Coding is Dead

Introduction

Hey guys, so I’m about to say something that’s gonna make a lot of people really mad. Ready?

Coding is dead.

Not “dying.” Not “changing.” Dead. As in, the golden age of hand crafting code line by line is over, and most people haven’t figured it out yet.

I know what you’re thinking. “But wait, there are still millions of programming jobs! Companies are hiring developers every day!” Yeah, and there were still people making horse-drawn carriages in 1920. Doesn’t mean the automotive industry wasn’t about to steamroll them.

I’ve been watching this transition happen in real time, and honestly? It’s both fascinating and terrifying. Let me break down what’s actually happening and why most programmers are completely unprepared for what’s coming.

The Writing Was on the Wall

Look, I’ve been in this industry long enough to see the patterns. And the pattern is clear: every layer of abstraction that gets added to programming makes the previous layer obsolete.

Remember when you had to manually manage memory? Then garbage collection came along and suddenly 90% of C programmers became “legacy maintenance engineers.”

Remember when you had to write your own HTTP handlers? Then frameworks like Rails and Express came along and suddenly you didn’t need to understand TCP/IP to build web apps.

Remember when you had to design your own databases? Then ORMs came along and suddenly SQL became optional.

Each time, the industry said “this will make programmers more productive!” And it did. But it also made most of the previous skill set irrelevant.

The AI Revolution Isn’t Coming—It’s Here

While everyone was arguing about whether AI would replace programmers, it already started happening. Let me give you some real numbers that nobody talks about:

GitHub Copilot Stats (That Nobody Mentions)

• 40% of code in popular repositories is now AI generated¹
• 73% of developers using Copilot report writing significantly less code²
• 55% faster task completion for routine programming tasks³

But here’s the kicker: that’s with the current, primitive AI. GPT-4 is basically a sophisticated autocomplete compared to what’s coming.

What I’m Seeing in Practice

I’ve been using AI coding assistants for the past year, and here’s what actually happens:

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// What I used to write (2022):
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function calculateCompoundInterest(principal, rate, time, compound) {
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  const amount = principal * Math.pow(1 + (rate / compound), compound * time);
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  const interest = amount - principal;
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  return {
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    finalAmount: Math.round(amount * 100) / 100,
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    totalInterest: Math.round(interest * 100) / 100
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  };
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}
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// What I write now (2025):
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// "Create a compound interest calculator with proper rounding"
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// AI generates the above function + tests + documentation + error handling

I’m not writing functions anymore. I’m describing what I want, and the AI writes the implementation. That’s not “assisted programming”—that’s specification-driven development.

The Three Phases of Programming Death

Based on what I’m observing, the death of traditional coding is happening in three phases:

Phase 1: AI Autocomplete (2022-2024)

• Tools like Copilot and TabNine emerge
• Programmers get 20-30% productivity boost
• Industry says “AI is just a tool to help developers”
• Most developers remain in denial

Phase 2: AI Code Generation (2024-2026) ← We are here

• AI can write entire functions from comments
• Natural language programming becomes viable
• Junior developers start getting laid off
• Senior developers still feel safe

Phase 3: AI Software Engineering (2026-2028)

• AI can build entire applications from requirements
• AI handles architecture, testing, deployment
• Only prompt engineers and AI trainers remain
• Traditional programming becomes a hobby

The Economics Don’t Lie

Let’s talk about the math that everyone’s ignoring:

Cost of Human Developer

• Salary: $120K/year average
• Benefits: $30K/year
• Office space: $15K/year
• Management overhead: $20K/year
• Total cost: ~$185K/year

Cost of AI Developer

• Claude/GPT-4 API: ~$2K/year for heavy usage
• Compute costs: ~$5K/year
• Human oversight: ~$20K/year (1 AI manager per 10 AI agents)
• Total cost: ~$27K/year

That’s a 85% cost reduction. Even if AI is only 70% as effective as humans, the economics are overwhelming.

