DeepSeek (reasoning) and Gemini (multimodal) have been useful for me — especially when I want stronger pushback or a different angle. What are you hoping to get that you’re not getting from the usual set?
It's interesting, as I type that out it makes me wonder why not just go back to the search engine since it has the AI summaries that have been getting better.
Finally, I do also like the longer reasoning when I have a tough question and usually like to copy paste it around to various models and compare their responses.
On the search engine comparison: do you feel LLMs reduce cognitive load because they maintain context, whereas search requires more manual synthesis?
Also curious — do you think the frustration is mostly with the model itself, or with the serving/infrastructure layer (Cloudflare, routing, batching, etc.) around it? Both comments seem to point at that layer in different ways.
In custom instructions I’ll sometimes write something like “tell it like it is.” Interestingly, some models then start with “okay, I’ll tell you like it is…” which makes me wonder whether that’s psychological framing, operational behavior, or both.
Curious why you asked — have you found customization meaningfully changes performance?
Since I primarily used ChatGPT, I picked up a bunch of prompts from people sharing it in order to optimize for better results. I don't know if this is relevant anymore as I think they've fixed quite a bit and now you can customize tone and warmth directly.
My prompts were more on avoiding filler, be more direct etc, no emojis etc.