Copilot makes your devs faster, not more reliable

Copilot has a reliability problem that its headline productivity numbers do not solve. GitHub's 2024 study measures 35% more code written by developers using the tool, but that figure says nothing about the quality of that code once it reaches production. That is exactly the trap CEOs fall into when they budget for Copilot as a pure velocity multiplier.

I have seen too many purchasing decisions made on that single speed figure, without anyone asking the question that actually matters for a dev budget: who reviews what Copilot writes, and with how much experience. That question, not the licence price, determines whether the investment pays off or gets expensive six months down the line.

What Copilot really changes in your developers' speed

Copilot, GitHub's code extension powered by a language model, generates real-time code suggestions from what the developer types and the context of the open file. It works through completion (the "ghost text" that appears as you type), through inline chat to rework a specific block, and through a wider chat panel to discuss an architecture or debug an error.

On that specific ground, the speed gain is real and measured. According to a GitHub study relayed by itsystemes.fr, developers using GitHub Copilot write 35% more code over the same period. Be careful not to confuse the two Copilots: this figure comes from a study of developers and the GitHub Copilot tool, not from Microsoft 365 Copilot, the assistant built into Word, Excel and Outlook that the citing article also discusses. The two products share a marketing name, not a use case.

How exactly does Copilot speed up code writing?

The gain comes mostly from boilerplate (repetitive standard code with no business value): configuration, basic unit tests, CRUD queries, component scaffolding. A developer on the r/DeveloppeursFrance subreddit describes exactly this mechanism in a thread about AI productivity gains: generating a CRUD API or a Docker configuration in a few seconds instead of typing every line. The gain concentrates on the mechanical part of the job, not on architecture decisions.

It is a point I repeat on every staffing engagement: Copilot compresses typing time, not thinking time. A dev who used to spend two hours writing a CRUD module now spends thirty minutes. But the time spent designing the data model stays exactly the same.

Why Copilot's reliability is the real issue, not its speed

That speed gain comes with a downside most sales pitches keep quiet about. According to the same itsystemes.fr article, the controversies centre on the variable quality of generated code (subtle bugs, potential security flaws) and on a risk of AI dependency that erodes team skills over the medium term.

insideapp.fr, an agency that uses Copilot in production on mobile projects, is blunt on this point: Copilot "boosts productivity, but human validation remains essential to guarantee code quality and security". That is not a defensive disclaimer, it is real-world feedback from applications delivered to clients.

Which bugs does Copilot actually let through?

The risk is not the obvious bug a unit test catches immediately. It is the subtle one: a SQL query that works on the test dataset but breaks at real volume, error handling that swallows an exception instead of dealing with it, an access right poorly checked in an API. A Reddit thread on r/DeveloppeursFrance sums up the tension between immediate gain and skill erosion: developers who get used to accepting the suggestion without questioning it lose, over time, the reflex of checking what they approve.

This is where the entire gap between a junior dev and a senior profile using the same tool plays out. A junior accepts the suggestion because it compiles. A senior with at least eight years of experience knows when the suggestion hides technical debt (the hidden cost of poorly written code, which slows down every future change) that will get expensive in six months. The tool is identical, the delivered result is not.

The real cost of Copilot once per-token billing is factored in

This shift to usage-based billing completely changes the budget maths a CEO has to do before signing. The flat subscription (roughly €10 to €30 per seat per month depending on the plan) long made the decision simple: a predictable cost, easy to multiply by the number of developers. I broke down the exact maths of this shift to per-token billing in a dedicated article, because the real cost now depends on the volume of requests sent, not on a flat fee.

How much does a Copilot-boosted developer really cost?

The answer depends first on who is at the keyboard. The table below compares three staffing scenarios a founder or non-technical CTO has to settle before buying Copilot licences in bulk.

The most dangerous scenario is not the one you would expect. It is not the AI-free status quo, which is simply slow. It is the junior alone with Copilot and no review safety net: the apparent velocity hides technical debt that gets paid in full at the first scale-up.

Should you hire a junior on Copilot or delegate to an augmented senior?

This staffing question comes up in every discussion I see on the subject, in one form or another: should you hire to absorb the volume, or delegate the critical part to a senior profile already augmented by the same tools. On r/chileIT, a developer who recently joined a company describes exactly this dead end in a thread about measuring the ROI of AI in development: management wants to justify Claude Pro accounts already rolled out, with no clear method to link AI usage to measurable time savings on tickets that do not fit a clean project framework (support, documentation, debugging).

Full disclosure: Extra Dev places senior developers on contract at €180 a day, so I have an obvious bias on this question. That bias also comes from what I see on the ground across several engagements: a senior augmented by Copilot ships faster than a conventional team without the speed turning into hidden debt, because they know how to filter the suggestions a junior would accept without questioning.

« The real advantage of AI in development is not coding faster, it is building an industrialised production system around it. Without a clear architecture to frame it, generated code quickly becomes unmanageable, whatever the tool. »

Vincent Roye, September 2026

When does the reviewer's seniority matter more than the tool?

As soon as the code touches money, personal data, or a system already in production with active users. In those three cases, Copilot's speed becomes a risk if nobody experienced reviews every accepted suggestion. That is the point insideapp.fr confirms on its mobile projects delivered to clients: human validation is not a comfort option, it is the condition for speed not turning against the project.

For decisions that specifically concern offshore outsourcing or choosing an IT services firm over a senior dev hired directly, the GoLive Software blog digs into that ground in more detail. Extradev.fr stays focused on direct senior dev staffing, not on the offshore model.

The calculation that settles it: when Copilot is worth the investment

The calculation comes down to a single criterion, not ten. Copilot is worth the investment when a senior profile (eight years of experience minimum) validates every suggestion that touches business logic, security or performance. It becomes a hidden budget risk when it runs without that filter, even if the velocity dashboard shown internally looks excellent.

According to Gartner, the majority of enterprise generative AI initiatives fail to reach the expected return on investment within the first twelve months, for lack of having set the right measurement indicators before deployment. That is exactly the blind spot the r/chileIT thread cited above reveals: measuring AI usage without linking that figure to a delivered result proves nothing.

My verdict: do not hire an extra junior to "run" Copilot faster. First test Copilot on a limited scope with your most senior dev as reviewer for four weeks, measure the number of features delivered without regression, then decide whether to extend the licences. If your team has nobody with at least eight years of experience to hold that filtering role, delegating that review to a contracted senior dev costs less than the technical debt unfiltered Copilot will eventually produce.