On Being a Generalist in a Specialist's World
I’ve written production code in Python, JavaScript, Go, and C++. I’ve done frontend, backend, infra, and now AI. Every few years, someone asks: “But what’s your thing?”
I never have a good answer.
For a long time, this felt like a weakness. Like I was somehow failing at the career game by not picking a lane. But I’ve come to see it differently.
The Pressure to Specialize
Career advice is clear: be the X person. The React expert. The Kubernetes guru. The machine learning specialist. Pick something, go deep, become the person everyone thinks of when that topic comes up.
LinkedIn rewards it. Your title becomes your identity. “Senior Backend Engineer” tells people exactly what you do. “Senior Software Engineer” tells them nothing.
Job descriptions want “5+ years in [specific thing].” Never mind that a lot of these things haven’t even been around for 5 years. The industry rewards depth—or at least the appearance of it.
I’ve never had 5+ years in one thing. Not because I’m flaky, but because I keep getting pulled into new problems. Every time I get comfortable, something interesting appears in a different domain.
The Path That Led Here
Here’s my actual career trajectory:
Riverbed: Systems programming, C++, network protocols. Deep in the weeds of packet inspection and performance optimization.
Cisco: Security, cloud infrastructure, Python. Completely different domain, different language, different problems.
PayPal: Payments, distributed systems, scale. Now I’m thinking about transactions, consistency, and what happens when millions of people want their money at the same time.
Robynn AI: LLMs, agent architectures, product. Suddenly I’m building AI systems, thinking about prompt engineering, orchestrating autonomous agents.
Each jump felt like starting over. Each time, I wondered if I was making a mistake by not staying to become the expert.
In retrospect, nothing was wasted. The systems thinking from Riverbed helps me debug AI agent behavior. The security mindset from Cisco makes me paranoid about prompt injection. The scale lessons from PayPal inform how we architect our infrastructure at Robynn.
What Generalists Are Actually Good At
Generalists have real advantages that specialists don’t:
Translation. I can talk to the ML team AND the infra team because I’ve been both. I speak both languages. When those teams are talking past each other—which happens constantly—I can bridge the gap.
Problem decomposition. When you’ve seen problems in multiple domains, you start to recognize patterns. You know which parts are actually hard and which parts just seem hard because you haven’t seen them before. You can break complex problems into subproblems more effectively.
Rapid prototyping. I can build a full-stack proof of concept without waiting on anyone. Need a quick ML model, an API, a frontend, and a deployment pipeline? I can do all of that—maybe not beautifully, but fast enough to learn if the idea is worth pursuing.
Debugging. The hardest bugs live at the intersection of systems. When the frontend, backend, and database are all behaving correctly in isolation but something’s broken in production, you need someone who understands all three. Generalists find those bugs.
The Costs (Let’s Be Honest)
I won’t pretend there’s no downside.
I’ll never be the person who wrote the book on [X]. When you read about the world’s leading experts on some technology, I won’t be on that list. That door is closed.
In deep technical interviews, specialists will always have deeper domain knowledge. They’ll know the niche edge cases, the obscure configuration options, the historical context for why things work the way they do. If the interview is “how well do you know [specific technology],” I’ll lose.
And imposter syndrome hits different when everyone around you seems to have “a thing.” At conferences, people introduce themselves by their specialty. “I work on compilers.” “I’m a security researcher.” “I focus on distributed consensus.” What do I say? “I… work on things”?
Where Generalists Thrive
That said, there are environments where generalists have a massive advantage:
Early-stage startups. When you’re 10 people, you can’t afford specialists. You need people who can do whatever needs doing this week. Someone who can write the backend, set up the CI pipeline, debug the mobile app, and talk to customers. That’s the generalist’s home turf.
Technical leadership. To lead an engineering organization, you need to understand all the pieces. The CTO who only understands backend will make bad decisions about frontend architecture. The VP who only knows infrastructure will underestimate product complexity. Breadth is a prerequisite for leadership.
New domains. In AI, crypto, or any emerging field—no one has 10 years of experience because the field didn’t exist 10 years ago. Generalists have a pattern for learning new domains quickly. That’s valuable when the domain itself is new.
Platform and infrastructure. When everything connects to everything, you need someone who understands everything. Platform engineers live at the intersection of frontend, backend, databases, DevOps, and security. Specialists struggle here.
The Reframe That Helped Me
I used to think I was a “jack of all trades, master of none.” The full saying is actually “jack of all trades, master of none, but oftentimes better than a master of one.” That’s closer to how I think about it now.
But even that framing is wrong. I’m not a generalist because I failed to specialize. I’m a systems thinker. My specialty is understanding how pieces fit together.
The T-shape model helped me make peace with my career: broad knowledge across many areas, with depth in a few. For me, those depth areas are distributed systems, AI agents, and web design. Not because I chose them strategically, but because I kept returning to them as I solved real problems.
Depth comes naturally when you’re solving real problems. You don’t have to force it. The generalist’s breadth gives you context; the depth emerges from repeated application.
If you’re a generalist feeling like a fraud, consider this: someone needs to build the bridges between specialties. Someone needs to see the whole system. Someone needs to translate between the experts who can’t understand each other.
That’s not a consolation prize. That’s a skill. And in a world that’s increasingly complex and interconnected, it might be the most valuable skill of all.
What’s your experience with the generalist/specialist tradeoff? I’d love to hear from others who’ve grappled with this. architgupta941@gmail.com or find me on X.
