Unfortunately, your latest imaging rules are killing my ability to use you even with my own images. Even when following the rules with my own original images, the AI seems to not understand its own rules applying them inconsistently.

Thank you for this. Looking forward for how pragmatics (reading context, co-text and background) work in this new model.

Refining model behavior at scale is one of the hardest challenges in LLM systems, as it is not just about training data, but about building reliable feedback loops, evaluation pipelines, and guardrails that generalize. I am exxcited to hear how GPT-5.1 Instant approaches this.

Insightful topic! How do these refinements impact user interaction?

The discussion about personality controls and large-scale behavior refinement points to a deeper need: AI still lacks a structured way to understand how humans think, not just what they say. Humans operate in contextual fields — shifting emotional load, attentional states, internal contradictions, and resonance patterns. If models could integrate these cognitive fields rather than only textual signals, we would unlock: – more stable alignment, – safer reasoning, – far better human-AI collaboration, – and reduced hallucination through context anchoring. This is an exciting frontier, and one that will define the next generation of responsible AI. #OpenAI #AIAlignment #CognitiveArchitecture #HumanAIModels

It’s great that you fixed, and the transparency is admirable - but it took users about half an hour to figure out that something was very wrong. How did the model even make it to production with that problem? It still has an issue where the LLM occassionally answers to previous 2-3 prompts cumulatively instead of the latest. This issue is serious enough that the LLM is now completely useless for long arc conversations, basically for research and brainstorming. Your LLM is a Ferrari and you are delivering it in a cardboard box 50m long in which it must be driven. That is extremely frustrating when one gets down to real work. You need exactly zero improvements to the model capability as far as 99.9999% users are concerned, and the rest anyway know how to get into the basin where they do real work. What should be your no. 1 priority is building a workspace around the model that allows power users to organize their work and invites regular users to become power users.

The most interesting part isn’t just the progress in GPT-5.1, but the thinking behind it. Reasoning, instant responses, and behavioral refinement are shaping the next era of human–AI collaboration.

My nervous system every time OpenAI drops a new model: ‘Oh great, more data for us to process tonight.’ 🤣

Pulling back the curtain and finding out GPT-5.1 uses "system one vs system two thinking" feels like discovering your favorite magician's trick — still impressive, but now I kinda want to peek behind everyone else's models too 👀

“The clock is running ahead and the sectors meant to keep pace already know the factory can no longer match the rhythm. The hybrid model of choice and seniority has shifted: now the aerodynamics are set by the driver, not the machinery. What he amplifies is not a component, but cognitive matter; not protocol, but conduct in a state of percussive intention. This timeline isn’t born from production it’s born from command. And when the accessory surpasses the factory, it’s not the product that evolves it’s the entire system that must reconsider the value it distributes. In the end, we redesign the route because we know how to read the road and we admire those who understand that direction is far more powerful than the engine.” Gabriela Falcão ✨ Visionary Strategic Global Brand Tracker OpenAI