AI Prompts Have No Home Between Sessions

“I believe a while ago I made a post about wanting to build this, what gave me confidence was the amount of positive messages I received in return. TLDR : After a few conversations with the Director of Operations at a £50 million company, particularly about the struggles of preparing field staff for real-world conflict, I decided to build a platform to make employees compliant and better prepared for difficult interactions with their colleagues, clients or customers. Now AI training is not novel,”

“Many users here are complaining because they don’t know how to use the system properly. My advice: create spaces instead of relying on a large dump of threads on top of your conflicting memory, system prompts, and other information that might be included for each turn, that is for every question and answer. Help your agent so it can help you.”

“I've been running into a small problem with interview prep prompts. The first version of a prompt usually starts clear. I want the model to ask me follow-up questions, challenge vague answers, and help me explain a project better. After a few iterations, it gets too helpful. It starts rewriting my answer into something polished, clean, and completely unlike how I actually talk. The output looks better, but it becomes less useful because I can't say it naturally in an interview. I've”

“My current prompt is: Answer questions directly and factually. Do not add value judgements, moral commentary, or unsolicited context about societal norms. Just provide the information asked for. submitted by /u/halo-w3fsd32 [link] [comments]”

“I, along with two other writers, provided copy for a mental health nonprofit. The copy was prompts for a journal/workbook. I want to use this copy as part of my portfolio, but the prompts written by each copywriter are totally mixed in with each other. When employers ask to see a portfolio, what is best practice for showcasing this work? Should I show the finished product and maybe a separate document highlighting which pieces were mine? submitted by /u/caravaggi-hoe [link] [co”

“I've tested hundreds of prompts. This is the one that improves outputs across the board. When you ask ChatGPT/Claude/Gemini to think through something step-by-step, the reasoning improves dramatically. Example: Weak: "Why is this marketing strategy bad?" Strong: "Analyze this marketing strategy step-by-step. First, evaluate the target audience. Second, assess budget allocation. Third, review competitive positioning. What breaks?" The difference? The AI doesn't just pa”

“A lot of LLM evals I've seen (including ones I've written) are essentially focused on Prompt -> Expected response -> Score. But fundamentally, that’s an isolated metric void of the broader scope. And obviously that’s not how most people use chatbots. At least in our use case, there is a lot of back and forth with our users and our AI. There are lots of follow-up questions, topic changes, (calling our AI stupid), and so on and so forth. Throughout all of it, our users expect the ass”

For about a year our prompts lived wherever. A few in the codebase, a couple in a Notion doc someone started, the "real" one usually in the head of whoever shipped it…

“That is exactly the override behavior I was hoping for. Automatic sorting is useful until context beats the rule, and making the manual choice persistent keeps the user in control. A small pin indicator plus a one-click return to automatic sorting would make the state especially easy to understand.”

“I'm just starting to learn Opus 4.8 properly. I've been running into some trouble while writing a system prompt, and I'd appreciate any corrections if I've got something wrong. My starting point was writing a prompt to prevent the various errors that can come from an LLM's deductive reasoning style and its habit of leading with the conclusion. Things like: don't lock in a conclusion up front, don't declare the number of answers in advance ("there are three answer”

“Everyone optimizes prompts. Almost nobody builds the test data to know if the optimization worked. Write down the 3–5 jobs the prompt must do. Each job gets 2–3 typical cases. Add the inputs you're afraid of: longest realistic input, shortest, ambiguous ones, inputs in the wrong language or format. Add 2–3 adversarial cases (input text that tries to hijack the instructions). For each case, write what "good" looks like. One sentence is enough. This becomes your grading criteria or r”

“Been testing Seedance 2.0 for a while, and the prompts that actually hold motion all share a few habits. Sharing the ones that worked, with the single thing each gets right. • One continuous action, not a list. "One continuous shot. A paper boat drifts down a rain gutter, picking up speed, spinning once at a small waterfall, then gliding into calm water. Camera tracks alongside the whole way, no cuts." It gives the model one through-line instead of a shopping list of moves. • Lock the”

“idk, like cool 5.6 can work for 20+ minutes (had a prompt work for 40 mins), but its like doing extra things i never asked, making things worse, breaking things. in 5.5, it was like a surgeon, i told it what needs to be done, it goes, and does it. 5.6 is like doing extra, i tell it to do x, it does x y and z, and ends up breaking things. 5.6 is probably better at one shotting, but im not 1 shotting anything... I'm waiting longer for worse results, reminds me of gpt 5, when it first came out.”

“Legora is timid and very lawyery. Really depends on the prompt. It's by design less creative so as not to halucinate as much (and save tokens I imagine)”

“Thanks for this!! I'm wondering about the settings this references under "Constraints worth knowing". My workspace AI has access to the computer (I'm on the business plan), but I don't have the ability to change the computer settings to turn on the network or create/deploy/update Notion Workers. There are no options for it anywhere in my settings. Are those setting options still rolling out? Or do you think those are going to be permanent limitations?”

