[marcyb5st]

I am pretty familiar with a 500k LOC codebase. If for every feature request/bug the agent has to go through a lot of it, spend a gazillion thinking tokens for understanding what it needs to do, plan, and then execute (assuming it gets it right) given the current cost of tokens I argue I am often more cost effective.

In fact, I believe that the most cost effective way is a collab of human+agent. Ie giving the agent direction as it goes along with the plan I can cut the thinking while keeping the speed. Basically helping the agent going from a breadth first search into a guided depth first one which is much more token efficient.

Additionally, humans have long term memory and knowledge of the context around your codebase. Agents do not, and while you can fit a lot in 1M context window, once you fill that the quality goes down considerably.

[stnikolauswagne]

Not to mention the fact that even the most well documented codebase will have documentation blindspots about real-world concerns or limitations that LLMs cant know about. Cursor yesterday tried to remove a document format from the codebase because it was convinced that it was non-existant, turns out that not only does it exist and is vitally important for our shipping process, but also the API it comes from does not document its existence at all.

[bayarearefugee]

This is why you can't be replaced today. I'm not sure you can rely on that remaining true for very long. And this goes for the vast majority of us.

To be clear, I'm also not saying LLMs will definitely displace a lot of us very soon. I'm just saying I wouldn't be surprised by either outcome and I don't know how anyone claims to know one way or another given the past year or so of progress.

[stnikolauswagne]

Im curious if that point comes before it automates away the entire mid-upper management caste.

In a hypothetical world where LLMs have enough context window and "understanding" to have no need for an experienced user to give inputs I would assume its also going to have enough information to make most business decisions and provide well formatted info to the C-Suite.

[marcyb5st]

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 1.210^19J [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...

[ben_w]

> - 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 think the economics here work out as "OK, so we've bought 80% the electricity in the US and used this to sell software to the 96% of humans not living in the US; this is profitable for the businesses, so nobody with money cares about the Americans who now literally can't afford to keep refrigerators running because we outbid them".

[Chrise_N]

Okay. You win.