The Torrential Evolution of Generative AI Tools

Since ChatGPT appeared, code generation was just something I used “here and there.”

But before I knew it, GitHub Copilot, Cline, and Claude Code started appearing one after another - features and services that excite me as a developer. It’s truly a torrential pace.

Moreover, each one has evolved beyond simple code completion to function as a genuine development partner.

The Reality We Can’t Keep Up With - Not Even Enough Time to Benefit

The problem is that updates come so fast that we don’t even have time to enjoy the benefits we want.

A new tool comes out, then immediately the next version is released. While we’re trying to grasp the features, new functionality gets added again.

Just when you think “this looks useful, let me try it,” the next wave has already arrived. We truly can’t keep up with this technological inflation.

And this isn’t just about code generation. Image generation AI (Midjourney, DALL-E, Stable Diffusion), music generation AI (Suno, Udio), video generation AI (Runway, Pika Labs)… it’s spreading to every creative field.

As a developer, just when you think “let me master code generation AI,” suddenly “maybe I should use AI for images, music, and videos too” - new options keep appearing.

It’s a storm of change at a level where you’ll be completely overwhelmed unless you focus somewhere.

Especially for individual developers, balancing time to try new tools with time to actually use them for development has become a major challenge.

For someone like me who squeezes out private time for development while juggling work, household chores, and everything else daily, my curiosity keeps sparking, bringing back that familiar feeling of being fired up.

“A new AI tool is out!” “I want to try this!” The excitement is just like encountering a new programming language or framework back in the day - that same rush.

But realistically, the only thing I can cut back on is sleep. “Let me stay up late tonight to play with this new tool,” but it’s obviously bad for my skin the next day.

It’s quite the dilemma.

Generative AI Has Become Essential to Life

The conversation about generative AI never ends, but these days we can’t live without it. Especially as developers.

  • Code scaffolding generation
  • Bug cause identification
  • Refactoring suggestions
  • Documentation creation
  • Design brainstorming partner

Before you know it, generative AI is involved in every aspect of the development workflow.

Just like how we reached a point where “we can’t research anything without search engines,” we’re approaching a situation where development can’t progress without generative AI.

The Earth-Shaking Changes from the BASIC and Assembly Era

I’ve been immersed in programming and software development since the days of BASIC and assembly language, and fortunately made it my livelihood.

Programming Environment of Those Days

Programming back then meant:

  • Coding in environments with barely any editors
  • Debuggers were luxury items
  • A small mistake would crash the entire system
  • References were only paper books
  • You couldn’t even copy-paste (had to physically type everything)

Looking back, I can’t believe we developed in such conditions.

Reckless Challenges of Youth

As a kid, I too dreamed of “making RPGs like Mario, Dragon Quest, and Final Fantasy!” But I was like “where do I even start?”

It wasn’t like today where you can “take a photo with your smartphone,” so I manually copied designs from CRT screens and borrowed game strategy guides onto paper. Character pixel art, map structures - everything by hand.

But how do you turn that into an actual game? All I had was a text editor and BASIC (later upgraded to Fujitsu High C compiler lol).

“Can I do it? Hell yes, I can.”

“First, let me make the tools! I’ll create the most user-friendly paint editor ever!”

Looking back, I might have been a bit of an oddball kid. I felt like the world itself was composed of if statements, for loops, and goto statements.

Walking down the street, I’d think “this sign is buggy!” or “this route is longer but statistically it’d be faster,” - I was probably a complete weirdo.

When friends said “I got a new game,” I’d say “then I’ll make one.” “Can’t afford a YAMAHA sequencer (music-making tool), so I’ll make something similar!” When mom said “help me with chores,” I’d counter with “can you help me debug instead?”

I was a completely unhinged kid.

Without the internet, I fought with error-filled books night after night. Looking back, it was probably that pure passion and recklessness that let me discover the joy of programming.

Little did I know I’d revive it online as Pixnote 30 years later.

Experiencing Gradual Evolution

After that, I experienced the gradual evolution firsthand: the emergence of integrated development environments (IDEs), internet documentation searches, Stack Overflow information sharing, GitHub code management…

But all of these were evolutions that extended existing development styles.

A World-Turning Revolution

However, the emergence of generative AI is fundamentally different.

While previous evolution was about “making development easier” and “increasing efficiency,” generative AI represents a “changing the essence of development” level of change.

From Mechanization Revolution to Intelligence Revolution

Looking at the bigger picture, previous technological evolution was purely a mechanization revolution creating physical tools.

  • Faster processors (improved calculation speed)
  • Larger memory (expanded storage capacity)
  • Better editors (improved input efficiency)
  • More advanced IDEs (integrated work environments)

All of these “physically supplemented and extended human capabilities.”

But generative AI is different. Because it has acquired intelligence - a trait that was uniquely human - we’ve shifted to a completely different world.

