Worth also noting that this chart has the bottom of the Y-axis cut off, exaggerating differences and making visual intuition basically useless.

Wow. Huge crash between 2022 and 2023, from 230 to down around 80. Why? That's the real question. What happened? It's post-COVID.

Then stuck in the 60-80 range since 2023. The sample period chosen by Citadel is wildly deceptive.

This is an important question and these crap stats are not helping.

Interesting chart that confirms hiring dynamics for SE have not much to do with AI despite all the PR, as in 2023 models and agents capabilities were quite limited, and now that capabilities increase hiring is picking up. I hope more journalists will start to challenge that narrative.

Click "max" to see its the corona peaks that's the outlier.

Wow, that says a lot with data. Thank you.

"Whole chart"

Graph starts with a black swan event

Indeed scrape a lot of places looking for jobs. While they don't get a lot of the startup scene, it's a better metric across the economy.

Is it not just the same as when people suddenly started having "an ask"? It is some kind of in-group speak that it is important that you adopt just to show that you are with the times.

I believe this wording originates from references to a Stock Ticker machine and the Ticker Tape which would "print" the "latest" values of stocks, interest rates etc.

I'm not sure whether it's AI spam, or somebody at an investment company who actually writes like that. It's an exaggerated version of the style in McKinsey reports.

They're addressing a very important question, and one for which there is surprisingly little hard data. It's too soon to try to see a trend from low-quality data. Three years of this data might be meaningful.

I don't work in IT but I use and love Claude code. What strikes me is maybe the overall software job market can not grow to surpass the post covid peak but any current professional software engineer has immensely valuable skills that can no longer be gained in the same way, if at all. I would think the counter argument to the greedy CEO argument is that AI breaks the former economy of scale in the opposite direction towards hyper specialization in business with small teams. In that scenario, as the economy grows with more and more business, the current software engineers are the substrate for a new type of off brand bargain CTO as opposed to the current , luxury brand CTO sitting at the top of oversized companies.The bull market becomes at the higher level that current software engineers step into. Most likely though, none of this is true and 15 years from now it all shakes out in a way that none of us could have really predicted from our vantage point because the prediction would sound ridiculous with the information at hand.

Computing cost and reliability remains the bottleneck. AI agents are nowhere near smart enough to carry out tasks on their own. Combined with the fact, 95% of gen-AI pilots "failed" [1], at least failed to improve the bottom line. Layoffs were never about AI, they were almost always about capex, and correcting the pre-2022 overhiring. All CEOs are hearing in 2026, "I didn't get anything done, but the model hit the limit".

However, if there will be, locally deployable, meaningfully capable AI models that can change the computing cost equation.

[1]: https://www.forbes.com/sites/jasonsnyder/2025/08/26/mit-find...

It really depends on how you define a software engineer. If you mean software engineers doing what we do today, the market probably won’t.

If you just mean “people who make software in any capacity”, it will probably grow (or has already grown) via product, marketing, etc folks making internal tools with AI (which may not work out, we’ll see).

Presuming we keep seeing LLM improvements, SWE will move up the stack like they did in the past. They used to work directly with hardware and software. Ops folks sprung up to do the hardware, and SWEs do basically all software using abstractions over hardware. This will be another step up where SWEs no longer work directly on software, but rather on the tooling that writes software which they hand over to marketing, HR, etc.

Again, presuming this all works out the way the AI folks plan.

The world runs on software. AI makes it easier to create more software, but it still requires humans to keep running and decide what to do. Maybe each individual project will need less pure coders, but there might be a lot more projects?

As long as software engineers are needed to leverage AI (they can manage the output, refine the prompts, check the BS), there is plenty of software to write and not having SWEs still means you will have to write less of it.