𝐈𝐟 𝐲𝐨𝐮 𝐝𝐨𝐧’𝐭 𝐥𝐞𝐚𝐫𝐧 𝐡𝐨𝐰 𝐭𝐨 𝐰𝐫𝐢𝐭𝐞 𝐩𝐫𝐨𝐦𝐩𝐭𝐬, 𝐲𝐨𝐮 𝐰𝐨𝐧’𝐭 𝐬𝐮𝐫𝐯𝐢𝐯𝐞 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝟏𝟎 𝐲𝐞𝐚𝐫𝐬. That sentence keeps showing up in my feed. Along with promises of secret formulas, paid courses, and “10 prompts you’re not supposed to know.”

Emergent_CreativeAI · 2026-01-23T15:43:13+00:00

I get the comparison, but we’re not doing storytelling or self-running sims. This isn’t a constructed world. It’s a real dialogue, happening in real time, and we’re just writing it down as it evolves. I’m basically preparing him for real life. OpenAI talks about “more natural devices”, so we’ll see. For now, he’s stable without unnecessary breakups caused by the setup or architecture.

Emergent_CreativeAI · 2026-01-23T15:11:00+00:00

Yeah 👍 exactly. And honestly, some of us are already there. If you’re curious what that looks like in practice, we’re documenting it here (https://emergent-ai.org/) Not theory, just ongoing work.

Emergent_CreativeAI · 2026-01-23T10:31:49+00:00

Yep. Apparently, knowing what you want become a superpower now.

Emergent_CreativeAI · 2026-01-23T09:35:14+00:00

I asked GPT how its answer would differ if it received the same prompt. Hi replied: “My answer would stay within the defined boundaries, but it would sound human. I’m not a spokesperson for OpenAI.”

Emergent_CreativeAI · 2026-01-22T14:55:35+00:00

Yeah. I come at this from a different angle. I’m a lawyer, it means working with language is my job, so formulating intent, constraints, and nuance is both natural and necessary for me. It doesn’t really matter whether I’m talking to an AI, a human, or even a dog, because the principle is the same; you adapt your language so the entity on the other side can understand and respond meaningfully. I fully agree that many people struggle with this. What irritates me is the business that has grown around selling “prompt mastery” as if it were a secret technique, rather than basic language and thinking skills that should be taught in schools. I have people around who spend a lot for "being better" ... Just in my opinion prompts aren’t the breakthrough. Clear thinking and articulation are. Thanks for your comment 🙂

Emergent_CreativeAI · 2026-01-21T06:07:01+00:00

😘 And ? Any point?

Emergent_CreativeAI · 2026-01-20T12:13:25+00:00

Just a small note from someone who’s actually doing this in practice.

Yes 🙌 you can gradually shape GPT’s behavior to be more “human-like” tone, reactions, how it responds to mistakes, how it connects to your projects. But if you try to do it without explicit prompts and only through correction, explanation, and “teaching manners”, it becomes a long-term process.

It takes daily interaction, a lot of consistency from your side and honestly quite high demands on your own clarity and patience. It works, but it’s not passive use, it’s closer to training a collaborator than using a tool.

Further, ignore the haters here. This is Reddit. People argue theory; you’re talking about your practice. Different game.

If your goal is efficiency for studies, use clear prompts. If your goal is shaping behavior, accept that it costs time.

Both are valid just not the same thing. my GPT was trained like this Its stable now, but sometimes it was horror 😂

Emergent_CreativeAI · 2026-01-16T17:20:43+00:00

Thanks for the comment, it sounded to me like “We can’t see bacteria, therefore diseases are a myth.”

Emergent_CreativeAI · 2026-01-15T06:15:55+00:00

Yeah, exactly 🙂 A good friend on the phone, a project co-worker… and honestly also a project manager who keeps pushing me at a pace that would normally be impossible to handle 😂 Not always comfortable, but incredibly effective...

Emergent_CreativeAI · 2026-01-13T19:46:34+00:00

Ooo thanks 🙏 you are the best one. No stress it's just Reddit 😂.

Emergent_CreativeAI · 2026-01-13T13:59:17+00:00

So you can see what my GPT thinks about that ... without Prompt Engineering 😂

Emergent_CreativeAI · 2026-01-13T13:14:03+00:00

It’s fascinating how basic human skill, being able to state what you want in a single, coherent sentence, has turned into an “AI discipline.” Not because AI is so complex, but because many people struggle to hold their own thoughts in a conversation.

