Interested in folks who have played around with this and had success in getting it to generate longer form narratives. Any strategies for keeping a narrative "on track" and remembering context you give it?
I just experimented with it. I couldn't get ChatGPT 4.5 to generate what I wanted, probably due to censorship or rate limits (ChatGPT Pro subscription); but Gemini 2.5 Pro Experimental did the trick.<p>This is the end result:
<a href="https://medium.com/@robertolupi/how-beelzebub-was-born-92352a2e637e" rel="nofollow">https://medium.com/@robertolupi/how-beelzebub-was-born-92352...</a><p>If you like it, please upvote on HN: <a href="https://news.ycombinator.com/item?id=43599273">https://news.ycombinator.com/item?id=43599273</a><p>This is the conversation: <a href="https://g.co/gemini/share/21bbaae2a26e" rel="nofollow">https://g.co/gemini/share/21bbaae2a26e</a><p>I switch mid-prompt from Italian to English. It is interesting to see that Gemini reasoned in English even when writing back the initial answers in Italian.<p>Basically, I gave a somewhat exhaustive but generic track then asked it to give enough information to create a theatrical piece. I provided some stylistic references. A piece suitable to create a script for a tragedy is less abstract than the average output of a LLM, and forces it to create characters.<p>Then I asked to rewrite it as a short story a couple of time, asking to make adjustments (add more details and action, less abstract ideas) until I was satisfied.<p>I think I'd consider using NotebookLM or RAG-based, if I wanted something bigger and coherent.