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The Code Canaries Are Singing — Our Path Toward AGI
How the fate of human software developers reveals our path toward AGI
You may have heard, humans are going out of business. First on the list: software developers.
As of today, there are nearly 30 million software developers in the world. I couldn’t believe it, but actually, the numbers have been steadily creeping up at single-digit growth annually for decades now.
Then again, more recently, software jobs in the US have actually been on the decline since COVID-19 and don’t seem to be reversing based on the stable trend.

Given that ChatGPT only came out long after this downward trend started, it’s not yet driven by AI. It's more likely caused by efficiency-seeking corporations moving American jobs to lower-cost remote offices in India.
In terms of AI impact, various AI tools such as Github Copilot are already being used by most developers. The only question is how much value is being added. Sam Altman says 300%, some say more like 3%. The median is probably closer to the latter, but those magic moments where the thing you want just magically appears and works on the first go are possible today.
Sidebar: Why pick on developers specifically? Well, somehow it just turns out that LLMs take to code like a fish in water. One theory is that code is like language, but not as messy. Less irregular verbs, as it were. So it’s inevitable that automating the developer is the first clearly defined target for the road to all-knowing all-capable AGI. Coding ability and quality is also easy to measure with dedicated benchmarks. So it’s the perfect testbed for AI labs.
Given the salary cost of 30 million developers is pretty high, this is a trillion-dollar opportunity for AI companies. Copilots are cute, but agents are the dev killer. For a moment, everyone thought Devin had cracked it. But here we are, still waiting months later. Others, too, are trying.

Recently, Factory AI set new a high score on the popular SWE-bench benchmark with their Code Droid system. Why is…