I think this is a bit hyperbolic. Someone still needs to review and test the code, and if the code is for embedded systems I find it unlikely.

For SaaS platforms you’ll see a dramatic reduction, maybe like 80% but it’ll still have a handful of devs.

Factories didn’t completely eliminate assembly line workers, you just need a far fewer number to make sure the cogs turn the way it should.

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 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.

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.

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

Anyways, formulas are a lot better than one shot.

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.

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

Speed, cost, security, job/task management

Next question

All of that will inevitably be solved.

50 years ago, using a personal computer was an extravagant luxury. Until it wasn't.

30 years ago, carrying a powerful computer in your pocket was unthinkable. Until it wasn't.

Right now, it's cheaper to run your accounting math on dedicated adder hardware. But Llms will only get cheaper. When you can run massive LLMs locally on your phone, it's hard to justify not using it for everything.

If I can run 50,000 fixed tasks that cost me $0.834/hr but OpenAI is costing $37/hr and the automation takes 40x as long and can make TERRIBLE errors why the fuck would I not move to the deterministic system?

Also, battery life of mobile devices.

But now, we not only have laptops, we run horribly inefficient GUIs in horribly inefficient VMs on them.

The dollar-per-compute trend goes ever downward.

Yes. That's precisely why my company runs dBase 7 on a fleet of old 286DX machine from Compaq. /s

Running obsolete software will be cheaper, but the value provided by the newer technology will make the difference insignificant.

Why do 50,000 tasks with an LLM when I can do 64,467,235 without an LLM that the LLM created for the same cost on probably far lower cost hardware?

Because you'll be outcompeted by people who make the best of the nondeterministic system.

There are several human activities where allucinations can cost lives. We can't use LLMs for everything.