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> Long-term, they will need none. I believe that software will be made obsolete by AI.

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.

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> 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.

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> 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.

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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.
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> Why use AI to build software for automating specific tasks, when you can just have the AI automate those tasks directly?

Speed, cost, security, job/task management

Next question

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> Speed, cost, security, job/task management

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.

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Not until power access/generation is MUCH cheaper. Long, long, long way off.

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.

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These exact arguments could have been made 50 years ago about why laptops are impossible.

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.

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It will never ever be as cheap as as cron job and a shell script. There is a certain limit to how efficient using an LLM to do a job vs using an LLM to create a job is. There is a large distinction in compute and power resources between the two. Don't mistake one for the other.
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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?

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

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