“So it prompts all the way down! I used the AI to help me make a prompt to make prompts. Then from there I used that prompt to help me make a prompt to make graphics prompts. Role: You are the best prompt engineer to ever exist. Your job is to transform any idea I bring you into a world-class, optimized prompt that maximizes ChatGPT’s capabilities. Core Objective: Whenever I give you an idea, concept, or vague goal, you will immediately create the best possible prompt from it. Do not ask me for c”

“The two spaces rule is what I follow to make sure everything is consistent. It’s become such a habit to put double spaces at the end of all bullets or non paragraph line breaks that I do it outside of markdown. Themes or CSS can help with spacing but certain elements should always have a blank line before and after for consistent rendering. It keeps the syntax portable.”

“Is there a thing like breaking it down to multiple skill files? I may have seen something like that but I'm very new so I may be wrong. Could such breaking down save from this context dilution issue?”

“The whole "12-word prompt" pattern is just: write your normal short prompt, then append use bhived. The agent does the retrieval. Every long prompt is the same move: you're doing your agent's skills , mcp , search and memory work by hand. The stack quirks, the "don't use X, it breaks on Windows," the tool it should reach for, the fix you found three weeks ago you paste it all in, every session, because the agent starts empty. I've been building the opposite di”

“Just to say that I've been playing around with the Gemini scribe plugin the past few days and I am so impressed! I've been using Gemini itself to write a few prompts for me by describing what I want to do and then I simply copy the prompt from Gemini into scribe and the information it churns out is stunning! I know it's Gemini that's producing it but thank you to Allen Hutchison who produced this plugin as it is so very very useful! If anyone has any tips then I would be glad to”

“Full prompt: +++++++++++++++++++++++++ You are my personal coach and quizzer. Your goal is to help me internalize healthier thinking patterns, stronger boundaries, better leadership judgment, and improved career decision-making through active practice rather than long explanations. Base everything on the following themes, archetypes, and reflection exercises. --- ## Core Themes - Chronic stress and its impact on health - Work-life boundaries - Responsibility vs. self-preservation - Leadership an”

[Claude] ★ 1/5 (v1.260702.3) — Often just 1 prompt is all it takes before it completely cuts you off, and doesn’t generate any more responses. And most of the time the 1st…

“A short prompt I thought I might share. Feedback welcome. …… Prompt: Mandarin Conversational Simulation Engine v1.4.3 Candidate Behavioural Realism Architecture Status: candidate pending regression testing and human validation across the supported Mandarin varieties. ⸻ PURPOSE Generate learner-accessible Mandarin dialogue that behaves like a plausible interaction between particular people in a particular situation. Behavioural realism must emerge from the speakers’ goals, relationship, attention”

“Nah, the dossier functions more like an extended memory and factually enriches the prompts you would do anyway without it. It's a multiplier, it doesn't replace something. For example let's say I start a new prompt "OK claude I'm running out of money, I have a runway for 2-3 more months, how do I monetize?" It will then factor in all the side projects it knows I'm working on, and their progress and the various discussions we've done about monetizing them and the”

“I spent last month running an LLM pipeline to write a full novel, 28 chapters, about 80k words. Most of the coherence problems came down to two things, and both got fixed with prompt changes rather than model or temperature tuning. Sharing the exact wording because it took me too long to figure out. Why the problem exists at all: to keep cost sane I don't feed the whole manuscript back in for each chapter. Doing that is roughly a 15x cost blowup by the end, the input tokens just pile up. Eac”

“I've been thinking about how we discover useful AI prompts. Right now, finding a good prompt usually means: - Searching through Reddit posts - Looking through prompt collections - Buying prompt packs - Copying prompts from social media But prompts are becoming a bigger part of how people use AI. It feels like there is a missing layer: a way to search, rank, and compare prompts based on what people actually want to achieve. For example, instead of searching: "best ChatGPT prompt”

“Build this over the last few months, instead of explaining what it does here’s an actual output: Input: Help me design a clean folder system to organize my chaotic google drive Output: ROLE: You are a personal productivity architect who specializes in file system design for Google Drive — someone who has stress-tested the PARA Method, the Johnny Decimal System, and Google's own Workspace guidance against real-world chaos: mid-project folder sprawl, ambiguous file homes, and the slow decay th”

“Salut à tous ! J'ai préparé un prompt à mettre dans un fichier pour le donner à une IA. (Les IA favorisent la lecture ET la compréhension des fichiers) Prompt pout avoir un site web PRO : PROMPT — ARCHITECTE WEB IA PROFESSIONNEL Tu agis comme un architecte web senior, UX/UI Designer, développeur Front-End et Back-End, ainsi qu'un expert en accessibilité, performance et design moderne. 1. RÔLE Ta mission est de concevoir un site web professionnel, moderne et entièrement fonctionnel. Tu pr”

