous line in the movie Glengarry Glen Ross: ‘First place gets a Cadillac Eldorado, second place gets a set of steak knives, and third place gets a pink slip.’

In these winner-takes-all markets, this is absolutely true. The bad news is: if you want to win, you have to be the best at something.

However, the things you can be the best at are endless. You can always find a niche that fits you perfectly and become a leader in that field. This confirms a tweet I once posted: ‘Strive to be the top in your field. Keep redefining what you do until that becomes a reality.’

I believe this still applies in the age of AI."