The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Nikunj Handa no published score: only 2 usable exchanges on raw tape, and a fair score needs 8+ record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

clear all ✕
2exchanges match
2on raw tape
1redirected or not addressed
Answered raw tape D 5 · C 5 · P 5 · Cm 4 4.85

Q use each type of API? So I know that in the past, the assistance was maybe more stateful, kind of like long running, many tool use kind of like file based things and the chat completions is more, Stateless, you know, kind of like traditional completion API. Is that still the mental model that people should have? Or like, should you by default always try and use the responses API?

A So, so the responses API is going to support everything that the chat, it's at launch going to support everything that chat completion supports. And then over time, it's going to support everything that assistance supports. So it's going to be a pretty good fit for anyone starting out with OpenAI. They should be able to like go to responses. Responses, by the way, also has a stateless mode. So You can pass in store false, and that'll make the whole API stateless, just like chat completions. We're really trying to, like, get this unification story in so that people don't have to juggle multiple endpoints. That being said, like, chat completions, just like, it's our most widely adopted API. It's so popular, so we're still going to, like, support it for years with, like, new models and features. But if you're a new user, you want to, or if you want, like, existing user, you want to tap into some of these, like, Built-in tools or something, you should feel, feel totally fine migrating to responses, and you'll have more capabilities and performance than, than check completions.

AI assessment note: “it's going to be a pretty good fit for anyone starting out with OpenAI.”

Redirected raw tape D 2 · C 4 · P 4 · Cm 3 3.25

Q Do you see people, uh, using the files and the search API together where you can kind of search and then store everything in the file so the next time I'm not paying for the search again and like, yeah, how should people balance that?

A That's actually a very interesting question. Let me first tell you about how I've seen a really cool way I've seen people use files in search together is they put their user preferences or memories in the vector store. And so a query comes in, you use the file search tool to like get someone's like reading preferences or like fashion preferences and stuff like that. And then you search the web for information or products that they can buy related to those preferences. And you then render something beautiful to show them like, here are five things that you might be interested in. So that's how I've seen like file search, web search work together. And by the way, that's like a single responses API call, which is really cool. So you just like configure these things, go boom, and like everything just happens. But yeah, that's how I've seen like files and web work together.

AI assessment note: “Let me first tell you about how I've seen a really cool way”

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