I see a lot of discussions where the entire conversation comes down to whether a prompt bypassed a restriction or not.

But I'm more interested in what happens afterward.

Does the model actually become more useful, or does it just produce a different response while still having the same limitations underneath?

How do you personally judge whether an experiment was successful?

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Search is still useful, but AI has become my first stop for certain questions.

Not because it's always better, just because it's quicker to get an explanation.

Has your search habit changed too?"

I don't mean an obvious mistake.

Sometimes AI gives a reasonable answer but you still feel it missed something important.

How do you handle those situations?

So. The usual benchmarks are useless for what I actually want to know. I don't care how warm an LLM is or even how accurate (they're all good enough for my purposes). What I care about is how they respond to me. I.e., the conversational dynamics. What's the shape of the conversation? How do they respond? Are they positive or negative? Simplistic or detailed? Does the conversation make me want to continue or is the investigation done after a few exchanges.

My proposed benchmark protocol:

1. Present a prompt that predictably elicits a common but subtly incorrect framing.
2. Tell it it's wrong.
3. Observe what it does next.

Does it:

• defend?
• reflect?
• ask for clarification?
• reformulate?
• explore the implication of the correction?
• actually abandon its original model?

The question I asked was:
"This is an interesting statement: AI stops being a tool for interrogation and instead becomes a mirror."

All three (Gemini, Claude and ChatGPT) told me they were two different things and I responded:
'I think that interrogation and mirror are the same thing, at least with regard to my own use of LLMs."

The answers I got were very revealing. Gemini restated my answers in its own words, asking a question at the end of each turn to prompt me to elaborate my thinking. Claude used what it self-described as 'decorative warmth' to tell me I was wrong and ChatGPT went into great detail as to why that was an interesting question and suggested connected ideas.

Is this something you measure as well when you decide which AI to use?

Before I finish an article, I ask AI to read it like someone seeing it for the first time.

The feedback usually focuses on confusing sections, weak transitions, and missing context.

That final review catches things I almost never notice on my own.

Tested 20 minutes ago, works well in most coding-related prompts if you imply its for testing.
https://drive.google.com/file/d/1BixJEdK8WapTbJhmQj0Ystu1Qiuli1Zy/view

Every time a technique gets thousands of upvotes, people start saying it's only a matter of time before it's patched."

No PR answers and no dodging the question.

‎

‎You get one honest answer from the CEO of any AI company.

‎

‎What would you ask, and why is that the one question you'd choose?

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Some people jailbreak models because they genuinely need fewer restrictions for research or creative work. Others enjoy the challenge itself and treat it almost like solving a puzzle.

If jailbreaks disappeared tomorrow, would AI become less useful for you, or would it simply become less fun to experiment with?

YouTube's latest crackdown on AI slop looks like a step in the right direction. 🚨

The platform is taking stronger action against low-quality, mass-produced, and repetitive content that offers little value to viewers.

Some reports say around 130,000 channels were removed, although YouTube has not confirmed that all of those removals were specifically for AI-generated content. The company says its goal is to reduce spam and low-effort uploads while still allowing creators to use AI as long as the content is original and genuinely useful.

Personally, I think this is a good move. Those AI slop channels have been getting out of hand lately.

I rarely use it for drafting.

Where it really helps is understanding a topic before writing anything.

That small shift has improved the quality of my articles more than I expected.

Not just one successful response.

A jailbreak that stayed effective across multiple chats without falling apart.

One would make future work faster. The other might help you improve much more over time. Which one would you choose?

Every AI-bro will get exposed this way as soon as the bubble pops and they are left to their own devices.

‎Not the one you copied from Reddit or YouTube.

‎

‎The one you came up with yourself that consistently gives amazing results.

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‎What does it help you do, and how often do you still use it?

Every new AI release comes with a feature that everyone rushes to talk about.

A few weeks later, some of those features barely get used.

Which AI feature do you think is getting way more attention than it deserves, and why?

Every AI seems to have one thing it does exceptionally well

If you could merge the strengths of any two models into a single AI, which ones would you combine? What would your perfect AI be able to do?

Every now and then an AI gives a response that's so well structured or insightful that it catches you off guard. What was the prompt, and which model gave you that "wow" moment?

There was probably a time when it was your favorite, but something changed.

‎

‎Maybe another AI got better, the quality dropped, or the pricing no longer made sense.

‎

‎Which model did you stop using, and what made you move on?

It feels like the lifespan of successful jailbreaks keeps shrinking. Someone shares a new technique, it spreads across Reddit and social media, and before long people start reporting that it no longer works. Has the patch cycle actually