Thinking, judging, creating… these were domains that only “humans could handle.” The moment AI started taking on these roles, the very premise of development changed.

Traditional Development Flow

Problem definition → Research → Design → Implementation → Testing → Debugging

AI Era Development Flow

Problem definition → AI dialogue design → AI-generated code → Human verification/adjustment → AI debugging

We’ve shifted from “writing programs” to “conversing with AI about programs.”

This is what I consider an earth-shaking revolutionary change.

The Wavering of Developer Identity

Honestly, there are moments when my identity as a developer wavers.

When faced with the reality that “code I spent hours writing can be generated by AI in minutes,” I’m beyond complex feelings - it’s so incredible I just laugh.

It’s like watching magic performed right in front of me. “Wait, seriously? How did you just do that?” I want to ask the AI. Sometimes I even feel a sense of divine awe.

Empathy for Vanished Professions

Throughout technological revolutions, ice delivery men, lamplighters, telephone operators, hand weavers, and carriage drivers… all disappeared.

“I feel like I understand how those people felt…”

The ice delivery man probably thought “cutting and delivering ice is my specialized skill!” and the lamplighter had pride thinking “I manage this town’s lighting!”

But the moment electricity spread, it became “oh, you just flip a switch.”

We programmers might someday be displayed in museums as “people who wrote code by hand.”

“Back in the day, humans used to tap keyboards to create programs” “Wow, that sounds hard! Now you just tell AI ‘make ○○’”

I can almost hear such conversations. Well, that might have its own charm.

But at the same time, I feel that “this is exactly why human roles are changing.”

New Human Roles

  • The ability to see the essence of problems
  • The ability to properly evaluate AI output
  • The ability to draw the big picture of design
  • The ability to ensure quality
  • The ability to make technical decisions

We’re shifting from writing code to creating better software through collaboration with AI.

Coexistence of Chaos and Benefits

Currently, we’re in a situation where chaos and benefits coexist.

The Benefits

  • Dramatic improvement in development speed
  • Lower barriers to realizing ideas
  • Improved learning efficiency
  • Liberation from mundane tasks

The Chaos

  • Tool evolution speed we can’t keep up with
  • New challenges in quality assurance
  • Changing value of traditional skills
  • Searching for new development methods

The Sense of Living in Revolutionary Times

From BASIC through C, C++, Java, JavaScript, Python… I’ve seen language evolution, but it was all an extension of accumulated progress.

That’s exactly why I can understand the magnitude of this revolution to my core.

Look, as I write this article, passionate feelings well up…

Various memories flash before my eyes like a slideshow.

  • The pure joy when “Hello, World!” first appeared
  • Those sleepless nights struggling with pointers for three days
  • The “Yes!” excitement when my first GUI app worked
  • The shock of “what an amazing era!” when I could search source code online
  • The surprise of seeing others’ code on GitHub and thinking “wow, you can write it like that?”

Looking back at each of these experiences, I realize they were all important turning points in technological history.

And now, by taking a bird’s eye view of these decades of technological transition, I can see the essence of the generative AI revolution.

Previous paradigm shifts all resulted in efficiency improvements in computational resources and toolchains. But generative AI is technology that fundamentally changes the approach to problem-solving itself.

Instead of thinking “how to implement,” we just need to convey “what we want to create.” The abstraction level has gone up a notch.

Historical Evolution of Abstraction

Looking back at technological history, we can see the evolution of abstraction at each stage:

  • Assembly to C: Memory management abstraction
  • Structured programming to object-oriented: Abstraction through data and process coupling
  • Rise of frameworks: Architecture pattern abstraction

And generative AI realizes the ultimate abstraction - “direct conversion from intention to implementation” - encompassing all of these.

We might be witnessing the most dramatic moment of abstraction in computer science history.

Hope and Anxiety for the Future

I honestly can’t see where this change is heading.

But what I can say for certain is that as long as we live as developers, we have no choice but to accept and adapt to this change.

And above all, if you have curiosity and willingness to learn about technology, you can enjoy this revolutionary era.

Actually, I’m having so much fun I can barely sleep.

Every time a new AI tool comes out, I get excited wondering “what can this one do?” I’m enjoying everything as entertainment - past experiences, the current technological revolution, and the slideshow of memories I just mentioned.

Watching features I once struggled to create get generated instantly by AI, I shout “whoa!” and then think “okay, what if I combine this with that to make something new?” - I’m enjoying the very act of creation itself.

Summary - As a Developer Who Enjoys Change

AI-driven development style is still in the trial-and-error phase.

But among my developer life that’s continued since the BASIC era, being able to encounter such an exciting change might be fortunate.

Keeping up is tough, but experiencing this revolutionary era on the front lines is a privilege of engineers.

While bewildered by the rapid pace of change, I want to remain a developer who enjoys change.

Never stop moving. Those who keep running at the cutting edge create the next era - with that mindset, I want to swim through this torrent.