Is Python Dead in 2026?
The Data Says Otherwise.

Key Takeaways

Python isn't dying - it's becoming more essential. Here's what the data actually shows and what John covers in the video above.

The developer job market is splitting in two. AI is automating basic coding tasks, which means entry-level "copy-paste" developer roles are shrinking. But developers who understand Python, AI, data, and system architecture are seeing salary bumps of thousands of dollars. The question isn't whether to learn to code - it's what kind of developer you want to become.

Python is the language of AI. Every major AI framework - TensorFlow, PyTorch, LangChain, scikit-learn - is built on Python. AI coding tools like Claude Code and GitHub Copilot generate more Python than any other language. If you want to work in AI, Python isn't optional.

Knowing Python makes you better at using AI. People who understand code can direct AI tools more effectively, catch errors in generated code, and build real systems. "Vibe coding" - describing what you want and letting AI build it - works far better when you understand the fundamentals.

Frequently Asked Questions

Full Video Transcript

Transcript of "Python Is Dead? The Data Says Otherwise" by John Elder

Can AI Replace Learning Python?

So AI can write code now. You've probably seen people on Twitter building entire apps without typing a single line of Python. They call it vibe coding and you just tell AI what you want and boom, out pops a working program. And that raises a pretty obvious question. Why would anyone bother learning Python in 2026?

Well, I've been coding for over 30 years and I'm going to tell you something that might surprise you. And the answer isn't what either side wants to hear. Stick around because the data on this is wild.

So, should you learn Python now that AI can code for you? And look, I get why people are asking this. 92% of developers are already using AI tools every single day. People who've never written a line of code are building apps with ChatGPT and Claude Code. So, it feels like maybe this whole learn to code thing is over. But here's the thing, the actual numbers tell a completely different story than what you're hearing on social media. So, let's dig in.

What Is Vibe Coding - and Is It Already Dead?

All right. First, let's spend like 10 seconds talking about what vibe coding is because this is where a lot of people are getting confused. So, Andrej Karpathy, the guy who literally coined the term vibe coding, one of the top AI researchers in the world. He worked at Tesla and OpenAI and recently he basically said it's already kind of passé. He's moved on to what he's calling agentic engineering. So, even the guy who invented vibe coding is saying, "Hey, it's not really a thing anymore."

What the Data Says About AI-Generated Code Quality

And the data backs him up. A study from Code Rabbit at the end of 2025 found that code co-authored by AI has 1.7 times more major bugs than human written code. And here's the scary one, 2.74 times more security vulnerabilities. So almost three times the security holes.

InfoIP did another study and found that yeah, AI makes you four times faster, and that's great, but the code it ships is 10 times riskier. So you're building four times faster, but creating 10 times more risk. That math just doesn't work.

And here's the one that really blew my mind. Experienced developers, people who actually know how to code, were 19% slower when using AI tools, even though they believed they were faster. They felt faster, but they weren't because they were spending all their time reviewing, fixing, and debugging what the AI had generated. Think about that. If experienced developers are struggling with AI generated code, what happens when someone with zero coding knowledge tries to build anything real?

The Job Market: Two Completely Different Stories

Now, let's look at the job market because this is where it gets really interesting. There are two completely different stories happening at the exact same time here.

Story One: Entry-Level Developer Jobs Are Getting Crushed

Story number one is the bad news. Junior developer job postings are down about 40% compared to just a few years ago. Over half of engineering leaders, 54%, say they plan to hire fewer junior developers. Entry-level salaries actually dropped from about $99,000 to $91,000 between 2025 and 2026. And Stanford put out research showing that employment among developers aged 22 to 25 fell nearly 20% between 2022 and 2025. So the entry level is getting absolutely crushed. That's real and I'm just not going to sugarcoat it.

