> Someone still needs to review and test the code, and if the code is for embedded systems I find it unlikely.

I feel like you didn't understand my comment. I am predicting that there is no code to review. You simply ask the AI to do stuff and it does it.

Today, for example, you can ask ChatGPT to play chess with you, and it will. You don't need a "chess program," all the rules are built in to the LLM.

Same goes for SaaS. You don't need HR software; you just need an LLM that remembers who is working for the company. Like what a "secretary" used to be.

> I feel like you didn't understand my comment. I am predicting that there is no code to review. You simply ask the AI to do stuff and it does it.

I didn’t, and thanks for clarifying for me.

This doesn’t pass the sniff test for me though - someone needs to train the models, which requires code. If AI can do everything for you, then what’s the differentiator as a business? Everything can be in chatGPT but that’s not the only business in existence. If something goes wrong, who is gonna debug it? Instead of API requests you would debug prompt requests maybe.

We already hate talking to a robot for waiting on calls, automated support agents, etc. I don’t think a paying customer would accept that - they want a direct line to a person.

I can buy the argument that the backend will be entirely AI and you won’t need to be managing instances of servers and databases but the front end will absolutely need to be coded. That will need some software engineering - we might get a role that is a weird blend of product + design + coding but that transformation is already happening.

Honestly the biggest change I see is that the chat interface will be on equal footing with the browser. You might have some app that can connect to a bunch of chat interfaces that is good at something, and specializations are going to matter even more.

It was a bit of a word vomit so thanks for coming to my TED Talk.

We hate talking to robots because they are largely useless when we have anything out of routine. We love talking to robots when we would ordinarily wait 30 minutes for a 3-minute conversation.

> I don’t think a paying customer would accept that - they want a direct line to a person.

What the customer wants only matters insofar as they are willing to pay for it. Sure, I'd rather talk to a person... But I'm not willing to pay 100x as much for a service that's only marginally better. Same reason I don't fly first class, as miserable as coach is.

Someone may want to pay for a boutique human lawyer/banker/coder/professor, maybe as a status symbol, the same way people pay $20k for an ugly handbag. But I think most people will take the cheaper and almost as good option, when the difference in quality is far overshadowed by the difference in price.

> someone needs to train the models, which requires code.

I'm not sure that training llms is a coding problem, but it doesn't much matter: llms can train each other.

> If AI can do everything for you, then what’s the differentiator as a business?

Good question. My gut says there isn't: all money flows to the model providers, everyone else is a serf at best parasiting on someone else's model.

Good points. People might not pay 100x for something but it’s all about perceived value. Part of a successful business is to identify the perceived value, and find out your PMF while being different enough from the competition. It’ll be interesting to see how things play out, we are in such early days still.

Because AI agents are tool users. Why does AI need to research 2026 tax code changes and then try to one-shot your taxes when it can just use Turbotax to do it for you? Turbotax has the latest 2026 tax changes coded into the app. I'd feel much more confident if AI uses Turbotax to do my taxes than to try to one-shot it.

> Turbotax has the latest 2026 tax changes coded into the app.

How does TurboTax implement the latest tax changes? My guess is that before the decade is over, the answer is "an LLM does it."

Yes but I’ll be glad to pay for human oversight at TurboTax.

Anyways, formulas are a lot better than one shot.

LLM technology will never achieve 100% accuracy in its output. There is an inherent non-determinism. Tasks that require 100% accuracy cannot be handled by LLMs alone. If an LLM is used to replace HR, it will inevitably do something wrong, and a human will need to be in the loop to correct it.

Same goes for chess, there will always be a chance that it makes an illegal move. Same goes for code, there will always be a chance that it produces the wrong code.

Maybe a new AI technology will be developed that doesn't have the innate non-determinism, but we don't have that now.

Relevant to your comment is this link from today's HN front page, about adapting LLMs to perform deterministic calculations.

https://www.percepta.ai/blog/can-llms-be-computers

So even in your example you still need to have someone to ask the AI to play chess. So there will still be a need for someone somewhere to ask the AI to do something and supervise it or guide it in the right direction.

You've misunderstood my position. My argument is not that "AIs can operate independently and don't need supervision," but rather that "AIs are able or will soon be able to perform complex behaviors directly without having to create traditional software first." The chess example is illustrative because you can play chess with the AI without first asking the AI to implement chess-playing software. This means that software is obsolete, not people.