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On a related note, I think that's a good monetization vector for chatbots. Long back I asked ChatGPT to recommend a few USB hard drives with very specific requirements -- including a small size and weight ("can be duct-taped to a tablet form-factor device without being obtrusive and constantly falling off"), low cost, and speed fast enough to boot an OS from. After a pretty technical conversation, it came up with 3 very specific products, one which ended up being the start point of the one I actually purchased on Amazon.

I came away thinking if those were presented as affiliated links, that conversation could have been monetized in a mutually beneficial way.

I keep thinking of that interaction whenever the discussion of ads on chatbots crops up. In an ideal world, model providers could better capture the value they provide. Unfortunately, I suspect such conversations are too rare, and often harder to monetize. (Like that time free tier ChatGPT helped me recover $500 in compensation for an airline delay. Great value for me, but no upside for OpenAI.)

Unfortunately given the amounts and timelines of returns that investors expect from OpenAI, and their scale, and with ChatGPT constrained to its “Free Consumer-facing Internet App” form factor, they are doomed to have to trade in the reserve currency of the web: ads.

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>I came away thinking if those were presented as affiliated links, that conversation could have been monetized in a mutually beneficial way.

I also ask LLMs for product recomendations. But the moment I suspect they are hidding the best items (not paying for the ad) to push the second best (not even talking about pushing shit as good products because they pay more) is the moment the LLM loses its value as recomender.

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So the only way this can work fairly if Walmart, etc implements MCP/API?
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How do you know what recommendations you can trust from the LLM output?
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You don't, but if they recommend second best options with any frequency, you'll find out eventually.
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The trouble is that monetization and usefulness tend to be in conflict. It starts out as, show affiliate links if there are any. Then it turns into, prefer targets that we have affiliate agreements for. Then, don't show products unless we have affiliate agreements. Then, prioritize ones that give us more money. And on and on.

If they want to capture some of the value they provide, they should do it the standard fashion where they directly capture value from me by having me pay.

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Gemini does this, it has Google Shopping links.
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My AI agents recommended RAM, GPU, and CPU upgrades, but deemed the prices were still pre-their-existence, when I went to the links they sent they were often 2x more expensive.
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Sounds like an opportunity for a live inventory context layer before an LLM makes recommendations
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Check out UCP
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do we need another protocol for this? seems like a stream data problem more than anything
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That's typical of my experience with all of these stock-aggregator sites. Either the best price is some dodgy or outright fake storefront, the item's OOS from the real vendor, or the price is out of date.

Trying to buy things like GPUs or SSDs are a joke. I really wish even one vendor would just implement an actual waiting list, locked to an account with a verified address and purchase history. I'm fine to wait for my purchase, but having to race bots for a lottery ticket purchase is a pain.

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This is my experience also, when trying chatgpt to purchase.
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