Based on a month of GPT5 usage, this model feels like primarily like a regression:
1. It's slow: thinking mode can take ages, and sometimes gets downright stuck. It's auto-assessment of whether or not it needs to think feels poorly tuned to most tasks and defaults too easily to going into deep reasoning mode.
2. Hallucinations are in overdrive: I would assess that in 7/10 tasks, hallucinations continuously clutter the responses and warrant corrections and careful monitoring and steering back. It hallucinates list items from your prompt that weren't there, software package functionalities/capabilities and CLI parameters etc. Even thorough prompting with explicit linking to sources, e.g. also wihtin deep research frequently goes of the rails.
3. Not self critical: even in thinking mode, it frequently spews out incorrect stuff, that a blatant "this is not correct, check your answer" can directly correct.
Note: I am not a super advanced prompt engineer, and this above assessment is mainly wrt the previous generation of models. I would expect that with progression of model capabilities, the need for users to apply careful prompt engineering goes down, not up.
I am very curious to hear your experiences.
