The episode, titled “We no longer pay developers to write code”, is available on the Underscore_ YouTube channel.
From AI experimentation to industrialization
About 18 months ago, Quentin started seriously experimenting with AI agents for software development. Initially skeptical, he gradually found that they could deliver certain developments faster, sometimes with a better implementation than the one he would have written himself.
But one of the main lessons from Clever Cloud’s experience is precisely that simply giving developers access to an AI tool is not enough. Adoption required changing practices, supporting teams, and even giving up on the idea of imposing a single tool: in a market evolving extremely quickly, developers experiment with different solutions and share what they learn.
When AI also transforms software quality
The focus then shifts from simply generating code to everything required to verify, test, and secure it. Unit and integration tests, distributed systems simulation, automated security audits: AI makes it possible to apply much more systematically practices that already existed but whose time cost sometimes limited their use.
At Clever Cloud, every commit in GitLab can be sent through simulation to look for failures, generate a report, and open an issue when a problem is detected. The question is therefore no longer simply, “How much code can AI produce?” but rather, “What organization and engineering pipeline do we need to build to use this capability in production?”
That is precisely what separates one-off experimentation from industrialization.
Rust, legacy, and new software development practices
The episode also explores Rust’s role in this transformation. Quentin explains why the language’s constraints and the precise feedback provided by its compiler create a particularly effective feedback loop with AI agents.
This approach is now part of a much broader project at Clever Cloud: reducing and ultimately eliminating the legacy accumulated since the company was founded more than 15 years ago, progressively rewriting components while preserving architectural decisions and strengthening their validation.
At the time of recording, Quentin still described eliminating legacy as a work in progress. Since then, this Rust rewrite is now nearly complete.
For a tech company of more than 100 people operating critical infrastructure, this goes far beyond a POC: it means fundamentally changing how software is designed, built, tested, and maintained.
What role is left for developers and CIOs?
This transformation ultimately raises a broader question: what happens to the developer’s role when producing code becomes significantly cheaper?
Quentin argues that value is shifting towards specifications, architecture, testing, and the environment in which software is produced. As a developer himself, he explains that it took him several months to come to terms with this shift.
For CIOs, this experience therefore raises the question of how to integrate AI without simply adding another tool to the stack, by rethinking the processes required to capture its benefits without sacrificing quality or security. This is precisely where Quentin believes companies focusing solely on code generation risk missing a large part of the potential gains.
Ultimately, this may be the main takeaway: the most structural gains emerge when AI leads us to fundamentally rethink how software is designed, built, and evolved. For European companies, the challenge is therefore no longer simply to adopt these tools, but to turn them into a genuine industrial capability.
To watch the full conversation between Quentin Adam, Micode, and Matthieu Lambda: