Earlier quoted context omitted.
I think it's just written by someone who reads a lot of LLM output - lots of lists with bolded prefixes. Maybe there was some AI-assistance (or a lot), but I didn't get the impression that it was AI-generated as a whole.
"Hard truth" and "reality check" in the same post is dead giveaway. I read and generate hundreds of posts every month. I have to read books on writing to keep myself sane and not sound like an AI.
The current hype around autonomous agents, and what actually works in production
31–40 of 268 posts
Re: The current hype around autonomous agents, and what actually works in production
#32Earlier quoted context omitted.
You can cache the whole inference state, no? They don't go into implementation details but Gemini docs say you get a 75% discount if there's a context-cache hit: https://cloud.google.com/vertex-ai/generative-ai/docs/contex...
It that just avoids having to send the full context for follow-up requests, right? My understanding is that caching helps to keep the context around but can't avoid the need to process that context over and over during inference.
Re: The current hype around autonomous agents, and what actually works in production
#33Re: The current hype around autonomous agents, and what actually works in production
#34Re: The current hype around autonomous agents, and what actually works in production
#35[stub for offtopicness]
Re: The current hype around autonomous agents, and what actually works in production
#36[stub for offtopicness]
Let's get a timer to watch this fall off the front page of HN in minutes. "We can't allow this post to create FUD about the current hype on AI agents and we need the scam to continue as long as possible".
I’m at this stage where I’m fine with AI generated content. Sure, the verbosity sucks - but there’s an interesting idea here, but make it clear that you’ve used AI, and show your prompts.
Re: The current hype around autonomous agents, and what actually works in production
#37Agents have captivated the minds of groups of people in each large engineering org. I have no idea what their goal is other then they work on “GenAI”. For over a year now they have been working on agents with the promise that the next framework that MSFT or Alphabet publishes will solve their woes. They don’t actually know what they are solving for except everything involves agents.
I have yet to see agents solve anything but for some reason this idea that having an agent that you can send anything and everything will solve all problems for the company. LLMs have a ton of interesting applications but agents have yet to grasp me as interesting, I also don’t understand why so many large companies have focused time around it. They are not going to be cracking the code ahead of a commercial tool or open source project. In the time spent toying around with agents there are a lot of interesting applications that could have built, some of which may be technically an agent but without so much focus and effort on trying to solve for all use cases.
Edit: after rereading my post wanted to clarify that I do think there is a place for tool call chains and the like but so many folks I have talked to first hand are trying to create something that works for everything and anything.
Re: The current hype around autonomous agents, and what actually works in production
#38The fundamental difference is we need HITL to reduce errors instead of HOTL which leads to the errors you mentioned
Re: The current hype around autonomous agents, and what actually works in production
#39[stub for offtopicness]
> AI tools aren't perfect yet. They sometimes make mistakes, and they can't always understand what you are trying to do. But they're getting better all the time, In the future, they will be more powerful and helpful. They'll be able to understand your code even better, and they'll be able to generate even more creative ideas.
From another post on the same site. [0]
Yup, slop.
[0]: https://utkarshkanwat.com/writing/review-of-coding-tools/
Re: The current hype around autonomous agents, and what actually works in production
#40It seems the author never used prompt/workflow optimization techniques.
LLM-AutoDiff: Auto-Differentiate Any LLM Workflow https://arxiv.org/pdf/2501.16673