When’s the last time you hired a typist?
In the 1950s, typing was a profession. Companies employed entire pools of specialists who trained for years to hit 80+ words per minute. Then word processors happened—and typists didn’t disappear because typing stopped mattering. They disappeared because everyone learned to type.
The skill became table stakes. The same thing is happening to programming.
AI writes most of our code now
At Hypha, AI generates 80–99% of our code. Not boilerplate—actual features, actual systems. Our team spends less time writing code and more time reviewing it, directing it, shaping it.
Writing code is no longer the job. It's becoming one skill among many.
Fluency
What "software engineer" used to mean
For most of my career, the job was clear:
- Know a language or framework deeply
- Translate requirements into code
- Debug when things break
- Optimize for performance
- Ship features
Master those, and you had a career. I got my first break when React was new—I’d built side projects with it, and all of a sudden React got me my first (and second) job.
Back then, being "cracked at React" was a job.
What the job is becoming
Technical fluency hasn’t disappeared. It’s just one skill among ten:
Problem definition. What to build and why. AI can’t sit in a customer call and hear frustration. Can’t synthesize five conflicting requests into one insight.
Customer discovery. Talking to users. Asking good questions. Extracting signal from noise.
Systems thinking. How pieces connect. Second-order effects. AI solves what’s in front of it. Humans see the whole board.
Design sensibility. Taste. Knowing when something feels right. AI generates ten options—someone has to know which one is good.
Clear communication. Specs. Prompts. Decisions. When you collaborate with systems that interpret words literally, precision matters.
Agent orchestration. Directing AI effectively. When to give autonomy. When to intervene. Management, except your reports run on GPUs.
Quality judgment. AI produces fast. Knowing whether output is good—that’s the bottleneck.
Technical fluency. Reading code. Debugging. Understanding tradeoffs. This used to be the entire job. Now it’s one of ten.
Prioritization. When building gets faster, deciding what to build becomes the constraint.
Domain expertise. Deep knowledge of your problem space. AI doesn't know what matters to your users.
What we're hiring for
Our interview process doesn't include leetcode. Instead, we give candidates a project—one that's intentionally impossible to finish in the time given.
That's the point. We're testing prioritization: what do you build first? What do you cut? We're testing AI fluency: can you leverage tools to move faster than should be possible? And we're testing product sense: given an open-ended problem, what do you choose to build?
Then we dig in. Walk us through your code. Why this architecture? What tradeoffs did you make? What would break first at scale? What would you do with another week?
The technical questions aren't gotchas—they're checking that you understood what the AI wrote. That you could debug it. That you made deliberate choices rather than accepting the first suggestion.
We're hiring for the ten skills listed above. The interview is designed to surface them.
If that sounds like you, check out our open roles.
The identity problem
I don’t know what to call this new role. We’re using “Member of Technical Staff” at Hypha—a placeholder. “Engineer” implies code is the point. “Product Manager” implies you’re not technical. Neither fits.
But labels aren’t the real issue. The deeper question is identity.
A lot of engineers—myself included—built careers around technical proficiency. Spent years getting good at something. That skill still matters, but it’s no longer the differentiator.
The typists who adapted became knowledge workers with broader scope. They didn’t lose their typing skills—they added new ones on top. Their careers expanded rather than contracted.
I think that’s the path forward. The people who thrive won’t be the ones who code fastest. They’ll be the ones who know what’s worth building.
But I won’t pretend there’s no grief in this. Watching a skill you spent years developing become commoditized—that’s humbling. It forces a harder question: what are you actually good at, underneath the technical proficiency?
Engineers who built their identity around React or Python or Kubernetes face the same question typists faced sixty years ago.
The skill still matters. It’s just not the job anymore.
If you’re navigating this shift too, I’d like to hear how you’re thinking about it. Reach out.