points by marcyb5st 3 days ago

I think you are assuming cost per task will become cheaper and that there is unlimited energy supply.

While tokens costs are going down, the number of token burned is going up and up. Case in point Sam Altman is complaining about their top token users burning through 100B tokens per month [1]. So you have token prices going down but token usage going up 10x per year (if you extrapolate linearly from what Sam was ranting about). This is happening because people trust more and more LLMs and give them more autonomy and more complex tasks (IMHO).

So if you really need a true unsupervised agent that replaces SWEs you need how probably much more than that. Say 20x that number (2T tokens/month) for each SWE. I'm gonna focus on the energy part as this is more tangible. Trying with some realistic numbers:

- To replace 1M SWEs for a year you need 2T tokens/month * 12 months * 1M SWEs ( = 2.410^19 tokens)

- Assuming 0.5J per token you get 1.2</i>10^19J [2] (I took the number for an llama3 8B model, probably is much more for SOTA models IMHO).

- A year has 31M seconds

- Over a year that is 380 GW of constant power that is needed only for replacing 1M SWEs and that is around 80% of all the current US energy consumption (450GW). And apparently there are 47ish Million SWEs globally as of 2025 [3]

I don't think there is enough power capacity to deliver all of this without pivoting all of society into building data centers and power plants.

So unless there is some breakthrough in efficiency/intelligence (ie you need way fewer tokens for what you have to do) your job is gonna be safish at least.

Of course I pulled that 20x out of my ass, but I believe it is somewhat realistic for a truly autonomous agent(s) that replace SWEs.

[1] https://finance.yahoo.com/sectors/technology/articles/sam-al... [2] https://arxiv.org/html/2512.03024v1 [3] https://www.slashdata.co/post/global-developer-population-tr...