"The companies that are using Copilot the most are also hiring the most. They’ve figured it out. They know Copilot makes their devs faster, so they’re scaling faster."
Gino Ferrand, writing today from Santa Fe, New Mexico 🌞
It’s become a kind of orthodoxy: AI boosts developer productivity, therefore you need fewer developers. Shrink the team. Cut the fat. Let the machines handle the boilerplate.
Except, quietly, something different is happening.
According to GitHub CEO Thomas Dohmke, the companies leaning hardest into AI tools like Copilot aren’t laying off developers. They’re hiring more of them. And not because Copilot failed to deliver speed gains. Quite the opposite. It worked. And when the machine started to deliver more output per engineer, the bottleneck moved.
Not to cost. To capacity.
The fastest teams saw it first. They weren’t thinking in terms of efficiency. They were thinking in terms of throughput. And suddenly, their problem wasn’t cost per line of code, it was how many features, experiments, or bets they could ship at once.
Productivity became a multiplier. So they scaled the input.
The Two-Track Reality of AI-Augmented Teams
This puts us on a collision course with the prevailing narrative. As recently as Q1 2025, we were seeing reports that entry-level software dev postings were down 38% from pre-AI peaks. CTOs were openly discussing hiring freezes, crediting AI tools for offsetting headcount needs.
And yet here’s Dohmke, from the cockpit of the platform hosting the world’s largest developer network, pointing to an opposite trend.
His data doesn’t suggest replacement. It suggests acceleration.
The best engineering teams are not automating their way to flat org charts. They’re compounding output. They’re using AI to do more, not less.
And that’s the unlock.
From Automation to Leverage
The developers who treat Copilot like autocomplete aren’t seeing this. But the teams that treat it like a junior engineer, like a collaborator, like a hundred tiny threads pulling code forward at once?
They’re realizing something different.
Each developer, when paired with an effective AI agent, becomes more than a unit of output. They become a node in a scaled problem-solving network.
More developers means more concurrency.
More concurrency means more feature delivery.
More delivery means more market experiments.
And that, in 2025, is the currency that matters.
So why does this matter for engineering leadership?
Because the assumption that AI will naturally reduce headcount is not a law. It’s a choice. A strategic one.
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Two Futures
In one future, you shrink the team. You “do more with less.” You slash hiring plans and count on Copilot to fill the gaps.
In another, you treat AI as leverage, not labor. You build systems around AI-augmented throughput. You hire for ambition, not austerity.
That second path is where the opportunity lies. It’s where engineering leaders start thinking not just about delivery, but about velocity curves.
It’s also where nearshore AI-fluent teams become crucial. Not just because they’re cost-efficient, but because they extend your ability to scale without latency or bloat.
The Real Question
The question isn’t “How many devs can I cut?”
It’s “How many devs can I activate with AI and turn into a strategic force multiplier?”
That’s a very different game.
And it’s one that GitHub’s own CEO believes the winners have already started playing.
More to come...
Recommended Reads
✔️ AI will boost recruitment of developers, not replace them: GitHub CEO (The Economic Times)
✔️ GitHub CEO to engineers: “Smartest” companies will hire more software engineers, not less… (The Times of India)
– Gino Ferrand, Founder @ Tecla