If AI Can Write Most of the Code, Do Developers Still Need to Code?

Imagine we receive a new task. In the past, the first thing many people would likely do was open an IDE, create a new file, and start writing code part by part. But today, the way many developers start their work might have changed. Some begin by typing to an AI, "Please take a look at this repository," "Please add this feature," or "What is causing this bug?" And in some cases, they can even send the requirements to the AI and let it start generating the initial set of code.

Interestingly, AI coding tools today no longer stop at just helping auto-complete code at the end. For instance, GitHub Copilot cloud agent can explore a repository, plan tasks, fix bugs, add features, add tests, edit documentation, and work on a branch before sending the changes back for the developer to review. Reaching this point, an interesting question arises: If one day AI can write most of the code for us, do developers still need to write code themselves?

This article does not intend to judge whether writing code yourself is better or using AI is better. Rather, I would like to invite you to consider whether, on the day AI plays a greater role in software development, the phrase "knowing how to code" and the role of a developer might be changing from what they used to be.

From a Code Completion Assistant to an AI that Takes on Tasks Itself

If we go back a few years, the image of an AI Coding Assistant might have been a tool that kept guessing what we were about to write and helped complete the next line of code. However, current tools are beginning to operate on a much larger scale.

For example, GitHub Copilot cloud agent can take a task, explore the codebase, plan operations, edit code, run automated tests and linters, as well as prepare changes on a branch. The developer can still come back to review the diff, make adjustments, and make a decision on the outcome before putting it to further use.

The use of AI Agents in developers' work is also starting to increase. A survey by Stack Overflow in April 2026 found that 59% of respondents use AI Agents in their work at some level of frequency, an increase from 31% in the 2025 Developer Survey, while the group using them daily increased from 14% to 37%.

Therefore, the question "Will AI step in to write code for us?" might no longer be a distant future matter. Because in the workflows of some developers, this is already happening.

If AI Can Write It, Why Do We Still Need to Write It Ourselves?

From one perspective, it might be seen that if AI can create functions, components, tests, or help fix bugs, sitting down to write every line of code yourself would probably not be as necessary as before. This perspective has its merits.

GitHub once conducted an experiment with 95 professional developers, assigning them a task to build an HTTP Server with JavaScript. It was found that the group using GitHub Copilot spent an average of about 55% less time on the task than the group that did not use it. However, this experiment was a test with a single type of task under specific conditions, so it should not be interpreted to mean that AI will make all types of development work 55% faster in every case. If AI can help handle repetitive code, generate boilerplate, or initiate parts of the work, developers might allocate their time to other aspects of the job. But the interesting point is that "being able to write code" does not mean "being able to take responsibility for the entire software."

A single software system does not consist merely of code that compiles successfully or a webpage that can be opened. We still have to consider whether the requirements truly match what the users want, whether the chosen architecture is suitable for the system, whether new code will affect other parts, what edge cases we haven't thought of, whether user data is secure, or if the system encounters an issue in production, where we will trace the root cause from.

AI can help us with many parts of these questions, but the ability to generate code and the decision of whether that code is genuinely appropriate for the system are still two different things.

Developers Use AI More, But Don't Believe Everything AI Writes

Another interesting point from the Stack Overflow Developer Survey 2025 is that even though AI has increasingly entered developers' workflows, confidence in AI's output hasn't risen accordingly. When asked about the accuracy of AI's output, 46% of respondents indicated they do not trust or somewhat distrust AI's accuracy, while about 33% stated they trust it, and only 3% are in the highly trusting group.

These numbers do not mean AI is unusable, but they reflect that getting code from AI and being confident that the code is correct are still separate matters. The more AI can generate code, the more important the ability to read code, verify logic, and know whether what AI created makes sense might become. Because if AI gives us 200 lines of code, but we don't understand what those lines do, deciding whether it is ready for real-world application will still be difficult.

Developers Might Not Need to Write Every Line Like Before

From another angle, saying that a good developer must write every line of code themselves probably doesn't align well with current software development practices anymore. This is because, in the past, we haven't been building everything from scratch anyway. We use libraries written by others, use frameworks, use packages, read documentation, find answers from the community, or use code created by others on the team. And now, AI has stepped in as just another tool in those workflows.

Therefore, having AI help generate boilerplate, write basic tests, refactor code, or help start some implementations does not automatically mean that developer doesn't understand programming. A more interesting question might be: After AI has written the code for us, do we know what it is doing?

If we can explain how this code works, why this solution was chosen, where the risks are, and if it breaks, where we should start fixing it, then not having typed every single letter of the code ourselves might not be the most important issue.

