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In the digital age, new technologies are emerging at a rapid pace, making artificial intelligence (AI) an omnipresent topic. While it promises considerable advances, its integration — particularly in software development — still sparks controversy. At Maarch, we’ve chosen to integrate AI as a development support tool within our R&D teams.
But how can we make sure this tool is used securely and managed properly?
To answer this question and detail our approach, we interviewed Nicolas Le Bozec, junior backend developer. In this article, he explains how AI is actually used within Maarch’s R&D, with a focus on internal security and the rigorous management of this technology.
Interview with Nicolas Le Bozec
Can you explain what AI is used for within Maarch’s R&D teams, and how it fits into your work processes?
First of all, you should know that we use the JetBrains¹ development tool, specifically PhpStorm². That’s mainly true for us as back-end developers. An AI licence is built in, which lets us use different models such as Claude, Gemini, ChatGPT and others.
We use AI in several ways. First for ideation: we can ask it to suggest implementation examples for a piece of development work, which helps us picture a possible approach.
AI also helps us fix bugs. If a piece of code isn’t working, we can ask it to identify what’s causing the issue and where the error lies. And if we want to go further, we can even ask it to run a failing unit test to analyse the root cause of the problem.
Today, all of this is far more automated than before, when AI was limited to generating text or answering questions.
AI can now carry out certain tasks on its own, but that’s still a work in progress. In R&D, we mainly use it to have a dialogue with it, not to let it modify the code directly, because that could create security issues. It could change something without us wanting it to, or without us even noticing, which would be risky.
Our real goal is to stay in control of the code and of what gets done. For now, AI is therefore used as an assistant: it supports us in our development work, helps us get unstuck in certain situations and lets us be more efficient, in particular by going straight to online documentation to find what we need. It’s a real time-saver when it comes to research.
Which tasks does AI save you the most time on day to day?
In practical terms, AI mainly lets us move faster on our development work. We can take on more tickets per sprint, because we’re more efficient at solving problems. Blockers that would have taken us a long time to analyse can now be identified much faster. We still own the fixes, but AI helps us pinpoint the source of issues more quickly.
For developing new features, AI also saves us time. Since there are so many different files, it helps us quickly identify which one we need to work in, without going through a lengthy research or thinking phase. By analysing the project structure, it can even help us sort or spot the relevant files more efficiently.
Beyond these uses, are there other tasks AI can help with today?
The tasks mentioned earlier are clearly the « safest » ones. AI can now generate code, meaning it can modify existing code directly, but since this is still very new, it’s risky to trust it completely. It still makes the occasional mistake.
What are the risks or limitations to consider when giving AI a bigger role in the code?
It raises ethical questions, since it could gain access to the entire codebase³, including environment files containing private keys or other sensitive information. So giving Artificial Intelligence full access doesn’t strike me as a very good idea.
Right now, it can modify pieces of code, but it needs to be restricted — for example, by telling it: « you can touch this file, but don’t go looking in the others. » It has to be limited and kept under control, because otherwise there can be major incidents: data leaks, or changes that could let a hacker access our systems and leak code. You have to be very vigilant when using AI, and that’s exactly what we do here.
You mentioned security concerns and the need to restrict AI. In practical terms, how do you ensure it only accesses authorised information?
We can see at all times which files it’s browsing and everything it’s doing — everything is kept under control. Internally, we mainly use conversational mode: we simply point it to the file we want it to work on. That way, we know it won’t go anywhere else, since it can only see that one file. We can even ask it to look at just one line of code or a specific element.
It only starts browsing other files if we explicitly ask it to search for a particular element in the code. In that case, it first analyses the file names to find the one matching the request, then reviews the code and chains together further analysis. Step by step, if it isn’t restricted, it could potentially end up accessing private keys or sensitive information needed for local development.
Do you think AI could eventually replace the developer role?
For my part, what I mainly do with AI is research and development. I run tests, try to see what works best, and look at how we can improve our working conditions to be more efficient…
I don’t think AI can fully replace developers, but it’s clearly transforming our profession. Today, it’s a bit like having a companion supporting us across a large number of tasks.
From your point of view, how is AI changing the developer role, and why do you think it won’t replace human expertise?
I think a developer today needs to know how to use AI and stay informed about the latest developments, because that matters — if only out of personal curiosity. That’s also the direction the profession is heading in.
I don’t believe AI will fully replace developers, at least not those who know how to use it. When you’ve mastered the tool, stay alert, and don’t let yourself get pulled into the risk of dependency, AI remains above all a tool for efficiency — one you need to keep an eye on.
That said, I understand why this might worry some people. Given how fast progress is moving, you can wonder whether, for cost or strategic reasons, some companies might be tempted to cut positions. But it really depends on each organisation, and some might ultimately realise they need to backtrack.
Before AI became part of your daily work, how did you go about researching documentation and technical solutions?
Before, we’d simply go to Stack Overflow to find people who’d run into the same problem as us.
How did you end up becoming, in a way, the AI go-to person within the R&D teams?
It’s very simple: I love new technology. I love discovering things, testing them, finding out more. Since AI was one of the emerging technologies when I joined Maarch, I got interested in it right away. I started using it, running tests, realising it could generate small code ideas, and I talked to my colleagues about it to explain its usefulness and how it worked.
Bit by bit, as AI kept improving, I carried on talking with them about it. I kept them updated on what I was discovering — the different AIs, French, American, Chinese — and everyone gradually started taking them into account, working with them and developing with them, until we decided to get JetBrains licences.
Today, AI is part of our everyday work. Since I keep myself informed about new developments, test what comes out, and think about what can or can’t be integrated into our working environment, I naturally became the team’s AI go-to person.
Definitions
¹ JetBrains
JetBrains is a company specialising in development tools, known for its powerful, intelligent working environments (IDEs). Its software is designed to help developers code faster, better and with fewer errors, thanks to advanced analysis and autocompletion features and, now, built-in AI.
² PhpStorm
PhpStorm is JetBrains’ IDE dedicated to PHP development. It offers a very fine-grained understanding of code, ultra-fast navigation, built-in tools for debugging, testing and managing complex projects, and native AI integration to support developers in their day-to-day tasks.
³ Codebase
A codebase refers to the entire source code of a project. It’s the technical foundation that brings together all the files, folders, modules and resources needed for an application to run. In short: it’s the heart of the software, the place where all the functionality lives.
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