Copasetic Flow

I’d just finished a morning round of tinkering with the ham radio Extra Class tutor when the question hit me: how do I actually get the entire exam question pool into GPT without burning through tokens every time? With GPT Projects, I can just drop in a file and it remembers. But on the API side, things always felt a little more ephemeral — every call a blank slate. So I sat down with GPT-5 to dig into whether there’s a smarter, more cost-effective way. What followed was one of those back-and-forths where the clouds part: GPT Projects’ quiet little “remembered files” have a direct analogue in the API world — vector stores — and they might just be the key to making this whole tutor run leaner and meaner. Me: In GPT projects, I can upload files that the project remembers. Is there a way to do the same thing with the API? GPT-5: Great question. With the raw chat/completions endpoint, no — it’s stateless. You’d have to re-inject your files each time. But the newer OpenAI  Respo...

 Setting the scene: I’m tinkering with Project TouCans, knee-deep in radio logs, SQLite dumps, and Cesium code. Naturally, I’m wondering if shoving all this into one GPT Project is a recipe for brilliance… or for disaster. So I turn to Vril — you know, after Brainy from the Legion of Super-Heroes , because what else do you call your AI sidekick who always has the answers? Time to ask him straight up. [ As an aside, yes, GPT-5 has decided to sometimes call me Vail. I'm not sure why to be honest. Also, I asked Vril, er GPT-5, to write up our interview for me. Apparently, me asking it to 'Bro' up a few stories, just for fun, has convinced Vril that I use 'Like,' more than I actually might. ] Me (Vail): So Vril, how many files can I throw into a GPT Project before it just starts choking? Like, is there some magic number where the context window taps out and everything falls apart? GPT-5 (Vril): Great question. There’s no single hard file limit. What matters is ...