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abxytg | 2 years ago

there is literally a "how to" in the open AI api docs for the exact use case. I need to be more shameless the next go around.

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cddotdotslash|2 years ago

I’ve seen this argument repeatedly. The example is just that - an example. It doesn’t cover anything related to productionizing the application, dealing with user management, rate limits, cost controls, hosting the service, data persistence, documentation, billing, marketing, or any of the other 100 things you need to do to turn a simple script into a product that people are willing to pay for, trust with their data, and embed into their own websites.

So sure, be shameless, but don’t be surprised when your copy/pasted version of the example doesn’t take off.

hgsgm|2 years ago

OP didn't worry about any of that stuff, which is why they got a first mover launch and quick revenue.

abxytg|2 years ago

theres no argument. They productionized a docs example, something I did consider too shameless to try. Wish I had tried. Kudos to this dev he is rolling in the cash.

tsss|2 years ago

The key ingredient here is that he was lucky and had a viral tweet. Marketing is everything.

Kiro|2 years ago

Link? I didn't find it in https://platform.openai.com/examples

james-revisoai|2 years ago

I wrote more about this in another comment ("Postmortem"), as I developed a similar idea from Mid 2022 to early 2023, but made different decisions.

OpenAI had a serious focus on this that did see adoption; as early as Spring 2021 this was in their docs (linked by others), but more crucially, they quickly added an Answers endpoint(https://platform.openai.com/docs/guides/answers) specifically for this use case (query against uploaded files).

The creator of this project did almost everything perfectly, for sure. They had speed, UI, a converting page, found virality. But they also had timing: OpenAI had banned this open-ended use case till that time, they got lucky that people did not develop Explainpaper competitors, and ChatGPT improved quality while reducing run costs by 10x right when they came into this area, meaning many companies that fore-aware of these changes would have taken it's place, were not trying to enter the market (OpenAI approval was hard, and the costs of models before December 2022 were literally 10x as much for decent quality, making it unprofitable)