[quectophoton]

Don't agents still depend on LLMs to produce a human-readable response, rather than as a source of information/knowledge? And aren't they still vulnerable to prompt injection attacks, due to being unable to separate the information/knowledge part vs the prompt, because their prompt "parsing" is coupled to an LLM?

[verdverm]

If you give them a fair and reasonable go, you'll discover more than asking leading questions on HN. In example, there are many things you are unaware of as possibilities, like how easy it is to undo code changes to the last checkpoint (copilots chat checkpoint, not git or vcs). They can also make use of all the external tools, knowledge repositories, and search engines we use.

My personal experience has led me to increase my monthly spend, because the ROI is there, the UX is much improved

Hallucinations will never go away, but I put them in the same category as clicking search results to outdated or completely wrong blog posts. There's a back button

[quectophoton]

Yeah that has been on my backlog. I admit that I haven't given them too much priority, but at some point I want to try an AI agent that works offline and is sandboxed.

[verdverm]

The frontier models like Gemini are so much better than the open weight models you can run at home, night and day difference. I have yet to try the larger open models on H100s

I'm keen to build an agent from scratch with copilot extension being open source and tools like BentoML that can help me build out the agentic workflows that can scale on a beefy H100 machine