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.
Programming is no longer a job. It's a skill.
Two years from now, five years from now—the timeline doesn't matter as much as the direction. Writing code is not going to be a job. It's going to be a skill embedded in dozens of other jobs, the way typing is today.
When typing became universal, it didn't create a world of professional typists. It created a world where typing was assumed—and the people who refused to learn got left behind. Programming is headed to the same place. Not because everyone will become a software engineer. But because everyone will use code the way they use a keyboard.
Boris Cherny, who leads Claude Code at Anthropic, put it this way: before the printing press, scribes were about 1% of the population. The printing press made 70% of the world literate within 200 years. AI coding tools are doing the same thing for programming—but in years, not centuries.
The numbers already reflect this. 73% of engineering teams use AI coding tools daily in 2026, up from 18% in 2024. MIT Technology Review named generative coding one of its 10 Breakthrough Technologies of 2026. "Vibe coding" was Collins Dictionary's Word of the Year in 2025. Replit's AI Agent has produced over 2 million apps in six months—without users writing a single line of code.
This isn't a prediction. It's already happening.
Engineering teams using AI coding tools daily
Source: Stack Overflow Developer Survey
What the job is becoming
For most of my career, the software engineering job was clear: know a language deeply, translate requirements into code, debug when things break, ship features. I got my first break when React was new—I'd built side projects with it, and being "cracked at React" was a job.
That job still exists in name. But at Hypha, AI now generates 80–99% of our code. Actual features, actual systems. Our team spends less time writing code and more time reviewing it, directing it, shaping it.
Fluency
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.
Everyone writes code now
At Hypha, we're not just asking more of our engineers. We're watching code spread across the entire organization.
Our designers write code. Not because we made them learn React. Because Claude Code lets them work directly in our actual codebase—faster than they could in Figma. They make real changes to see what they look like in real time: tweaking a button component, adjusting spacing, iterating on color. They build prototypes with mock data—"here's what a Hypha bar chart should look like"—getting the full benefit of our component library and agentic context on our codebase. And our website is just a Next.js app—our designers commit directly to it, their changes go through PR review like any other code. They're literally coding.
Our PMs write code. They use Claude to rapidly prototype ideas and build proof-of-concepts with mocked data. The goal is communication—when a PM can show a working rough version instead of describing one in a doc, the conversation with engineering is completely different. They also rubber duck with Claude instead of pulling an engineer off their work, asking questions about the codebase, understanding how things connect, finding where the limitations are. Their PRDs are dramatically better because they can see what they're specifying before they specify it.
Our go-to-market team writes code. They use Claude to build customer decks, investor presentations, and internal tools. Six months ago, these would have been a ticket to engineering or a request to design. Now they just build them.
None of these people would call themselves software engineers. They're designers, PMs, and marketers who happen to use code as one tool among many. Just like nobody calls themselves a "typist" anymore—they're all professionals who happen to type.
Same skill, different focus
Everyone is writing code, but they're not all doing the same thing with it. The skill is universal. The application is specialized.
Engineers focus on what they've always focused on—but at a higher level. Scale. Edge cases. Reliability. Observability. Security. Systems architecture. The code itself is increasingly AI-generated, but the judgment about what that code needs to do, how it needs to behave under load, how it fails gracefully—that's engineering. The job isn't writing code. It's ensuring the system works.
Designers focus on what code looks and feels like. They prototype in the real medium. They iterate on interactions, spacing, motion—working directly in the codebase instead of an abstraction layer removed from it. Their output is a working starting point, ready for an engineer to harden.
PMs focus on what's worth building. They prototype to validate. They build to communicate. They use code to rapidly test assumptions, to iterate on ideas in hours instead of sprints. The code is a thinking tool.
Go-to-market teams focus on what moves the business. Custom presentations, internal dashboards, workflow automations. Code as leverage for their actual job.
The skill is the same. The intent is different. And that's exactly how typing works today—an accountant and a novelist both type, but they're doing fundamentally different things.
The lines are already blurred
This isn't just us. Anthropic's own product lawyer built an AI bot with no coding background. Non-technical Y Combinator founders are building functional prototypes with vibe coding tools. LinkedIn launched a "Full-Stack Builder" program that trains employees across all roles—not just engineering—to build with code.
Satya Nadella said it directly: "Now anyone can be a software developer." 30% of Microsoft's code is AI-written. At Google, it's over 30%. At Anthropic, it's 70–90%.
Jensen Huang told people to stop learning to code in the traditional sense. Focus on domain expertise—biology, education, operations—and let AI handle the implementation. Dario Amodei, CEO of Anthropic, said some of his engineering leads don't write any code anymore.
The direction is unmistakable. The specialized skill is becoming ambient infrastructure.
Share of code that is AI-generated
What this means for you
If you're an engineer: your value isn't your ability to write code. It's your ability to think in systems. To understand failure modes, to architect for scale, to make judgment calls that AI can't. The engineers who thrive won't be the fastest coders. They'll be the ones who understand what's worth building—and how to build it right.
If you're a designer: code is your new medium, an extension of design thinking. You can now prototype at the speed of thought, in the actual material your work ships in. The designers who thrive will be the ones who stop handing off static mockups and start building.
If you're a PM: code is your thinking tool. Build rough versions. Understand constraints firsthand. Write better specs because you've already felt where things break. The PMs who thrive will be the ones who show, not tell.
If you're in any other role: look at the repetitive, manual parts of your job. The spreadsheet gymnastics. The ticket-and-wait workflow. The things you've always wished you could just build. You can now. The people who thrive will be the ones who reach for code as naturally as they reach for a keyboard.
The typists who adapted in the 1960s became knowledge workers with broader scope. They didn't lose their typing skills—they added new ones on top. Their careers expanded.
The same opportunity is here now. Programming isn't disappearing. It's dissolving into everything. Your value—as an engineer, designer, PM, or anything else—hinges on whether you're willing to reinvent how you work.
If you're navigating this shift too, I'd like to hear how you're thinking about it. Reach out.