A while back I got annoyed at a specific genre of blog post: "we asked ChatGPT what the best CRM is and here's the answer." One screenshot, one run, treated as if the model holds a stable opinion. It doesn't. So I built a small harness to measure that instead of hand-waving about it.
The setup is boring on purpose. Eight models. Sixteen B2B software categories (CRM, project management, email marketing, that kind of thing). For each category I ask every model the same plain question: what is the single best tool here. One pick, no hedging allowed. I log the raw response, the parsed pick, the model, the timestamp, and the exact prompt into a JSONL file. Then I do it again next month.
Two things fell out that I did not fully expect.
First, across all sixteen categories the eight models never once agreed on the same tool. Not close-but-different. Zero unanimous picks out of sixteen. I assumed there would be at least a couple of categories where everyone converged on the obvious incumbent. Nope.
Second, and this is the one I keep chewing on: the models do not even agree with themselves. Ask the same model the same question in a fresh session and it swaps its own top pick around 74% of the time. Same model, same prompt, nothing changed but the session. Roughly three-in-four odds it contradicts what it told you yesterday.
