nemo44x

We are going to have so much high quality furniture.

We actually do have standards for some software engineering. Claude isn’t writing anything that is life/death critical.

Static analysis for example. Although I’ve heard that LLMs can now do that if a user wanted it.

Everything Anthropic says absolves them of responsibility and is self serving.

We are living in such a weird, amazing, and miraculous time. It’s completely surreal.

Yes. And yes you can churn slop. And I’m sure many will and many will get stuck with a source base that grows bigger than LLMs can cope with and becomes unmaintainable.

But you can also have many engineers operating it, testing outputs like you would in a real factory, etc.

Will be interesting to see how this pattern evolves. If it even makes sense.

> At the same time, we'll keep helping people focus on the work that matters most, build new skills, and, where it makes sense, find new opportunities across Microsoft.

Anthropic is already doing this - some software engineers have redeployed into research roles, for example. “Redeploying” is going to be the latest HR trend I think.

The calculus may be that DeepSeek (or similar) + human is good enough and that the frontier simply won’t have the growth to get to the next level that differentiates them and justifies the token cost. They get stuck in a race to the bottom which is opposite of what they want.

The $100/month guy for inference isn’t the prize. It’s the thousands of companies spending millions/month.

It’s not unusual for someone to spend $5k in a week. 2 guys at my place just spend $150,000 over 3 months building out a factory.

We are aggressively exploring open weight models now.

Their entire goal is to get to AGI via RSI ASAP. If they do they win. But if not they’ll be a legendary story of a flying too high too fast.

That they are IPOing tells me that the massive amount of funding they need is no longer available privately and that this is their 1 opportunity to get the funds they think they need to get there.

Biggest risk is the growth stalls as everyone moves to open weight models. They certainly like telling stories.

I’d challenge that and say that the opportunity cost was massive. So you needed to be super precise and confident in what to spend the time doing.

Now that opportunity cost is much lower so experimentation is more practical than before.

They do when they see the cost savings and ROI. It’s the one reliable thing that makes a company switch from any tech to another one.

Looking at our AI spend today vs 1 year ago we have massive changes. Anything that can bring this under control and potentially save millions a year is being explored.

We will probably end up with a combo of open weight models for most work and frontier models for key projects. For now. Who knows what the landscape looks like in 1 year.

Everyone I know is either starting to or planning to switch to open weight models. Cost savings are just too good.

This is what will cook frontier AI and probably prevent the investment scale to happen for AGI. Humans + good enough cheap AI is just more economic and unbelievably productive. Like why we fly on jet technology from the 1960s still with incremental improvements.

It’s why Anthropic is desperate for capital and trying to get to a scale where AGI appears. But I’m afraid they won’t get there in time and the money to build the bigger model will have dried up.

Their thesis is there won’t be companies when they achieve AGI. They are trying to fund that accomplishment by selling tokens to the companies they plan on making obsolete eventually. Essentially getting everyone to fund their own demise.

It’s shovels all the way down. Nvidea is selling shovels to frontier model labs who are selling shovels to AI companies who are selling shovels to actual businesses who have nicer power point presentations, a lot more dashboards, and some inference driven workflows.

Patriot. God bless, Mr. Zuckerberg.