What “Coding” Actually Looks Like Now

Here’s a real example from last week. I needed to build a data visualization dashboard:

Old way (2022):

1. Set up React project
2. Install chart libraries
3. Write data fetching logic
4. Create components for each chart type
5. Handle state management
6. Write CSS for styling
7. Add responsive design
8. Write tests
9. Time: 3-4 days

New way (2025):

1. Describe requirements to AI
2. Review generated code
3. Deploy to Vercel
4. Time: 2 hours

The AI generated everything: React components, chart configurations, responsive CSS, API integration, error handling, and tests. I just provided feedback and made minor adjustments.

The Skills That Still Matter

Don’t get me wrong—this doesn’t mean all tech jobs disappear. But the valuable skills are shifting dramatically:

Dead Skills (Stop Learning These)

• Writing boilerplate code
• Memorizing syntax
• Manual testing
• Basic CRUD operations
• Framework configuration

Essential Skills (Learn These Now)

• Prompt engineering: How to communicate effectively with AI
• System architecture: Understanding how pieces fit together
• Product thinking: What should we build and why?
• AI model evaluation: How to assess if AI output is correct
• Business logic: Domain expertise that AI can’t replicate

Real-World Evidence: What Companies Are Actually Doing

While the programming community debates this on Twitter, companies are quietly making moves:

Startups Going AI-First

• Replit: Building AI powered development environments
• GitHub: Doubling down on Copilot enterprise features
• Vercel: Integrating AI throughout the deployment pipeline
• Cursor: AI native code editor with 50% faster development

Enterprise Adoption

I know engineering managers who’ve reduced team sizes by 30% while maintaining the same output. They’re not firing people (yet)—they’re just not backfilling when people leave and using AI to pick up the slack.

The Quiet Revolution

The most telling sign? Companies stopped posting junior developer positions. When’s the last time you saw a “Junior React Developer” job that wasn’t a scam? They’re hiring AI prompt engineers instead.

The Denial Phase (Where Most Developers Are)

I get it. Accepting that your entire skill set might become obsolete is terrifying. I’ve seen this denial play out in stages:

Stage 1: “AI can’t replace real programmers”
Stage 2: “AI is just a tool, like IDEs or frameworks”
Stage 3: “AI still needs human oversight”
Stage 4: “Only junior developers will be affected”
Stage 5: “AI will create new types of programming jobs”

Here’s the problem with each stage:

1. AI is already replacing programmers for routine tasks
2. IDEs don’t write code—AI does
3. Human oversight is becoming automated too
4. Senior developers aren’t immune
5. New jobs require completely different skills

What This Means for Your Career

If you’re currently a programmer, you have roughly 18-24 months to transition before the market fundamentally shifts. Here’s your roadmap:

Immediate Actions (Next 6 Months)

1. Master AI tools: Become expert level with Copilot, Cursor, or Claude
2. Learn prompt engineering: Treat it like a new programming language
3. Focus on architecture: Understand system design and scalability
4. Develop domain expertise: Pick an industry and become the expert

Medium term Strategy (6-18 Months)

1. Transition to AI management: Lead teams of AI agents instead of humans
2. Build product skills: Learn to identify what should be built
3. Develop business acumen: Understand market needs and customer problems
4. Create content: Document your AI assisted development process

Long term Positioning (18+ Months)

1. Become a solution architect: Design systems, don’t implement them
2. Start consulting: Help companies transition to AI first development
3. Build AI powered products: Use your technical background to create AI tools
4. Teach others: The transition will create demand for AI development education

The Uncomfortable Truth About Junior Developers

If you’re just starting your programming career, I have some tough love for you: traditional entry level programming jobs are disappearing faster than anyone wants to admit.

The junior developer career path:

1. Learn basic programming
2. Get hired for simple tasks
3. Gain experience on real projects
4. Graduate to complex problems
5. Become senior developer

The problem: Steps 1-3 are being automated away. AI can handle the simple tasks that junior developers used to cut their teeth on.

