this post was submitted on 17 Nov 2025
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Not really. By breaking down the problem you can adjust the models to the task. There is a lot of work going into this stuff and there are ways to turn down the randomness to get more consistent outputs for simple tasks.
This is a tricky one... if you can define good success/failure criteria, then the randomness coupled with an accurate measure of success, is how "AI" like Alpha Go learns to win games, really really well.
In using AI to build computer programs and systems, if you have good tests for what "success" looks like, you'd rather have a fair amount of randomness in the algorithms trying to make things work because when they don't and they fail, they end up stuck, out of ideas.
To play devils advocate, agentic things wouldn’t necessarily include software development. “Hey siri create me an e-commerce site” isn’t likely to happen for a long while, because like you said it’s a complex thing that doesn’t have clear success measures. But “hey siri get me a restaurant reservation at place, hire a taxi for me to get there, and let Brad know the details” can be broken down into a number of different “simple” things that have simple to define measures of success. Did a reservation get booked? Did we tell Brad the details? etc.
You should try it. If your e-commerce site is simple with a lot of similar examples out in the wild to point at, I believe the latest agents actually can do such a thing. You'll just have to give them access to your financial account details so the site can process payments to you, you understand? While that's a joke, it's also true. You need to be able to check what the AI has done to be sure it's doing what you want.