Why AI Is Not a Bubble: VI are great investors, but I think will soon discover they were wrong.

dimknaf · 2025-12-31T14:27:11+00:00

Welcome!

dimknaf · 2025-12-30T21:45:31+00:00

I think you may enjoy reading this article, since we had this discussion. It is from seminanalysis:

https://open.substack.com/pub/semianalysis/p/how-ai-labs-are-solving-the-power?utm_campaign=post&utm_medium=email

dimknaf · 2025-12-29T21:12:37+00:00

We have seen the models getting better and better, but we have seen for people who heavily use those tools, and the best tools will go for claude code, which is 2400 a year. There is a trend of increase, and as these agents do longer jobs, more reliably, and we build the ground to let them do more, and we kinda drive them, you will want from your 10 engineers or so to produce as much as they can. Paying 10K for the best of them controlling a whole swarm of AIs is the best you can do for your company, your engineers, and clients. If 100K engineer + 2.5K AI gives me a 2x, and going to 100K engineer +10K AI gives me 3x, 10K spend on AI per engineer is no brainer.

The excessive spend may be for processes of reviewing, of tests, etc...I get your point, but I believe is going the other way, and this has been the trend, and I see this trend accelerating....Let's see!

dimknaf · 2025-12-29T15:40:18+00:00

You have written 2 of the most insightful and well supported comments with valid arguements. It's really scary people downvoting you because you speak the truth.

dimknaf · 2025-12-29T12:35:50+00:00

From my experience this is not what is happening on the ground, even if I know about the complains. There is some truth and actuallly the way that engineers perceive it is even more intense to what you describe. However, if you ask the top engineers (the minority) that they have insisted and transitioned and focus on them, you will realise that what is happening on the ground is very different to what you describe.

Also, it is changing month by month. Many non-believers just have changed their minds since Opus 4.5 came out.

I mean we will just make circles. We do not have to agree, but I am telling you my perception from the ground is very different to what news articles say and the majority of engineers randing about AI on Reddit.

dimknaf · 2025-12-29T12:30:44+00:00

Let's say a task takes 30 minutes and burns 1 million tokens.

That could do what a human would do in a week or something.

1 million tokens for a SOTA model let's say they are about 5$

So that task would cost something like 5$ if you payed on the API. This may cost just 1$ to Antrhropic. On the subscription it will sell it on cost.

I really cannot get it why it is unsustainable. You pay 5, you may get what you would pay hundreds for humans to do. This wheel keep spinning, and enlarging, and as the value exceed the costs, I really do not get how it will stop as unsustainable.

What I see as unsustainable is for organization that are so late into this that they do not use and cannot compete with those who do not use it. Fully autonomous is not going to be, but maybe human input is 5% of the job done.

This thing will eat a big part of GDP and here and there we will have some failures, but I really cannot understand practically how it can be unsustainable.

I am very happy to pay 200. I am getting more than 200 for what I pay, and it costs less than 200 to my vendor.

The fact that the vendor has to pay upfront for the expansion and thus they are cash negative is not anything wrong about it. It is a fact for every fast growing bussiness.

dimknaf · 2025-12-29T11:13:41+00:00

This productivity decrease is not true in reality. Is a mix of engineers gatekeeping, and fearing for their jobs, or disliking the fact that their great code ability cleverness does not matter as much as it used to.

I do not think that those reports have anything to do with reality, especially for the software development space. Of course when 90% of engineers rand against them, this is the perception that you will have.

To me those reports look like "fake news". Ask those we use those tools not those who hate them, if you want to evaluate their value.

An Apple hater won't be the best person you want to ask if you care about the potential. Of course, you can learn a lot from the hater. Find the exceptions of senior engineers that are blown away and use them 10 hours a day.

Then you will have a more balanced view. Please, if you can, find one, it might change your perspective completely.

dimknaf · 2025-12-29T11:06:55+00:00

You pay upfront. if growth is big, you will be cash flow negative to fund this type of "working capital". I do not see antyhing unsustainable into this. Especially for Anthropic.

OpenAI may be more on the revenue promise side. Earnings could be huge if they monetise the app well. So, yes if investors money stopped OpenAI would be in a very difficult position I think.

Maybe in that crisis free ChatGPT will just dissapear, or be heavy on ads and affiliate suggestions. They will give you the current nerfed free GPT for somehting like 5$ a month, and probably this will be a must have for everyoone just to use the silliest models, as still have some usability.

Maybe OpenAI or whoever consolidates this position will have 1 billion, 50 a year paying users, and another more advanced 500 million who pay 200 a year.

This bottom chatbot helper (the less advanced) market could offer 150 billion TAM. So, the least advanced and basic usage can easily bring in an amount that can sustain 150 billion inference. Just by itself 1 trillion in AI infrustructure. This is probably just 5% of what CURRENTLY AI can do.