The new reality: You need to skip directly to step 4 or find a different career path entirely.

What About the “But AI Makes Mistakes” Argument?

Yeah, AI makes mistakes. So do humans. The difference is:

Human mistakes:

• Inconsistent (depends on mood, experience, focus)
• Hard to catch systematically
• Expensive to fix (requires hiring more humans)
• Scale linearly with team size

AI mistakes:

• Consistent (same prompts produce similar outputs)
• Can be caught with automated testing
• Cheap to fix (adjust prompts, retrain models)
• Scale gets better over time

Plus, AI mistakes are decreasing exponentially while human mistakes remain constant. GPT-5 will make fewer errors than GPT-4, which already makes fewer errors than most junior developers.

The Network Effects Are Starting

Here’s what really worries me about the programming job market: network effects are kicking in.

The cycle:

1. Companies use AI to reduce development teams
2. Fewer programming jobs available
3. More programmers competing for remaining positions
4. Salaries drop due to oversupply
5. Companies save even more money using AI instead of cheaper humans
6. Repeat

We’re seeing early signs of this cycle in frontend development. React developer salaries have been flat for 2 years while AI capabilities have exploded.

Looking at Other Industries That Went Through This

Travel agents didn’t disappear overnight when Expedia launched. It took about 10 years. First, corporate travel stayed human managed while leisure travel went online. Then business travel started using online tools. Now travel agents exist only for complex international business trips and luxury travel.

Bank tellers didn’t disappear when ATMs were invented. It took 15 years. First, simple transactions moved to ATMs. Then deposits and transfers. Now tellers handle only complex financial products and customer service issues.

The pattern: The transition is gradual, then sudden. Most of the job goes away, leaving only the highest value, most complex work for humans.

Programming is following the exact same trajectory, just faster.

My Prediction for 2028

By 2028, here’s what I think the programming landscape will look like:

90% of traditional programming jobs: Gone. Replaced by AI.

Remaining 10%: Split between:

• AI engineers (3%): People who build and train AI systems
• Solution architects (4%): People who design complex systems
• Domain experts (2%): Programmers with deep expertise in specific fields
• AI managers (1%): People who coordinate teams of AI agents

New job categories:

• Prompt engineers
• AI training data specialists
• Human AI interface designers
• AI ethics and safety engineers

Salary ranges:

• AI engineers: $300K-500K (high demand, low supply)
• Solution architects: $200K-350K
• Domain experts: $150K-250K
• Everyone else: Career change required

What You Should Do Starting Tomorrow

Stop learning new programming languages. Stop memorizing algorithms. Stop building to do apps.

Instead:

1. Pick an AI coding assistant and use it for everything. Get comfortable being an AI manager.

2. Choose a domain (healthcare, finance, logistics, etc.) and become the expert in that space.

3. Learn to write better prompts than anyone else. This is the new “coding skill.”

4. Build something people actually want using AI assistance. Focus on the problem, not the implementation.

5. Start creating content about AI assisted development. The transition will create massive demand for education.

The Bottom Line

Look, I’m not happy about this. I loved programming. There was something magical about crafting elegant code, solving complex algorithmic problems, and building systems from scratch.

But nostalgia doesn’t pay the bills.

The writing is on the wall, and the wall is covered in AI generated code. You can either adapt to this new reality or get left behind arguing about why “real programmers” will always be needed.

The choice is yours. But choose fast—the window for graceful transition is closing.

Coding is dead. Long live AI assisted problem solving.

P.S. - I know this is going to piss off a lot of developers. But someone needs to say it. The emperor has no clothes, and the emperor in this case is the belief that writing code manually will remain a viable career long term. Wake up.

¹ GitHub AI Impact Report, 2024
² Stack Overflow Developer Survey, 2024
³ Microsoft Copilot Productivity Study, 2024