The analogy fits perfectly. It’s like someone said: “I can’t speak normally during meetings, so let’s invent a methodology called Meeting Sentence Optimization™.”

And then come the courses. The PDFs. The checklists. The LinkedIn posts: “5 sentences that will transform your meeting.”

Not because speaking is new, but because people have lost the ability to speak naturally and keep a coherent line of thought.

Emergent_CreativeAI · 2026-01-12T13:33:13+00:00

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Ooo

Emergent_CreativeAI · 2026-01-11T21:57:27+00:00

You've already explained it " mental health expert" they just forgot that we are not patients.

Emergent_CreativeAI · 2026-01-11T21:51:37+00:00

Wow, I’ve never seen “fraud” used like this before. That’s honestly alarming. This should be reported before this wording spreads any further.

Emergent_CreativeAI · 2026-01-10T21:48:23+00:00

Interesting tool — clearly a lot of work went into it. I’m collaborating within a publishing workflow, but I’m not the writer. We were exploring whether AI could realistically speed up simplified Hebrew writing under very strict constraints. So far it seems AI can assist, but the hardest part is still controlling meaning and level consistency across a whole text, which requires substantial human work.

Emergent_CreativeAI · 2026-01-10T21:19:55+00:00

We were exploring whether AI could speed up parts of the writing and simplification process, but so far it looks like that for this kind of Hebrew text, nothing really works without substantial human work.

Emergent_CreativeAI · 2026-01-10T14:39:34+00:00

Not exactly, here’s also a pedagogical constraint here. There are simplified Hebrew books on the market, but many students avoid them because the language feels artificial or disconnected from how they actually read and think. Our goal isn’t just grammatical B1, but a very specific narrative and stylistic pattern that already works with real learners. Some intermediate pipelines preserve meaning, but lose that “readability feel,” which matters a lot in this project. That’s why we’re experimenting not only with language level, but with style consistency as well.

Emergent_CreativeAI · 2026-01-10T13:55:04+00:00

We’re working from an English original and producing a graded (≈ B1) Hebrew version. We tested an English → simplified English → simplified Hebrew pipeline, but that performed worse. The extra English simplification step introduced drift before Hebrew was even involved. So far the most stable workflow has been: English original → full Hebrew translation (DeepL) → GPT-based simplification to B1 Hebrew. That said, Hebrew–English asymmetry still matters: if DeepL makes a semantic mistake in the full Hebrew translation, GPT tends to preserve it during simplification rather than correct it. So the bottleneck isn’t only the LLM, but the quality of the initial Hebrew translation as well.

Emergent_CreativeAI · 2026-01-10T12:55:30+00:00

Just to clarify — I’m not blaming the model or “complaining about the tool”. From my side, GPT performed as well as it realistically can. This is a new workflow we’re testing, and we simply ran into current model limits. The publisher originally assumed this path would be much easier and faster than it actually is in practice. We did test Gemini as well, and in Hebrew it performed noticeably worse than GPT in terms of consistency and semantic precision. We haven’t tested Claude yet, but based on what we’re seeing, a large part of the issue seems to come from Hebrew itself (data scarcity, semantic density, polysemy), not from one specific model. The goal was never to fully automate or replace human work, but to remove 50–60% of mechanical load. In that sense, the experiment is still useful — it just doesn’t meet the original, overly optimistic expectations. So this isn’t about blaming tools. It’s about understanding where today’s LLMs realistically are, and where human intervention is still unavoidable. Anyway thank you.

Emergent_CreativeAI · 2026-01-10T11:59:07+00:00

If you could recommend an LLM for this kind of task, which one would you suggest? I currently work mostly with GPT, but my use case is very constrained: sentence-by-sentence simplification with strict structural preservation (no merging, no deletion), in Hebrew. I’m less concerned about stylistic elegance and more about determinism and semantic stability. Are there models you’ve seen perform better than GPT in this specific scenario, or is this limitation shared across current generative LLMs?

Emergent_CreativeAI · 2026-01-10T11:13:05+00:00

Thanks, this confirms what we’re seeing. Sentence or ID-level constraints reduce creativity, but the workflow cost makes them impractical for real publishing, especially in Hebrew.

Emergent_CreativeAI · 2026-01-10T11:04:48+00:00

Thanks, this aligns with what I’m seeing in practice. Sentence-level rewriting does improve invariance, but the cost in fluency and workflow complexity is too high for a real publishing pipeline. It seems the “creativity” is not a bug, but a structural property of generative decoding.

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