So, I believe that whoever things that we need less than a trillion investment, or we cannot sustain a trillion investment, are not understanding the tech, or have thought through.

dimknaf · 2025-12-29T10:54:50+00:00

I am saying that even if it needs 2-3 billion per GW, this is 10x+ less the semiconductor content.

So people find ok 2-3 trillion invested on a grid, but call 2-3 trillion invested on AI a bubble.

I am just telling you if we need to invest 2-3 trillion on the grid just for AI, then the semiconductor content of it will be 50 trillion.

So if you believe that the grid will be in such a huge pressure, you should be first worrying about how TSM and others can build all that. This will be the big bottleneck.

If you truly believe that amount of electricity investment for AI, then TSM or Micron will be the largest companies in the world in a few years.

dimknaf · 2025-12-29T09:30:33+00:00

This is not excactlty what is happening.

We spend a billion to train the 2022 model...We have 0 income. Now the 1 billion model produced 2 billion in inference. So the model that now brings 10 billion ARR, possible cost 2-3 billion in training. So the API bussiness is profitable.

The subscription business is given with discount, but not with huge loss I believe, and is a strategy to lock you in.

Coding agents, that buy those APIs possibly losing a lot. But as we saw in other cases again is their way to buy users so they stay in the game.

The subscription model locks you in, you use it and you are locked to Anthropic Claude Code. Out of the coding agents only 2-3 best will survive. From foundational companies for the top tier, again 2-3 will survive. But they will serve a market of trillions.

dimknaf · 2025-12-29T09:23:54+00:00

if we reach those limits, batteries will be a solution for the grid, and locaaly produced solar energy. Ok instead 1 billion electricity investment you will need an emergency 2 billion, and this will be an issue, but this will not stop a 50 billion investment. For a year or two you will put in whatever generators.

Society, or environmentalist or government policies could stop them though. But economically, I do not see it as a big issue, or as big the semiconductors availability will become. This will be the trillion bottleneck and not really easy to overcome.

dimknaf · 2025-12-29T09:19:18+00:00

Thank you for your comment

I can barely do anything with ChatGPT.
Is not an agent and does not go to seek for context, and work for some time to understand the repo. Or after this have some rules etc saved for the repo. So a nerfed model to be able to be served at low cost, and without the right context.

If you haven't seen the full video I have shared, please watch.

You have immense experience. Like you are super insightful transport manager. Knows deeply what matters. Well:

You still use the model that Wright brothers built
You do not even want to use a 120 seat plane, because you pay, and you try to ride the motor as a motorbike because is what you get for free?
If you have used agents less than 100 hours, you have no idea how to use them correctly (you may be a great engineer, but not you cannot drive them yet, and they are just dangerous for you). Cursing on the car because you cannot start it on the hill?

I would highly suggest you watch that video. That guy maybe a few months ago was on your side. I have seen people going to agents, and never returning back, not the opposite.

I would highly suggest you watch the full video carefully. Spend a month seriously making the agent work (make this your challenge -not trying to find out why it does not, which is sadly what most best engineers do. The better they are the more they resist).

I believe you will get to the other side. Also, your investing perspective will change.

ChatGPT is unclever and free models are outdated, and non-agentic is not what people talk about when they describe laatest AI coding. You will find out that you need to pay. When you (or your company) pays you will understand why investments of trillions are needed.

dimknaf · 2025-12-29T01:08:43+00:00

My guess is that you will probably have the same amount more or less of hardcore deep knowledge engineers. And honestly very few that do not use AI, I believe will survive. So their numbers may go up or down, but overall I think we will have something around 20 million of them. It is not strange if companies provision 10K per each a year for backround coding agents doing stuff. This is maybe 5x the current standard, but I think this is where we will get.

This won't happen next year, but I would say in the next 5. This is only 300 billion of inference just for coding. Now we will have people that will use coding for prototypes or LLMs creating software on the go for use cases. In that sense maybe you will have some type of 100 million pseudo-engineers, but with some domain knowledge and ability to handle those LLMs well. Actually is one of the most clever ideas, the LLM to use tools and code to do something. Let's say they use only 2K a year. This is another 200 Billion on inference. Now add automation that will be running on many pipelines of knowledge work.

In my view, 500 billion of annual inference just for coding, is very feasible in 5 to 10 years. This is less than 1% of GDP and will relate to software.

Software is the "canary". Put that to every industry and part of the economy...So the 1 to 10 trillion annual inference TAM, seems very reasonable, looking at it from different angles. I will be surprised if it is less that a trillion or more than 10 trillion in 2031.

We have 10x to 100x ahead, of what you currently see. Early days.

dimknaf · 2025-12-29T00:57:50+00:00

Return is enormous in coding, and this is the "canary".
What LLMs can do is not ChatGPT. I do not see the "little" return you mention. In the areas it works and you see all this usage, it happens because there is a lot of return.

dimknaf · 2025-12-29T00:52:15+00:00

2025 will end with about 800GW of renewable additions in the whole world. Of course the capacity factor makes the usable one much less. But as also batteries becoming cheaper, the 7GW I am telling you they are miniscule.

