How AI Is Changing Developers

In the last few years, AI has moved from “nice to have” to “hard to live without” for developers. At first it was just code completion and smart hints. Now it’s getting deep into how we build software: the methods, the toolchain, and even the job itself.

Here are some structured thoughts on how AI is affecting developers, based on trends and personal experience.

Every library will have AI-first docs

Future libraries and frameworks won’t just have docs for humans. They’ll also have a manual for AI:

• How to use
• Why it is designed this way
• What NOT to do
• Conventions & Best Practices

Once these rules are written in a structured way, AI can onboard to a library faster and more consistently than a junior developer.

Docs won’t just be knowledge anymore. They’ll be instructions AI can execute.

AI will be a must-have for developers

Soon, “writing code without AI” will feel as strange as “writing code without an IDE.”

• It won’t be about whether you use AI
• It’ll be about how well you use it and where

AI will become:

• A standard productivity tool
• An extension of a developer’s thinking
• A second brain

Developers who don’t use AI will fall behind in both speed and understanding.

As AI gets smarter, it replaces “time”

AI isn’t replacing developers right away. It’s replacing:

• Lots of repetitive time
• Basic development costs
• Higher output per hour

Boilerplate, CRUD, basic validation, simple logic — all of that will get swallowed fast.

It’s not people being replaced. It’s waste.

Orchestrating multiple AIs becomes real

The future isn’t “one AI does everything.” It’s more like:

• Claude writes core code
• Copilot generates and maintains unit tests
• Codex and similar tools write docs and examples
• Other AIs handle refactoring, performance analysis, security checks

The dev process itself becomes an AI orchestration system.

The developer’s role looks more like:

Architect + conductor + quality gatekeeper

Only great infrastructure gets amplified by AI

Even if AI can teach you “how to use it correctly,” it still can’t invent mature infrastructure for you.

We still rely on:

• Stable base frameworks (like ABP)
• Engineering capability proven by many projects
• Long-term maintenance and evolution

AI is an accelerator, not the foundation.

For open source, AI is actually a better companion:

• Helps understand the source code
• Helps learn design thinking
• Helps ship faster

The stronger the infrastructure, the more value AI can amplify.

Frontend feels mature; backend still evolving

From personal experience:

• AI is already very strong in frontend work (Bootstrap / UI components, layout, styling, interaction)
• Backend is still learning and improving (business boundaries, architecture trade-offs, implicit constraints)

This shows: the clearer the rules and the faster the feedback, the faster AI improves.

Writing rules for AI is productivity itself

In the ABP libraries, we’ve already written lots of rules for AI:

• Conventions
• Usage limits
• Recommended patterns

As rules grow:

• AI becomes more stable
• More predictable
• Base development work can be largely automated

Future engineering skill will be, in large part: how to design a rules system for AI.

The real advantage is better feedback loops

AI gets much stronger when there’s clear feedback:

• Tests that run fast and fail loudly
• Logs and metrics that explain behavior
• Code review that checks for edge cases and security

The teams that win are the ones who can quickly verify, correct, and learn.

About a developer’s career

Sometimes I think: I’m glad I didn’t enter the software industry just in the last few years.

If you’re just starting out, you really feel:

• The barrier is lower
• The competition is tougher

But whenever I see AI generate confident but wrong code, I’m reminded:

• The industry still has a future
• It still needs judgment, taste, and experience

There will always be people who love coding. If AI does it and we watch, that’s fine too.

Chaos everywhere, but the experience is moving fast

Big companies, platforms, tools:

• GitHub
• OpenAI
• Claude
• All kinds of IDEs / agents

New AI tools, apps, and platforms keep popping up. New concepts show up almost every week. It’s noisy, but the big picture is clear: AI keeps getting better, and the overall developer experience is improving fast.

Get ready for the AI revolution

Looking back at personal experience:

• Before: Google
• Now: ChatGPT
• Before: manual translation
• Now: fully automatic
• Before: writing unit tests by hand
• Now: AI does it all
• Before: human replies to customers
• Now: AI-assisted or even AI-led

From code completion to agents running tasks, and now deep IDE integration — the pace is shocking.

Closing

AI is not the end of software engineering. It is:

• A leap in cognition
• A restructure of how work gets done
• An upgrade of roles

What matters most isn’t how much code AI can write, but how we redefine the value of “developers” in the AI era.