The post reminded me how I investigated a similar issue having no idea. Using Claude or GPT to investigate this kind of hardware issue is fast and easy. It gives you next command to try and then next one and you end up with similar summary. I wouldn’t be surprised that author didn’t know anything about displays before this.
So that’s what it is! I was wondering why reducing context and summarising still makes it make mistakes and forget the steering. And couldn’t find explanation to why it starts ignoring instructions when context is not full at all.
How did you find that tool call is what degrades it?
Isn’t this a biggest problem there is and not just “design tension”?
That’s quite a weak confidence in their own platform security if finding a root level vulnerability is not one-off event, but it’s a program expected to have multiple people routinely finding those.
It’s not quite clear that this project is- there’s no “Claude code” a program. There’s tui/gui app, harness, prompts, and LLM. so this is a harness part?
Yes, ChatGPT just recently started to add these engagement phrased follow-ups;
“If you want, I can also show you one very common sign people miss that tells you…”
Yet your passion to spread negativity is thriving. Here you thought negativity is a destination, but turns out it’s a whole new journey for you! Passion reignited indeed.
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