Software's centaur age may last decades

We are currently living in the age of centaurs (2022-20??). Right now, human engineers paired with AI coding systems are more effective than either by themselves. For future generations of software engineers — human or otherwise — this will be the most significant fact about the current period.

As in chess’s own centaur age, people are always ready to claim that the centaur age is over and the age of AI supremacy has begun. But the age of centaurs in chess lasted about twenty years, and previous centaur ages have lasted far longer.

This should be encouraging to many of us. If software engineering goes along similar lines, we may be able to ride it out another decade or two: enough to make serious plans about what comes next, or to finish out our careers entirely.

A brief history of the centaur age

It began with GitHub Copilot, which launched in 2022 as AI-powered autocomplete. A confident engineer who knew exactly what they wanted could tab-complete their way through lines of code and sometimes entire functions. Being able to chat with language models like GPT-4 provided the next upgrade. Although the models would still get things wrong, it was helpful to have a generalist on tap for areas that were a complete mystery.

Coding agents rose to prominence with Cursor’s “agent mode” in 2024 and Claude Code in early 2025. Early agents needed close supervision to prevent them from going off the rails, but were still helpful to automate straightforward tasks. Current agents — after the November 2025 release of Claude Opus 4.5 — are reliable enough to run entirely unsupervised. Their output still needs human review, but the kind of mistakes they make are more mistakes of alignment than regular bugs: not matching the organization’s technical values, over-engineering certain areas and under-engineering others, deciding where to spend effort, and so on.

It is no longer possible to credibly argue that an unassisted software engineer can beat a centaur team. The value provided by coding agents is just too great: not just the speed of producing code, but the speed of review and testing. However, we are not yet at the point where an unsupervised coding agent can beat a centaur team either. All the impressive work I’ve seen from LLMs has had a competent human software engineer in control. Centaurs are on top.

Will software’s centaur age be shorter than chess’s?

Would we expect our centaur age to be shorter? On the one hand, chess is a much simpler problem than software engineering, and is more amenable to learning methods like self-play.

On the other hand, software engineering is massively more lucrative to solve, and many orders of magnitude more funding is being plowed into the problem than was with chess.

On the third hand, “solving” software engineering means creating much more software, which increases the total work-to-be-done, so even if the relative human share of that work is shrinking, the overall amount of human work might grow.

On the fourth hand, the level of generally-capable AI needed to address software engineering will have huge effects on other fields, the ripple effects of which are likely to negatively impact software engineering jobs (for instance, crashing the economy, widespread social unrest, and so on).

On the fifth hand, we might think that chess had an unusually fast centaur age. Previous centaur ages lasted much longer. In knitting, where a human and a knitting-frame could outcompete any hand-knitter, the centaur age lasted two hundred years. On the sixth hand, technological change is moving ever faster.

I could probably find a seventh, eighth, and ninth hand if I wanted to¹. But overall I think we have no real idea of how this is going to turn out. Chess is the most recent example of a centaur age we have, and it’s attacked by the same AI-based forces of automation as software is. It’s thus reasonable² to make a default assumption that the length of software’s centaur age will be similar to chess’s.

Living in the centaur age

Suppose I have convinced you that human-AI partnerships will be the dominant force in software engineering for at least the next decade. What then?

Don’t quit! Don’t give up on software engineering and go become a carpenter, or open a cafe, or try to get a retail job. Unless you are somehow really, really passionate about doing those things, it is going to suck: unrewarding, grueling work that you are not good at. A decade of software engineering work is long enough to take your time and think seriously about your next steps.

Lean into the partnership. A guaranteed way to fail in a centaur age is to refuse to become a centaur. The idea that AI is a passing fad was a reasonable position to hold in 2023, but we’re way past that now. The AI financial bubble popping will not mean the end of AI. It’s here to stay.

Think hard about what value humans can still add. This is going to change over time, and getting it right is the difference between being an effective (and employed) centaur and being a meat proxy. In 2023, technical expertise was the primary source of human value. Today, I personally think it’s going to come down to alignment, but this is still early days. I’ve also seen arguments for taste, though it’s hard to define that non-circularly. We need a lot more engineers thinking through this problem.

Don’t panic

It’s a common fear response to try and skip ahead to the worst-case scenario. But those of us working in the age of centaurs should avoid that. We need to think about how the job of software engineering functions now, not how it might function in twenty years when AI has completely transformed the landscape.

People are too quick to declare that we’re in the software engineering apocalypse. We can certainly see it from here, but we’re not there yet. The spectre of full automation can loom on the horizon for decades. If you panic and jump ship early, you could be giving up on an entire normal-length career.