#ai#career#development#frontend#backend

AI won't replace devs, but it will filter

After using AI daily, my view became clear: AI doesn't replace developers, but it changes who remains relevant.

AI won't replace devs, but it will filter

Whenever a new relevant technology emerges, the same fear arises:

“It's over now, developers will be replaced.”

This discourse is not new. It has already appeared with modern frameworks, with low-code, with no-code — and now with AI.

The difference is that, for the first time, AI actually writes usable code. And after using AI daily in my workflow, my view today is clear:

AI doesn't replace developers. It filters.

And it's worth making something explicit from the start: this is what is working now, with the tools that exist now. Nothing prevents all of this from changing — and quickly — as is already happening.

The important question is not if AI will replace you, but in which layer of the problem you operate today.

What AI already does better than many devs

Using AI daily removes any romanticization of the subject.

Today, AI performs tasks with extreme efficiency such as:

  • simple CRUD creation
  • boilerplate generation
  • repetitive and predictable code
  • validations, regex, and data transformations
  • translation between languages
  • basic UI components

These activities have always existed, but now they are no longer a differentiator.

Perhaps in a few months the scope will change, perhaps expand, perhaps become even more trivial. But in the current scenario, if a dev's value is concentrated only on this, the risk is already real.

Testing different AIs in my workflow

Instead of treating AI as something generic, I started testing different tools for different problems — at the current moment.

This doesn't mean they will be “the best” forever. It just means that they are the ones that worked best for me now.

Two clearly stood out.

Gemini 3 Pro: real acceleration for UI and UX

In my recent tests, Gemini 3 Pro proved extremely competent for:

  • designing initial screens
  • proposing coherent layouts
  • organizing visual hierarchy
  • suggesting accessibility improvements
  • helping to think about navigation flows

It understands interface intent very well, something essential for front-end.

Perhaps another model will surpass this tomorrow. But today, for UI/UX, it greatly accelerates the phase where I would normally spend more time.

🔗 To follow Gemini's evolutions:

Claude Opus 4.5: technical depth and backend

Claude Opus 4.5, in my current experience, stood out in:

  • business logic
  • backend code organization
  • reading legacy code
  • careful refactorings
  • discussing architecture and trade-offs

It tends to be more conservative, which is positive in systems where errors are costly.

This doesn't mean it's perfect or immutable. It means that today, it works very well as a technical peer for reasoning.

🔗 To follow Claude and Anthropic:

Launching projects faster changes the way we work

One of the most visible impacts of AI today is the reduction in time between an idea and something running.

This blog is a direct example of that.

I used AI to:

  • structure initial content
  • organize loose ideas
  • validate approaches
  • accelerate decisions that previously stalled the project

The project did not lose identity or quality. It simply got off the ground faster.

Perhaps in the future this gain will become standard or lose impact. But now, this completely changes how personal projects and technical experiments are born.

IDEs with AI: real gains in the current workflow

Beyond the models, IDEs with integrated AI are changing the workflow at this moment.

Not because they are perfect, but because they reduce friction in common problems.

Cursor: accelerated reading and refactoring

Cursor has become present in my daily life because it:

  • understands the context of the entire project
  • facilitates refactorings
  • accelerates code reading
  • reduces time spent trying to understand systems I didn't write

Perhaps another IDE will do this better tomorrow. But today, the productivity gain is real.

🔗 Useful links:

  • https://cursor.sh
  • Discussions and examples on GitHub and Reddit (r/programming, r/webdev)

Antigravity: architectural vision and context

Antigravity stands out especially when the project grows:

  • better navigation between files
  • understanding dependencies
  • a more architectural view of the system
  • less time lost hunting for references

In larger systems, this reduces something critical today: cognitive load.

🔗 Useful links:

What AI still doesn't solve (so far)

Even with all this evolution, there are still clear limits — in the current scenario.

AI still doesn't:

  • understand real business context
  • evaluate organizational impact
  • decide trade-offs responsibly
  • deal well with implicit rules of old systems
  • communicate technical decisions to non-technical people

Can this change? Perhaps. Some things are already evolving fast.

But today, the responsibility remains human.

The filtering is already happening

The market is not ending. It is adjusting to the current moment.

  • Juniors without a strong foundation feel it more
  • Mid-level devs who only execute tasks tend to stagnate
  • Those who understand the why of the code gain a real advantage

Today, often:

A good developer with AI delivers more than several mediocre developers without it.

Nothing guarantees that this equation will be identical two years from now. But now, this is what is happening.

The type of developer who remains relevant

From what I've seen so far, those who remain relevant are those who:

  • master fundamentals
  • read code with ease
  • understand product impact
  • communicate technical decisions well
  • adapt quickly to new tools

The tool changes. The foundation remains.

How I try not to be filtered

In my current daily life, I try to:

  • understand why the code works
  • question technical decisions
  • read other people's code
  • care about business impact
  • write: documentation, PRs, and this blog

These practices continue to make sense regardless of the tool of the moment.

Where to follow this topic consistently

Some sources that make sense to follow today, knowing that everything changes quickly:

  • Technical blogs (Google AI, Anthropic, OpenAI, Meta AI)
  • Hacker News
  • GitHub Trending
  • Newsletters like TLDR, Bytes.dev, and Import AI
  • Devs who share real experiences on Twitter/X and LinkedIn

Less hype, more people showing practical use.

Conclusion

My view, based on what I am using and testing now, is simple:

AI will not replace developers. It will replace shallow developers.

The bar has been raised. And it will continue to move.