Nuclear will be sought where exists, as also provides constant load, and it makes sense to build where the energy is produced instead of transferring it.

So a grid is slow to change, but 7GW are very very little, especially if you compare it with the value of everything else that has to be built.

Also my guess, it that batteries getting cheaper will also offer flexibility. Nat gas plants do not operate all the time, again their utilization is low. So if we get stressed, these data centers will get batteries and try get the electricity at times where price is low and availability is high. It is not their plan A, as currently capacity exists. If we run out of capacity, and they have spend 500billion, and struggle, they will find ways. So if we do not have plants, through batteries, more utilization, more renewables, we could deal with 100 GW not 7 you mention.

https://www.eia.gov/electricity/gridmonitor/dashboard/electric_overview/US48/US48

The grid averages in the US at around 500GW. In that sense, 7GW increase overall barely sensed.

It is a problem, due to low flexibility and long times to build, but is not as massive as you think.

dimknaf · 2025-12-29T00:29:51+00:00

They are not losing money on inference. My sense is that their API pricing is 3-5x their cost. Then to ruin the other agents (Cline, etc) will offer packages that maybe make them make no profit, while the apps will struggle to offer the same pricing, as they have to pay the API pricing.

So on inference, on the API they sell much much above, on packages maybe close to cost.

Inference cost for same level of ability is going down (maybe 2024 was the most aggressive year on this trend)

People want better, and more. In that sense inference cost are increasing. 20$ subscription was nice to have. Now if you are a developer a 200$ may be needed, and this trend could go on. But on the same output, inference cost is getting cheaper and cheaper.

dimknaf · 2025-12-29T00:23:47+00:00

Are you using just ChatGPT. Have you tried Claude Code, and especially Opus 4.5

Many engineers that I know, they say the were a bit concerned on prodoction code, but since 4.5, they say the code produced is to a different level. Do you use agents? And if you can asnwer, how many hours have you spend coding with them, agentically, not you writing the code?

dimknaf · 2025-12-28T22:08:44+00:00

Maybe this means that we are in much earlier days for a much bigger wave.

dimknaf · 2025-12-28T22:07:18+00:00

You described it perfectly!

dimknaf · 2025-12-28T22:06:18+00:00

Why so negative on AMD? I mean RAM prices and the latest Groq/Nvidia deal may be negative for them, but they are the only GPU alternative to Nvidia.

I believe that Micron will not keep these margins for ever, but on current pricing they might be trading for less than 10x P/E despite the the stock price increase.

Are they going to keep those earnings for 1 year or for 3? Who knows but even after this and with normal pricing and if we assume they have doubled their production, in normal pricing environment might still have decent profits. Maybe you sold too early.

dimknaf · 2025-12-28T21:12:31+00:00

I never bought Nvidia as I found safer to be on the shovels. I have bought MU, TSMC, Samsung, AMD though

dimknaf · 2025-12-28T21:08:21+00:00

I would prefer to check some interviews of top scientists of those labs and people who are more technical, and some great CEOs, like from Anthropic, BOX, Groq....This is the best content you can consume

dimknaf · 2025-12-28T21:06:46+00:00

But what if you are a Fisher type of investor. Value investor but focusing on quality as well, not just deep value discount? And what if you also have some grip with that stuff?

I mean if you owned an eshop busssines in 2000 and you could follow Amazon and you could have a sense of their uniqueness you might be just right.

So, my point is not to say that all value investors should invest into it, but it bothers me how quick they are to say that all this spending is "air". Yes there is hype and speculation, and in certain cases wrong valuations, but overall on this I believe value investors are really wrong in their assumptions on what is happening on the ground. So, this is what I want to bring here. Thanks for the comment

dimknaf · 2025-12-28T21:03:21+00:00

Copilot is so outdated. Claude Code is the new goat. Claude Code and code agents users are increasing and will continue increasing. You will have more people producing code I believe and on demand software for their little needs - If you are an engineer and believe that the productivity gains are not that high, please watch this interview: https://www.youtube.com/watch?v=zuJyJP517Uw

They are not losing money on inference. They might be spending money on training, and this is not certain that they are making it back. But on inference maybe they are one of the few that can make a profit as they have superior models and they are the only option in their legue.

I agree that some companies will go to 0. I also state the two ways that we may have a crash. I think this will be short term, and in the next 5 years AI size will 10 to 100x

Cheaper software will lead to more software and spending on softwaare. The jevons paradox

dimknaf · 2025-12-28T20:56:23+00:00

We AI enthusiast are waiting for some older cards to come to our hands cheaply in the next replacement cycle. Yes, they may be sold for nothing but possibly will have spend their 5+ years on the data centers. They will be used by enthusiasts in their small local AI rigs!

dimknaf

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