Story Two: Senior Python Developers Are Getting Big Raises

But here's story number two. Senior Python developer salaries hit $172,000 in 2026 and that's up 15% from a year ago. There are over 108,000 active Python job openings right now. Python hit 26.14% on the TIOBE index, which is the highest rating any programming language has ever received in the 23-year history of that index. Nearly 58% of all developers use Python. And the Bureau of Labor Statistics projects 15% growth in software dev jobs over the next decade and 36% growth in data science.

So, what's happening? Well, the bottom is falling out, but the top is exploding. And that tells you something really important about what learning Python actually means in 2026.

The New Model: Python as the Quality Gate

So here's where you need to shift your thinking. The old model of learning Python was you learn the syntax, you learn loops and functions and classes, and then you go get a job writing basic web apps or CRUD apps. That model, yeah, that's gone. AI can do that. And honestly, AI can write a basic CRUD app probably better than a junior developer can.

But here's the new model. You learn Python so you can understand, audit, direct, and fix what AI generates. Python isn't the production line anymore. Python is the quality gate. You're not learning Python to write every single line of code yourself. You're learning Python so that when AI spits out code with 2.74 times more security vulnerabilities, you can catch it. When it generates something that looks right, but has subtle logic errors, you can spot them. When you need to architect a system that actually scales, you know enough to direct the AI properly.

Think of it like this. Let's say self-driving cars get really good. Does that mean nobody needs to understand how cars work? No. It means the people who understand how cars work become much more valuable because someone has to make sure the self-driving car isn't going to drive you off a cliff. That's you with Python.

Why Python Is the Prerequisite for AI Work

Google's head of research just came out and said that basic programming skills are "more important than ever." Andrew Ng's DeepLearning.ai launched a course called AI Python for Beginners because Python is literally the prerequisite to working with AI. You can't fine-tune a model. You can't build a RAG pipeline. You can't do any serious AI work without Python. So, the language that powers AI is the language you need to learn to work with AI.

What You Should Focus On Learning

So, if you're watching this and you're thinking, "Okay, I'm convinced. What do I actually need to focus on?" Here's my take.

Number one, learn the fundamentals: variables, loops, functions, classes, error handling. You don't need to memorize every method on every object, but you need to understand what code is doing when you look at it. You need to be able to read code fluently.

Number two, learn to read and debug. This is more important now than ever. Your primary job with AI generated code is going to be reviewing it. Can you look at a function and spot the edge case it missed? Can you trace through the logic and find where it breaks? That skill is worth its weight in gold.

Number three, learn the AI ecosystem. Python plus AI is where the money is. Learn the basics of working with APIs. Learn a little bit about how models work. Understand concepts like tokens, embeddings, and prompting. That combination of Python knowledge plus AI understanding is the new sweet spot.

And number four, build real projects, not to-do apps or calculator apps. Build something that solves a real problem. Use AI to help you, absolutely, but understand every line of what it generates. That's how you develop the judgment that companies are paying $172,000 a year for.

The Bottom Line: Learn Python to Work With AI

So, should you learn Python in 2026? Absolutely. But not for the same reasons people said 5 years ago. You're not learning Python to compete with AI. You're learning Python to work with AI, to be the human in the loop who makes sure the AI output is actually correct, secure, and well architected.

The junior developer who just writes what they're told to write, yeah, AI is replacing that. But the developer who understands systems, who can audit code, who can architect solutions and direct AI tools effectively, that person's getting a big raise. And the data shows that clear as day.

And a great place to start is with a totally free PDF copy of my book, Intro to Python Programming. This was the number one Python book on Amazon.com when it first came out. People seem to really like it. And you can get a totally free copy today. Just head over to codemy.com/book.

About John Elder

John Elder has been coding for over 30 years. He runs Codemy.com, an online coding education platform where he's taught over 20 million students and a YouTube channel with over 250,000 subscribers. He also runs JohnElder.AI, where he teaches AI, Python, and agentic workflows.

John is based in Las Vegas, Nevada and has authored multiple courses on Python, Django, Tkinter, and AI development. His teaching philosophy focuses on practical, real-world coding skills - not theory.