Artificial intelligence can already write code, create components, detect bugs, generate tests, and work on entire projects.
Tools that seemed like science fiction a few years ago are now part of many developers’ daily work.
This has raised an inevitable question:
Will artificial intelligence eventually replace web developers?
The short answer is that AI is already replacing tasks, but that does not necessarily mean it is replacing the developer.
The distinction matters.
AI has already changed how we code
Adoption of artificial intelligence among developers is widespread.
According to the Stack Overflow Developer Survey 2025, 84% of respondents use or plan to use AI tools in their development process. Among professional developers, 51% reported using them daily.
Today, we can ask AI to:
- generate components;
- explain code;
- find bugs;
- write tests;
- refactor;
- consult documentation;
- modify multiple files;
- analyze a repository;
- propose an architecture.
We are moving rapidly from assistants that completed a few lines of code to agents capable of carrying out entire tasks.
That changes our work considerably.
But there is something we should not confuse:
Writing code is not the same as developing software.
So, what can AI replace?
Probably an increasing amount of repetitive work.
Imagine you need to transform this array:
const users = [
{ name: 'Ana', active: true },
{ name: 'Pedro', active: false },
];into a list containing only the names of active users.
AI can generate this almost instantly:
const activeUsers = users
.filter(({ active }) => active)
.map(({ name }) => name);Competing against AI to see who can write that function faster makes little sense.
But someone still needs to know:
what the code does, whether it actually solves the problem, and what could go wrong.
That is where the difference between generating code and understanding software begins.
The most interesting finding: we use AI, but do not fully trust it
Here is an interesting contradiction.
Although AI adoption among developers keeps growing, trust is not growing at the same pace.
Stack Overflow found that 46% of developers distrust the accuracy of AI tools, compared with 33% who trust them.
There is a reason that will sound familiar to anyone who codes with AI.
66% identified receiving solutions that are “almost right” as one of their main frustrations.
That “almost” matters a great deal.
Code can look perfectly reasonable and still contain:
- a logic error;
- an unnecessary dependency;
- a vulnerability;
- performance problems;
- a poor architectural decision.
AI can generate a hundred lines in seconds.
But if you then spend an hour figuring out why those lines broke production, generating more code does not necessarily mean being more productive.
Does AI really make us code faster?
Sometimes it does.
But not always.
This is where the research gets interesting.
Different studies have found significant productivity improvements when using coding assistants.
However, an experiment by METR on early-2025 AI tools involving experienced developers found something unexpected.
Participants worked on open-source projects they knew deeply. Before starting, they believed that using AI would reduce the time needed to complete their tasks by approximately 24%.
The result was the opposite.
Under the conditions studied, they took approximately 19% longer when using AI.
This does not mean AI makes every developer slower. The study itself makes clear that its results apply to experienced developers working on repositories they knew very well.
But it demonstrates something important:
Using AI does not automatically guarantee greater productivity.
It depends on the task, the context, and especially our ability to evaluate what the tool is doing.
So, does learning to code still make sense?
More than ever.
But probably for different reasons.
You do not need to memorize every JavaScript method or compete with AI at writing syntax.
You need to understand the fundamentals well enough to look at generated code and ask:
Is this actually correct?
When AI generates a working application, there are still questions to answer:
Is the data validated?
Is authentication secure?
Does the architecture make sense?
Can the application scale?
Are we exposing sensitive information?
Does the solution actually meet the requirements?
Will we be able to maintain this code in two years?
Artificial intelligence can propose a solution.
The developer is still responsible for evaluating it.
The risk of coding without understanding the code
This brings us to one of the most popular concepts of recent years: vibe coding.
The idea is essentially to describe what we want in natural language and let AI generate much of the software.
For prototypes and personal projects, it can be incredibly useful.
The problem begins when we put code into production that nobody understands.
An application can work perfectly during a demo and still have security, performance, or architectural issues that emerge later.
Using AI therefore does not remove the need for technical knowledge.
In fact, it may increase the importance of a different skill:
knowing how to review.
The developer is moving from writing to directing
Perhaps this is the change that really matters.
For a long time, the workflow was:
Problem → Developer → Code → Product
Then assistants arrived:
Problem → Developer + AI → Code → Product
Now we are entering a different stage:
Problem → Developer → AI agent → Code → Review → Product
The developer begins working at a higher level.
They define goals.
Provide context.
Choose an architecture.
Review results.
Test.
Correct.
And make the final decision.
DORA, Google’s research program on software team performance, reached an interesting conclusion in its 2025 research:
AI primarily acts as an amplifier.
It can amplify a good development system.
But it can also amplify poor practices.
Someone who understands development can use AI to work much faster.
Someone who does not understand what they are building can also generate mistakes much faster.
What will happen to junior developers?
This is probably one of the biggest challenges.
Many tasks traditionally assigned to junior developers are precisely those that are easiest to automate:
- simple components;
- small changes;
- documentation;
- basic tests;
- repetitive tasks.
This could change how people enter the industry.
There is a paradox:
to become a senior developer, you need experience; to gain experience, you first need to be a junior.
That is why I think learning syntax alone will become increasingly insufficient.
New developers will need to strengthen fundamentals such as:
JavaScript, Git, APIs, databases, debugging, security, architecture, testing, and performance.
And add a new skill:
knowing how to work with artificial intelligence.
So… will AI replace us?
Nobody can say with certainty what these tools will look like in five or ten years.
Denying that AI could reduce certain jobs would be just as unrealistic as claiming that every developer will disappear.
What we can observe today is something much more concrete:
AI is already replacing tasks.
And it will probably replace many more.
But developing software has never been only about writing code.
It is about solving problems using technology.
As long as we need to understand problems, design solutions, assess risks, make decisions, and take responsibility for the result, there will still be a role for people who know how to do those things.
Perhaps the developer of the future will write less code manually.
But they will need to understand the system they are building more deeply.
The right question is not “developer vs. AI”
Artificial intelligence can generate code much faster than a person can type it.
Trying to compete with that would be pointless.
The opportunity lies elsewhere:
what can a good developer accomplish when they also have artificial intelligence available?
Research faster.
Automate repetitive tasks.
Explore different solutions.
Find bugs.
Generate tests.
Learn technologies.
Build prototypes.
Work with agents.
AI can become a powerful multiplier.
But there is one condition:
we need to understand enough to recognize when it is wrong.
That is why the future of development will probably not be:
AI vs. developers.
It will be:
developers working with AI.
Perhaps the most important skill will no longer be writing every line of code manually.
It will be knowing what to build, how to build it, and how to recognize when the machine is getting it wrong.
References
Stack Overflow — Developer Survey 2025
Data on developers’ adoption, trust, and use of artificial intelligence.
METR — Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
A controlled experiment on the impact of AI tools on experienced developers.
DORA / Google — State of AI-assisted Software Development 2025
Research on the impact of artificial intelligence on software development teams and organizations.