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1245 points adrianh | 1 comments | | HN request time: 0.206s | source
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ahstilde ◴[] No.44491178[source]
This is called product-channel fit. It's great the writer recognized how to capture the demand from a new acquisition channel.
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toss1 ◴[] No.44491291[source]
Exactly! It is definitely a weird new way of discovering a market need or opportunity. Yet it actually makes a lot of sense this would happen since one of the main strengths of LLMs is to 'see' patterns in large masses of data, and often, those patterns would not have yet been noticed by humans.

And in this case, OP didn't have to take ChatGPT's word for the existence of the pattern, it showed up on their (digital) doorstep in the form of people taking action based on ChatGPT's incorrect information.

So, pattern noticed and surfaced by an LLM as a hallucination, people take action on the "info", nonzero market demand validated, vendor adds feature.

Unless the phantom feature is very costly to implement, seems like the right response.

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1. Gregaros ◴[] No.44491641[source]
100%. Not sure why you’re downvoted here, there’s nothing controversial here even if you disagree with the framing.

I would go on to say that thisminteraction between ‘holes’ exposed by LLM expectations _and_ demonstrated museerbase interest _and_ expert input (by the devs’ decision to implement changes) is an ideal outcome that would not have occurred if each of the pieces were not in place to facilitate these interactions, and there’s probably something here to learn from and expand on in the age of LLMs altering user experiences.