Over a month later, I still don't know where my referral reward went. Endless canned replies, no real effort, no one who can resolve it. I've used ChatGPT since launch and been a long-term subscriber. All I wanted was an explanation. This experience has been appalling.
6/6 Repeating the same evidence for weeks has wasted my time. I want a specific answer: what benefit did those 250 points provide, when was it applied, and how was I supposed to use it? If OpenAI cannot verify delivery, I want the promised reward or an equivalent remedy.
1/6 On Aug 29, 2026, OpenAI emailed me that my ChatGPT Desktop referral succeeded and 250 points had been added to my account. More than five weeks later, I still have no clear explanation of what usable reward I received. @OpenAI, this needs a real answer.
5/6 On Oct 4, I also asked about retention-offer eligibility, acknowledging it was not guaranteed. Support escalated again. On Oct 6, it declined referral restoration, an equivalent credit and goodwill credit, without identifying what the 250-point reward actually was.
We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:
Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:
Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better:
Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better:
Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work!
In summary:
- As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding.
- Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.