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Python print() Function

When you start learning Python, one of the first things you need to learn is how to display information on the screen. For example, you might want to display: A welcome message. Your name and age. The result of a mathematical calculation. Student marks and results. Information generated by a Python program. Python provides a built-in function called print() for displaying information. The print() function is one of the simplest and most frequently used functions in Python. It helps programmers display information while testing programs, solving problems, and developing applications. In this article, we will learn how to use print() with practical examples and their outputs. 1. What Is the print() Function in Python? The print() function is a built-in Python function that displays information in the output area, usually the terminal or console. Let's look at a simple example. print("Hello, World!") Output: Hello, World! In this example, Python displays the text Hello,...

Coding Is Dead.Coding Is Dead — 2026

**Coding Is Dead — 2026**

*An Obituary for the Craft That Built the Modern World*


Three years ago, if you told a software engineer that typing code by hand would feel as quaint as handwriting a letter, they'd have laughed you out of the stand-up. Today, they're not laughing. They're rewriting their LinkedIn bio.


The numbers are brutal. Bootcamps that once had thousand-person waitlists have gone dark. Computer science enrollment is down for the first time in a decade. Junior developer job postings have evaporated — not shifted, not transformed. Evaporated. The industry didn't pivot around the coder. It just moved on without them.


**The Slow Death Nobody Noticed**


It didn't happen overnight. It happened in four stages, each one quietly lowering the bar for what a human needed to know. First came autocomplete. Then came Copilot-era tools that finished your thoughts. Then came agent frameworks that wrote entire files on command. Then came 2025, and the tools stopped asking for your input at all.


The transition was so smooth that developers barely noticed they were becoming *editors* rather than *authors*. They were reviewing AI output, tweaking variable names, approving pull requests the machine had already written, tested, and documented. The job title said Engineer. The job description said "prompt, review, ship."


We trained a generation to speak machine. Then the machine learned to speak human — and it never looked back.


What collapsed wasn't engineering. Engineering — the *thinking*, the architecture, the judgment — that's still alive, barely. What collapsed was *coding*: the manual, syntactic, line-by-line act of writing instructions for a computer. The keyboard shortcut. The muscle. The craft.


**Who Actually Got Hurt**


The mythology of the tech industry was always that anyone could learn to code and change their life. Bootcamps sold this dream for $15,000 a seat. Self-taught developers lived it. For a decade, it was even true. The ladder from "I learned Python on YouTube" to "$120k salary" was real and it was short.


That ladder is gone. The bottom rungs — the for loops, the CRUD apps, the bug fixes, the WordPress plugins — all the entry-level work that once employed hundreds of thousands of people and taught them to eventually become senior engineers? AI eats that work for breakfast and asks for more.


The people who got hurt aren't the Principals at Google. They're the career-changers who spent six months at a bootcamp in 2023. The self-taught kids who were almost there. The offshore teams hired to write boilerplate at scale. The industry didn't close the door on them. It removed the door, filled in the doorway, and put up wallpaper.


**The Senior Developer Delusion**


Ask any senior developer today whether they're worried, and most will tell you no. "AI just handles the boring stuff," they'll say. "It frees me up for the interesting problems." And they're not wrong — yet. The interesting problems still require human judgment. System design, stakeholder alignment, architectural trade-offs: these demand experience and context that no model has perfectly mastered.


But here's the trap: the boring stuff *was* how you earned the right to solve interesting problems. Junior developers wrote boring code. They made boring mistakes. They learned from them. They became senior developers. Remove the boring work and you get a generation of people who never got the chance to become senior at anything.


In five years, who fills the seats when today's seniors retire? You cannot fast-track ten years of experience. You cannot prompt-engineer your way to intuition.



**What "Coding" Actually Becomes**


Coding in 2026 is not dead in the way that painting is dead. Painting survived photography. Painters are still out there. But photography didn't need painters anymore — industries didn't hire them, newspapers didn't call them, studios didn't train armies of them.


The same schism is happening here. There will always be people who code for the love of it — hobbyists, artists, researchers pushing the edges of what machines can do. But the *industry* — the economic engine that made "learn to code" the great equalizer promise of the 2010s — that's restructuring around a world where code is a commodity and the human who writes it by hand is an expensive anachronism.


What fills the gap? Something we don't have a clean word for yet. Part product manager, part systems thinker, part AI wrangler, part domain expert. The valuable human in the software loop of 2026 is not the one who knows Python best. It's the one who knows *what to build*, *why to build it*, and *whether the AI actually built what they asked for*.


**Grieve It. Then Figure Out What's Next.**


There's a real loss here worth acknowledging. Coding was more than a job skill. For an entire generation, it was a way of thinking — methodical, logical, iterative. It taught people how to break big problems into small ones. It was *genuinely empowering*. The kid who built their first app in a bedroom at 3 AM and felt like they could make something from nothing — that feeling mattered.


AI can produce the app faster. It cannot produce that feeling. Whether the next generation finds an equivalent — in systems thinking, in AI orchestration, in some new form of creative technical work we haven't named yet — is the real question of the next decade.


But let's not pretend that "everyone should learn to code" is still a useful answer to anything. The advice has expired. The certificate is no longer valid. The era it described is over.


*R.I.P. Manual Coding — 1950 to 2025*


The eulogy isn't pessimism. It's clarity. You can't navigate what's coming if you're still giving directions to a city that burned down. Coding is dead. The work of understanding that — and building something true in its place — is just beginning.


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