Career Strategy for Young Software Engineers
To prevent AI displacement until 2030
What you’re about to read is pragmatic career advice for navigating your path as a young software developer in the age of AI and protecting yourself against AI displacement.
Most career advice for young developers today is lazy or non-actionable: “Learn AI, or you’ll be replaced.” “Master prompt engineering.” “Coding will be fully automated soon.”
The real question is: Who are you choosing to compete against?
In my view, there are three exciting career paths you can take today that combine high reward potential, fast career velocity, and long-term protection against AI displacement:
Work in an AI Lab
Become an AI-native builder
Join a good crypto company
Depending on who you are, your skills, and your personality, one of these will be a better fit. Below, I’ll describe each option and explain why I believe option 3 is the best choice for most talented young developers.
1. Work in an AI Lab
(Anthropic, OpenAI, DeepMind, Mistral, etc.)
This is an extremely exciting and potentially high-reward path. The rate of progress and shipping velocity at some of these companies is astonishing. If you land on the right team, you will learn from incredibly talented people and work on the cutting-edge of a technology that will change everything.
Compensation is strong. These companies raise capital at massive valuations and do so quickly, so there is potential upside in their equity if you join early. Geographically, most of the interesting opportunities are concentrated in San Francisco, with some exceptions, such as DeepMind’s offices in London and Zurich, and outliers like Mistral.
The competition is brutal. If you are not exceptional and don’t have a very strong background in math, data, or theoretical computer science, it will be extremely hard to get in. In practice, this often means top-tier undergraduate programs, master’s degrees, or PhDs in CS, ML, or hard sciences like physics, or some other form of extraordinary early achievement.
There is also an ironic long-term risk: people inside these labs often joke that they may be among the first to be replaced. The “self-improving AI engineer” is one of the holy grails on the path to AGI.
To remain relevant long-term, you need to move toward higher-value work. That, too, is extremely competitive.
2. Become an AI-Native Builder
(working on most SaaS startups, becoming an indie builder)
AI is leverage on human intelligence. If you can use these tools to their full potential, you can become a 10x or even 100x engineer.
If you stay on the cutting edge of AI tooling, your output can vastly exceed what’s expected from a junior developer, which makes you highly attractive in the market.
Right now, junior developers face a tough landscape. Getting good first experiences is harder than it used to be. You will likely need to rely on indie projects, open source, and self-directed work to stand out.
There is also long-term uncertainty. As AI gets more capable, building standard software applications will become increasingly automated. You may find yourself competing not only with other engineers but with designers, product managers, and AIs themselves. To thrive, you will likely need to become a generalist, with good taste and high agency.
If more senior engineers in your company also become AI-native, their experience and soft skills may compound their advantage, putting you at risk of becoming obsolete.
For entrepreneurial types, there is another attractive path for AI-native engineers. Being an AI-native builder makes the “one-person software company” a real possibility. If you are resilient, comfortable with uncertainty, and can stomach the loneliness and emotional rollercoaster of building alone, this can be a powerful direction.
3. Join a Good Crypto Company as an Engineer
Mission-critical, security-sensitive, and regulated software tends to resist full automation. Think about nuclear systems, defense, or aviation. Crypto belongs in this category, but with one major difference: it is the only one that is also a fast-growing industry and allows for fast career progression.
You can become a world expert very quickly. The field is young, under-documented, and full of unsolved problems. This creates steep learning curves but also rapid differentiation, which is not the case in other mission-critical software, such as aviation systems, where career hierarchies and progression are more conventional.
Unfortunately, crypto is an industry with a very high noise-to-signal ratio, so choosing wisely which company to work for is incredibly important. Look for companies solving real problems and generating real revenue that can sustain the industry’s inherent volatility, and filter out pure hype and token valuation promises.
AI and crypto are converging. Intelligent agents, autonomous wallets, onchain identity, risk modeling, and automated market infrastructure are all emerging at the intersection of these two worlds. An exciting latent career space is opening at the intersection of these two fields, so becoming an AI-native crypto engineer working on hard problems can potentially cover your AI-displacement risks while offering high-reward and fast progression opportunities.
In regulated, security-sensitive verticals, the risks of full displacement are lower, so you are not directly competing with AI. You are mostly competing with other engineers. That distinction matters a lot.
Choosing Your Competition
One useful way to think about these paths is to ask: Who am I competing against?
In AI research labs, you are competing with the best AI researchers in the world.
As an AI-native builder, you are increasingly competing with AI itself.
In crypto, you are mostly competing with other engineers.
Each of these is a valid choice. But they are very different games.
If you are exceptionally strong in math and computer science and thrive in elite academic environments, AI labs might be your place.
If you are highly independent, product-minded, and enjoy uncertainty, becoming an AI-native builder could be powerful.
But for most talented young engineers who want fast career growth and long-term defensibility against AI displacement, crypto remains one of the most asymmetric bets available today.
Talent matters. Effort matters. But the game you choose matters more than both.
Choose your competition wisely.
P.S. I run Range, a crypto startup, so I’m biased. But I still think this reasoning holds even if you strip away my personal incentives. Looking to hear what others think.