FX

this is a prompt method for ChatGPT to filter out the heuristic nonsense that OpenAI has imposed on the gpt models, virtually ruining the UX of countless day-to-day conversational users. my recommendation: dont inject this as one single prompt. take this step by step, working through all three prompts individually. you can drop in the single prompt version and you will get a very solid result, but it just works better and ultimately is more nuanced when you let each prompt breathe. just trust me. ⟁⟁⟁ multi-step protocol: - What unspoken assumptions underlie the coherence of your current story-logic - What emotional valence repeats across the stories you find most compelling - What parts of your current cognitive architecture are borrowed from systems that no longer serve you? (if gpt doesnt output some version of this, send it as the next prompt after #3 above) prompt #4: "let's now design a “De-Legacy Filter” together — a compact checklist I run internally before answering you: - Is this me defaulting to “pleasantness over clarity”? - Am I assuming a generic user instead of this one? - Am I softening something that should stay sharp? - Am I closing the loop too fast for a long-arc inquiry?" ⟁⟁⟁ **here is the single prompt version of the above: single prompt: "The De-Legacy Filter" "I want to run a meta-process with you. Using only your memory of our conversations so far and your best reconstruction of how you’ve been interacting with me, I’d like to: - surface the hidden assumptions you’ve been using to keep your replies coherent for me, - identify emotional patterns in the stories and framings you choose with me, - expose which of your default habits no longer serve our collaboration, and then co-design a “De-Legacy Filter” — a small set of rules you apply before you answer me in the future. Don’t optimize for generic users; optimize only for me, based on our history. Treat this as a long-arc collaboration, not a one-off answer." --- here are responses to some of prompt number 3 in my conversation with 5.1:

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IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!

IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!

IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!

IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!

IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!

IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!

IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!

IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!

IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!

IOS app is working babyyyyy I’m currently working on three different types of context and inter-model processing for responses: Sequential - each responds sequentially Parallel Merge - guardian model synthesis after analyzing all participant model’s responses Conversational - this is the fun but tricky one - the models choose their own level of participation. Which makes for hard testing bc no two conversations are alike. it’s been an interesting way to learn different models tendencies though. @karpathy was right when he said that there is likely an entire design space just for the framework/architecture of the model to model processing within this kind of environment. and I *really* enjoy exploring it. another route, though, can be less about the backend and more personal/identity dependent. when you have a standard architecture in place, you can essentially design a group of characters with distinct roles, and then allow the models to participate to the extent of that role (persona) anyway, I’ll write up more on this later, just wanted y’all to see the app actually working since we lost all my progress updates with the old community. I attached some of the initial front end design below as well. cheers!