It’s really tough to have sanity fight against hype bros in your head. Probably I should just not visit the internet anymore

To me it’s all just people getting scammed better. With every model it looks better, but it’s at least equally worse to work with, which is the reality it needs to be. It’s less scalable more, code, tougher to understand. Your digging your own grave better kind of.

Every wrong direction/mistake is more expensive and takes more time to fix. When you have small loops you can catch those mistakes faster and cheaper.

To me we are very far off from economically given long-running tasks to agents.

Probably even less because you would spend those 1500 extra per employee also if you just save 10% so 150 per employee that’s 1.5% on salary.

This is imho one of the best ranges we can assume for now how much would that be on the whole swe market?

Increased complexity of your systems. Increased pipelines of your system.

You might reduce the likelihood of errors, but at an overproportinal cost of time it takes to complete (which some might argue is irrelevant, but has the cost of human context), and with an way higher time and focus needed for all bugs that the system doesnt work.

You’ll have to fix adapt and maintain all your verification layers, because just because you set them up they are not perfect.

Your testing pipeline becomes incredible slow and you need to maintain it as well.

It’s tremendously weaker than a hands-on approach.

I’ve written this exact same article in January and since then completely switched my position.

Good luck on everyone trying this. You shuffling your own grave and waste time.

New language, infrastructure, general level of understanding of something I barely have an idea of.

Rubber duck debugging, if i dont know the correct solution

Checking my code for issues and bugs.

But not for:

- writing my code - agentic coding (help me)

The inference has reduced drastically. It’s basically just chatting. I don’t let it write anything, but sometimes I purposely use the browser window instead of them sitting in my codebase, because I know it gets things subtly wrong and migth focus on the wrong things.

The same way people used to say don’t copypaste code at least write it out I think it’s still true. It helps to buidl the mental model and to find the right abstractions.

Also my highest respect for responding so calmly without lowering your debating level to mine. I try to best to explain what I think is wrong.

To start I didn’t interpret the article as a burn.

I think it’s interesting to explain what’s wrong with it, because it seems similar to what‘s wrong with AI. The issues are subtle.

- Anthropic doesn’t have a profitable quarter, it’s financial engineering (https://www.wheresyoured.at/anthropics-profitability-swindle...)

- The first argument about your subscription price, doesn’t has anything to do with the overall claim of the article. It would if at all be a weak argument to support the opposite. Subsidizing prices signals a lack of PMF.

- That you hire sales people after you had a billions of funding is nothing surprising and doesn’t indicate PMF or not.

- AI Implementations are fresh and of course AI Failures are thin, but so are AI successes. I haven’t seen any companies creating billions of shareholder value because they’ve massively invested in AI and their competitiors didn’t You really can look at these things in 5 to 10 years and it is multi-faceted including cultural acceptance.

- That they need to buy more compute to satisfy the requests is probably the strongest argument in the artical, but don’t conclusive. The product is been sold heavily subsidized and in hype cycle. And again both OPENAI and Anthropic have to show growth in order to justify the IPO.

- Regarding the part about revenue I refer to the linkedm article above, as it does explain it very well.

The conclusion is reasonable given the arguments, but not the title.

However it is missing all the real discussion points that are actually in observation at the moment.

Local models as alternatives, IPO finanical engineering, how AI implementation actually will perform over years... Let’s all not forget crypto. It’s been full of "use cases" just a bunch of years ago. I like the idea of crypto(btc,eth) and I’m still invested, but 99.99% of coins have died on promies.

So this is not a piece of critical thinking, but this reads like a twitter thread to sell me a course :/

How long would it taken you to do it yourself? How much longer will the next task take you, compared to when you would’ve written the code yourself. How is the mental model compared to when you would’ve written it yourself?.

I’m not saying you’re wrong, again there are use cases. But the calculation is not plain and simple it goes deep into our perception, perceived productivity versus actual productivity.

I’ve 2 months maxxed out all 6k of Claude Code and bought Antigravity on top. My codebase became 140k lines. I introduced tons of bugs and spent another 2 months, deleting 80k of code. I wish I would’ve just chatted with AI and not let agents touch my codebase. I would’ve saved approx 300$ subscription prices a month and 2 months of my life.

I know everything you’ve done for the tech community, but I please you to take some time off and reflect on this article. It’s not on par with ur usual level, but the tendency has been visible from the last couple of articles.

It’s quite an elaborate swindle obviously. But you generate hype with underselling your core product, you claim way more usability then there is. Users will experience usability initially. Everything multiplies with each other and then you put it on the market. Everybody involved makes money and you’ve succesfully extracted money from everyone who’s invested in NASDAQ index funds at the very least.

> Dario and Sam are saying “if you buy our coding agent subscription you can build a game with zero skill and one shot and then be rich”?

That’s Anthropics marketing, yes.

Also their offering is not uniqe that justifies a 1 trillion valuation. The first companies are already rowing back. It’s a really certain time window that they are about to hit now with their IPOs

The companies that have signed these enterprise deals haven’t done a ROI analysis. They had Fomo.

AI has some use cases, but not at the price it’s currently priced at. I’ve been on AI since GPT-2 with a lot of heavy users. Every user has the same story, curiosity, surprise, hype, hate, realization. Enterprise is usually a bit behind and are right now at hype cycle, that’s where they sold all the deals and do the IPO.

It’s really a VC masterclass.

Don’t get me wrong there is are useful cases of AI, but not the way the want it to be. Quite similar to Blockchain. The idea of decentralized money has right to exist. 99% of other coins not.

AI is a faster, but still less accurate search engine. AI is great in finding bugs, it’s great at ruber duck debugging.

The reason I call it a swindle is, because along with the marketing it gives tons of people in the world the impression, they can now build their own startup, game, infra etc without the need to learn it themselves. This leads to millions of abandoned and low qualiy projects and products, because the vast majority has never built the mental modal necessary to solve the problem thoroughly. In the end they’ve wasted months and money (but burnt tokens). This is what I call a swindle.

All early adaptors I know have not drastically winded down their usage, not because of money, but because there is no new case. If you want to explore a new project you can get onboarded quickly learn a lot and then switch to documentation and live testing. For me usage is the lowest it has been the last 2 years.

I would not let AI touch my code. I have anxiety around it, because it will gripple back up. I will let it read my code and let me know what I did wrong so I’m sharpening myself.

100s of companies including open source solution can offer that for me.

All my non-tech friends are now in hype cycle and share their hype and fore forseeable frustration with me.

I have to say I’m in a way impressed in how AI has been rigorously vc-utilized (conciously or not-conciously) to generate these vast companies with the whole world watching.

The downside is you use less tokens.

I’ve not listened to a radio station for years. No offense :/

Bigger harnesses need to balance upping your token usage and being helpful.