What AI Can Do Might Not Equal What We Want AI to be Responsible For

Another piece of data from the Stack Overflow Developer Survey 2025 also helps make this picture clearer. When asked about integrating AI into each part of the development workflow, respondents were particularly hesitant about highly responsible tasks. 76% stated they have no plans to use AI for Deployment and Monitoring, while 69% have no plans to use it for Project Planning.

This shows that while developers might be more willing to let AI help create or fix code, it doesn't mean they are ready to hand over every system decision to AI simultaneously. Even the workflow of the GitHub Copilot cloud agent itself is designed to allow developers to come back and review the diff, make adjustments, and decide on what the agent has done before utilizing it further.

Thus, the picture of the future might not be "Developer vs AI" as we like to question, but rather "Developer + AI," where each party takes on different roles.

So, Should Developers Still Practice Writing Code Themselves?

If you are someone just starting to learn programming, the answer to this question might differ from someone who has been working for many years. For beginners, trying to write code yourself is still a way that helps you understand the working process of a program, encounter errors, try debugging, and gradually see how the logic you write affects the program. AI can step in to help explain, point out mistakes, or propose solutions. But if we let AI generate everything from the start without understanding the fundamentals at all, when the code has issues, it might be very difficult to know where to even begin checking.

As for developers who already have a foundation, their way of working might change to another format. Instead of spending the majority of their time typing code themselves, they might use AI to help generate the first draft, and then dedicate that time to reading, reviewing, testing, adjusting architecture, or solving more difficult problems instead. Here, there might be no single answer that suits everyone, because each person has different levels of experience, workloads, and ways of using AI. But one thing that remains equally important is that we should understand what we are building.

Are Developer Skills Changing?

In the past, we might have judged a developer's fluency by how well they remembered syntax or how fast they could write something up. But in a world where AI can generate a large amount of code in a short time, what sets developers apart might gradually shift toward other skills more.

Whether it's explaining problems clearly, selecting the appropriate solution, understanding large codebases, reviewing code, debugging, system design, spotting edge cases, or deciding when to use answers from AI and when to inspect more thoroughly.

AI might help reduce the amount of code a developer has to type themselves, but that doesn't mean it reduces the amount of things a developer has to think about as well. Perhaps what is changing isn't that "developers will stop writing code," but rather the proportion of time we spend writing code compared to thinking, verifying, and decision-making.

Frequently Asked Questions (FAQ)

Will AI replace developers 100%?

Based on the perspective in the article, the future isn't about AI replacing developers (Developer vs. AI), but rather a collaboration (Developer + AI). Even though AI can help write code or build preliminary systems, we still need developers to understand requirements, design architecture, verify accuracy, and take responsibility for the resulting software.

If AI can write code, do beginners still need to practice writing code themselves?

It is still absolutely necessary. For beginners, writing code themselves is the process of understanding fundamentals, logic, and problem-solving (debugging). If you use AI to generate all the code without any foundation, you won't be able to pinpoint what needs fixing when the system encounters issues.

How much do developers currently trust the code written by AI?

Although developers are increasingly incorporating AI into their workflows, confidence in the results remains relatively low. Data from the Stack Overflow Survey indicates that many developers are still skeptical of AI's accuracy, and most are not ready to let AI handle high-responsibility tasks like deployment or monitoring on its own.

What skills should developers focus on in the AI era?

Developer skills will shift from focusing on "memorizing syntax and typing code" to higher-level skills such as clear communication and problem explanation, system design, code reviewing, debugging, and analyzing whether the code generated by AI is secure and suitable for real-world application.

Conclusion Do We Still Need to Write Code Ourselves?

Perhaps the answer to this question isn't simply "must write" or "must not write." Developers in the future might not need to type every line of code themselves as before, as AI can increasingly step in to help create, edit, and manage certain parts of the work. But at the same time, reading code to understand it, verifying what AI creates, making technical decisions, and being responsible for the software delivered are still parts of development work.

Therefore, the question might not be "Who types the code?" but rather "Who understands and can decide whether this code should really work this way?" What about you? If one day AI could write almost all the code for you, would you still want to write code yourself? Or do you think the developer's role is changing from "a person who writes code" to "a person who thinks, checks, and directs what AI writes" more?

Let's share our perspectives because there might not be a single answer for all developers. And for anyone who enjoys in-depth content and new perspectives in the software development world like this, don't forget to follow Superdev Academy. We have plenty more great articles waiting to be updated for you.