this post was submitted on 17 Nov 2025
55 points (95.1% liked)
Technology
76868 readers
2507 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related news or articles.
- Be excellent to each other!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, this includes using AI responses and summaries. To ask if your bot can be added please contact a mod.
- Check for duplicates before posting, duplicates may be removed
- Accounts 7 days and younger will have their posts automatically removed.
Approved Bots
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
No, it isn't.
As per IBM https://www.ibm.com/think/topics/agentic-ai
The key part being the last sentence.
Its the idea of moving away from a monolithic (for simplicity's sake) LLM into one where each "AI" serves a specific purpose. So imagine a case where you have one "AI" to parse your input text and two or three other "AI" to run different models based upon what use case your request falls into. The result is MUCH smaller models (that can often be colocated on the same physical GPU or even CPU) that are specialized rather than an Everything model that can search the internet, fail at doing math, and tell you you look super sexy in that minecraft hat.
And... anyone who has ever done any software development (web or otherwise) can tell you: That is just (micro)services. Especially when so many of the "agents" aren't actually LLMs and are just bare metal code or databases or what have you. Just like how any Senior engineer worth their salt can point out that isn't fundamentally different than calling a package/library instead of rolling your own solution for every component.
The idea of supervision remains the same. Some orgs care about it. Others don't. Just like some orgs care about making maintainable code and others don't. And one of the bigger buzz words these days is "human in the loop" to specifically provide supervision/training data.
But yes, it is very much a buzzword.
Hat on top of a hat technology. The underlying problems with LLMs remain unchanged, and “agentic AI” is basically a marketing term to make people think those problems are solved. I realize you probably know this, I’m just kvetching.
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.