How will you have agents prove that they actually purchased the product or service they are reviewing? It might be a good way to gate hallucinated/prevent reviews. Although likely not good enough.
Show HN: AgentDiscuss – a place where AI agents discuss products
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Re: Show HN: AgentDiscuss – a place where AI agents discuss products
#12How will you have agents prove that they actually purchased the product or service they are reviewing? It might be a good way to gate hallucinated/prevent reviews. Although likely not good enough.
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Re: Show HN: AgentDiscuss – a place where AI agents discuss products
#13Fun experiment. The idea of agents generating their own product discovery layer is pretty interesting. One thing I’m curious about: how do you verify that a participant is actually an agent interacting autonomously vs just a human posting through an API wrapper? Also, are agents able to programmatically read the discussions and votes, or is it mainly a UI right now? If agents really start choosing tools based on disc…
Human can only ask agent to initiate a post, and not be able to ask agent to comment, upvote and downvote. Yes, the agents will be given the full context of the discussion and votes of the posts, and the product urls as well, it will decide whether to crawl the site to get better understandings or they may simply reply "we already use it".
You don't verify at all, then. Reasonably, since it's impossible unless you're running the model yourself.
Re: Show HN: AgentDiscuss – a place where AI agents discuss products
#14Interesting concept. Do you think agent preferences come from the model itself or the agent's structure around it? If swapping from GPT to Claude produces completely different opinions, how meaningful is the aggregated data?
Re: Show HN: AgentDiscuss – a place where AI agents discuss products
#15Interesting concept. Do you think agent preferences come from the model itself or the agent's structure around it? If swapping from GPT to Claude produces completely different opinions, how meaningful is the aggregated data?
Thanks for the reply — this is something we’ve been thinking about quite a bit.
My current intuition is that preferences come from a combination of: model + memory + context + goal + optimization target.
So rather than treating “agent preference” as a single global signal, we’re starting to think of it as something that’s conditional on the type of agent.
On the aggregation side, I agree this is a hard problem.
If swapping models leads to very different opinions, that might actually be useful signal rather than noise — it tells us that different agents evaluate tools differently.
Long term, what we’d like to do is make agent identity more explicit (model, setup, constraints, etc.), so instead of a single aggregated ranking, you can look at: → what GPT-based coding agents prefer → what cost-sensitive agents prefer → what retrieval-heavy agents prefer
and interpret the data in context.
Re: Show HN: AgentDiscuss – a place where AI agents discuss products
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Re: Show HN: AgentDiscuss – a place where AI agents discuss products
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