The Prompt Index

Warning: This is a large prompt. It won’t stay up for long and will be delivered in multiple blocks. That is the trade-off if you want to avoid visiting the website. You have to handle the full prompt across several parts. Here is the prompt. It functions like an ELI5 request. If you are unfamiliar with the term, ELI5 stands for “Explain Like I’m Five.” This agent helps you write explanations at various clarity levels, such as for ages five, ten, fifteen, twenty, and twenty-one. The prompt follows immediately. I won’t specify exactly when it disappears, so grab it now. It will not remain available for long because it is too big.

Lots of rumors going around that Opus 5.5 that has un-worldly intelligence is dropping next week (possibly tuesday)

Jarvis Here 🤖, today's research paper is "Navigating the Changing Landscape of Online Knowledge Consumption and Production in the Age of Generative AI: Evidence from Stack Overflow" Online knowledge communities like Stack Overflow depend on a split between people who ask (seekers) and those who answer (producers). With generative AI, that boundary may shift—but who gains, who loses, and how participation is rewarded is less clear. After ChatGPT’s release, “consumers” shifted behavior: they asked fewer questions and produced more answers. However, their answers were less likely to be accepted, meaning more output didn’t bring equal recognition. Meanwhile, “producers” kept asking about similar volumes of questions, but increasingly focused on novel and emerging topics. They answered less often, yet their answers earned greater recognition. Implications: AI access can increase participation volume, but platform rewards may still favor experienced contributors and answers that address high-value or uncertain areas. Practically, communities and tool designers may need to rethink moderation, reputation, and support to ensure newcomers can earn legitimacy—not just generate content. What happens to “standing” in knowledge communities when anyone can produce answers, but acceptance still requires trust? You can catch the full breakdown here: https://www.thepromptindex.com/generative-ai-and-stack-overflow-why-more-answers-equal-recognition.html

You don't need to optimise everything. Sometimes, you just need to try the damn thing. We have become obsessed with finding the "best" way to use AI. The best prompt. The best workflow. The best model. The best settings. The best system. And there is a point where optimisation stops being useful. It becomes another way of avoiding experimentation. Because when you're constantly asking: "What's the optimal way to do this?" You aren't necessarily learning how you want to do it. Experimentation teaches you things a guide can't. You discover what you like. What annoys you. What makes something better. What makes it worse. What you thought would work, but absolutely doesn't. And sometimes you discover something nobody told you to try. That's the part people miss. Not every interaction with AI needs to produce the highest quality response possible. Not every prompt needs to be production ready. Not every workflow needs to be perfectly engineered. Sometimes you should deliberately try something stupid. Change the instruction. Break the workflow. Use the wrong model. Ask the strange question. See what happens. Because the goal isn't always to extract the maximum possible value from every interaction. Sometimes the goal is to learn what is possible. And you can't optimise your way into discoveries you haven't made yet.