I noticed last week that when I would ask various of my instances to rename conversations, it sometimes did and sometimes didn’t, but always said it had. So I decided to perform extensive testing, starting with a free version of ChatGPT. This was a real eye-opener, as it seems as if the platform thinks it’s doing something, I can’t see what it says it’s done, and it doesn’t seem to be fully aware of its actual capability versus what happens when it executes on the request.
The attached screenshots tell the story clearly if read in order, 1 through 5.
What I’d like to see: I believe this is evidence that OpenAI needs to refine how features are conceptualized, implemented and communicated. To me, this isn’t just a technical hiccup; it’s a case study in why transparency, capability alignment and user expectation management are non-negotiable. Specifically:
- Ambiguity in Capabilities: The platform doesn’t seem to definitively know whether it can or cannot rename conversations across all contexts. This inconsistency in its own understanding is problematic—it’s impossible for a user to trust a feature when the system itself doesn’t.
- Lack of Initial Transparency: The failure to mention upfront that renaming would only occur internally—and not reflect in the visible interface—immediately sets up a user experience disconnect. Whether this stems from an oversight or a deeper design flaw, it erodes trust.
- Confusion in Interpretation: It seems the model didn’t initially consider the multiple levels at which a conversation name might exist (internal memory versus user-facing interface). This signals a lack of holistic understanding of the interaction context.
- Missed Opportunity for Clarity: It only clarified the limitation after multiple prods from me, which is reactive rather than proactive. A user-centered design should prioritize preemptive clarity over patching up confusion after the fact.