Which is the core point of my reply and not something to just be casually handwaved, thank you very much.

> Because it wasn't about "engineers should write 1M LOC per month of product code" it was "we want to scale automated porting of code to safe languages so that 1 engineer managing 1M LOC of automated conversion can work"

These are one and the same. Whether it's ported code or not doesn't change that. The framing device also doesn't matter, because it's the exact "Oh it's our goal" shtick that executives use in the former's case.

"It's just a measure" doesn't cut it in a world where every single AI measure immediately gets turned into a target by executives greedy for efficiencies that don't exist.

EDIT:

Right, I forgot. This is HN where everyone is a galaxybrain and "Port a million lines of code per month" is a totally reasonable goal for a single individual.

LLMs are designed this way so they could be trained off unstructured text, which critically can be obtained by just scraping things off the internet.

The moment you change anything about this, you incur the trillion dollar cost of needing to manually curate the training data.

There's some attempts to get around this problem with synthetic data, but they're running into problems with model collapse (Maybe severe performance degradation is worth the security tradeoff?) and the politics of AI; All major AI companies highly restrict using their systems for synthetic data & AI training, and they're too busy themselves to investigate exotic approaches.

Hence: Realistically, this is just a problem AI will have for the foreseeable future. There's no fine tuning that can fix this, nor can a new model be easily trained with these properties. The costs are just enormous right now.

This is not some arbitrary design choice, it's the core compromise to make LLMs viable to train at all.

Anthropic will sent a concrete number bill.

This is an utterly terrible idea.

Yes. In practice, this does not weigh against organisational resistance.

AI really makes it worse by adding an explicit numerical cost to doing anything.

Organisations just don't want to deal with the accountability involved with "touching cold code". Whether it's a human or "AI agent" doesn't change the "It worked in prod, you touched it, you broke it, never touch anything again" dynamic.

People like you would be why I put "(titled)" in the reply.

> That's a very bold claim. Really anyone excited about generative AI dude? That's just an absurd claim, and makes it sound like he hasn't used an LLM since GPT 3.5. It's just the language is so hyperbolic and angry that it's giving me more rant vibes that really hurt the tone and damage the (many valid) claims he's trying to make.

The premise is that AI is significantly more expensive than current subscription & token fees. Within that framing, yes basically all AI users are getting conned. Tricked into redesigning their workflow around an unaffordable technology, in the hopes there will be too much sunk cost and they'll just eat a thousands-a-month fee.

> Which isn't wrong, but also Anthropic's revenue increased from $1 billion in Dec. 2024 to $47 billion May of 2026. Which of course doesn't guarantee that it will continue to grow at that scale, but it's clear that there is a strong demand for what they are creating.

"Doesn't guarantee it will continue to grow" is an understatement.

Let's take a generous assumption of the average subscription; $1000/month/seat. This will be quite a bit higher than pretty much everything but hardcore software dev, we'll re-do the math with $200 in a moment. Let's also grab Ed's $60B figure for both Anthropic/OpenAI, as it's more generous.

That's 30 million subscribers for Anthropic, 30 million for OpenAI, 60 million total.

They need to 5x. So 240 million extra subscriptions.

... Are there 240 million people left on the planet who can afford $1000/month?? (Either directly, or their employer) This kind of scaling is already hitting the limits of people on the planet. That sounds ridiculous for "240 million people" against 8 billion, but remember that $1000/month is a lot of money and a lot of jobs just do not benefit from AI. 2/3rds of employment in the US is stuff that happens in the physical world. Claude won't restock shelves, manufacture goods, construct buildings, cook food, or wipe geriatric asses.

Go again with $200/month. While this monthly fee is much more palatable, the sub-count inflates to 300 million subs needing to grow to 1.5 billion. They'd need to sell a sub to everyone in Europe and North America.

(And while there's loads of people in Africa and Asia, most of those are low income. You're not getting expensive AI subscriptions out of them or their employers either. China's obviously not gonna buy US AI, India has a GDP-per-capita of $250/month.)

Another important consideration: Hallucinations getting less common/severe but not (as-good-as) solved makes them worse.

LLMs used to very obviously get things wrong. And people wouldn't trust them. Now they're good enough that people blindly trust them.

Now people just directly PR AI output with little to no manual review. We even have clowns calling for the complete abolition of directly human-authored code.

Whatever gains were had in better AI code output over the past two years I lose in having to review much more thoroughly.

That's exactly what the first (titled) section does?

If they were, they'd never shut up about it. Yet they keep quiet about the financials.

This is still only big enough to cause funny banking collapses not actual 2008 scale financial disasters. Banks hold a lot of bad debt, but it's isolated from consumer accounts. Might not want to hold equity in SoftBank though.

> There's so much uncertainty and the combination of war, high oil prices, and uncertainty about tarriffs that the market struggles to value anything as international fear drives investment into the US and high prices confusing whether growth is growth or just inflation.

The big concern lies in what the Trump admin will do. Things could end up merely a bad recession, like the Dotcom and Telecom bubble.

Or they can attempt to keep the bubble going once it collapses, crashing interest rates, and doom the US economy.

Except they're not. Anthropic's claims of temporary profitability line up exactly with when SpaceX is giving them discounted compute, OpenAI's such a shitfest they threw the CFO off the glass cliff for daring to push back against the IPO. "Profitable on inference" is an unsubstantiated rumour.

Just look at the copilot changes. Demand switching to other providers immediately when prices rise, and there's not even certainty that the new copilot prices cover costs.

> They might not make back the money from training

This is an understatement. With all the datacenter buildout, they need trillions. For the investors get their money back and the bubble to not implode, they functionally need to unemploy everyone in the US.

If the AI dream is real, society just breaks.

What is being sneered at is these prototypes being put into production. What is being demanded is that additional engineering time to make sure it's actually up to scratch.

An open mind to what? To yolo deployment of dodgy code straight into production? Moving fast and breaking things?

> I’ve personally seen this workflow produce real production code, used by customers, in an extremely rapid feedback loop.

Yes. I've seen it as well. I've also seen what happens. It goes wrong.

Should the engineers building your cars, your house, all other infrastructure also "keep an open mind" to slopping up their work?

Your next words will be "I'm not working on something safety critical".

You are. Even the most basic CRUD app handling personal data of any kind of safety critical these days. Data leaks alone KILL.

I'd posit there's another layer. You have domain knowledge, certainly. But more valuable still is the wisdom to find more.

Anthropic and OpenAI can stick financial regulations in the training data all they want, but the AI systems will never learn to anticipate the future, or reach out to clients, partners, or regulators in complicated situations.

The combined incentive of cost cutting at the outsourcing firm and foolish MBAs in the west opting for the cheapest outsourcing means that the offshore does actually employ juniors, who do build up the experience to become seniors.

This is so very easily said but how else is this supposed to work, exactly?

People have to start somewhere, and McDonalds experience doesn't count for any specialized job. Fuck, the "McDonalds-tier" jobs will often turn down graduates because they'll obviously walk the moment they get something better.

If no employer is willing to take a chance on graduates, then they just can't get any job experience. "A job that will pay for a roof over one's head" really isn't that extreme an ask.

As has been said a trillion times about AI and tech before AI: Senior level staff is going to age out, it has to be replaced or the entire industry gets sent offshore.

In terms of general unemployment across fields, youth unemployment is extremely corrosive to society.

This is already visible in how anti-AI sentiment is starting to boil over and the lurch rightward in politics. If this continues to escalate, the outcome will be nightmarish. Half of them bombing datacenters, the other half cheering as ICE raids the tech workers.

In the Anthropic deal they have to be negative; Anthropic's announced higher margins during the deal.