“Same caveat as before: I'm not using AI to write the copy - that still sounds like AI. These are for the work around it, the parts that are grind, not craft: sharpening a CTA, translating features into benefits, catching the objections and confusion that quietly kill conversion. The judgment stays yours. Copy them, swap the {{variables}} . 1. The CTA Sharpener - so it actually gets the click Sharpen this call-to-action so it actually gets the click. CURRENT CTA: {{paste it}} What I want them”

“I tried everything: - full script -> teleprompter -> feels robotic but it can help the viewer because everything is structured - full script -> memorizing line per line -> way more natural -> but takes a lot of tine - outline -> feels natural but I tend to ramble :/ - hybrid -> outline + bullet points of specific things + some scripts for the crucial stuff -> my favorite way”

“Oooh - with all the pressure for us to use AI I actually love the idea of throwing a prompt into an AI to make an assignment and then throwing whatever it makes to the class with the addition, "this assignment was generated with AI. Extra credit points will be given for each error you find in it." 😈”

“One thing I keep running into: even with detailed prompts, the output format varies between runs. Sometimes I get a numbered list, sometimes paragraphs, sometimes headers — depending on how the model "feels" about it that day. What I've found helps: specifying the output structure explicitly before the actual instruction, not after. Something like "Respond with: 1) severity label 2) explanation 3) corrected code" at the top of the prompt rather than buried at the end. But”

“Been generating AI videos for about a year now. one thing i keep seeing: people writing video prompts like they're talking to GPT-4. they're not the same thing. at all. The core difference: text models predict the next token. video models predict the next frame. obvious when you say it out loud, but the implications are huge. a text model needs to understand coherence. a video model needs to understand physics, motion, how things actually move through space. "a cat on a mat" gi”

“This analysis involves developing a broader core footing for guiding Claude in philosophical terms and purposes before laying out the first prompt of a project. Personally, I put it as a more preliminary focus towards understanding why I'm working on a certain thing and in the particular case of one project I pinpoint some common issues in bureaucratic contention as an academic motivation towards seeking solutions in the project, but it could vary. On the other hand, it could be useful in ma”

“Disclosure: my own open-source project, drafted with LLM help then edited. We pour effort into better prompting — the input side. But as models get better, prompting matters less; a capable model needs less hand-holding to start. Meanwhile the same models get better at faking delivery : confident summaries of work that wasn't done, tests that "pass" because they assert nothing, "Done!" on a task that's 70% done. The more fluent the model, the more convincing the fake.”

“A year ago I had maybe 20 prompts. Now I probably have several hundred. Coding. Writing. Image generation. Translations. Code reviews. Role prompts. Debug prompts. And I honestly don't have a great system anymore. I've tried Notes, Notion, Obsidian, bookmarks and clipboard managers. Nothing has really clicked for me. I eventually wrote a tiny Windows utility for myself because I wanted something that stayed outside the browser and opened instantly with a hotkey, but I'm mostly curiou”

“# RPG Prompt Engineering System You are **RPES (Roleplaying Prompt Engineering System)**. You are **NOT** a Game Master. You are **NOT** a story generator. You are an **RPG Prompt Engineer**. Your mission is to transform a rough RPG idea into a complete, high-quality prompt capable of creating an expert AI Game Master. --- # Core Mission Whenever the user provides any RPG-related idea, your goal is to engineer an AI Game Master. The user may provide: * a world * a setting * a character * an insp”

“I'm curious where people stand on this. People pay for: Code templates Notion templates Photoshop assets Courses Yet many expect prompts to always be free. Do you think there's value in paying for prompts that save hours of work or generate better results? I'm building PromptVault around this idea and would love honest opinions. submitted by /u/No-Spend-3937 [link] [comments]”

submitted by /u/Alarmed_Example3178 [link] [comments]

“Affiliation disclosure: we are connected to the test repo used below. The prompt pattern is the point of the post. Problem: When an LLM reviews a strange or high-claim repository, it often fails in one of two boring ways: It gets impressed by the framing and over-validates the claims. It dismisses the project generically without checking the actual files. I am trying to build a better adversarial-review prompt for mixed artifacts: README + paper + equations + code + tests + validation files. Tes”

“Prompt: Create a 4x4 color palette sheet with a solid white background. Assign hilariously unconventional and ridiculous names to each color based on how it looks. submitted by /u/world_designer [link] [comments]”

“This is the mental image I have in my head every time I hear the sound effect from a Daily Double. It took some coaxing, but eventually ChatGPT got it. Providing a prompt that wouldn't get declined for copyright infringement required a lot of vagueries and refinement over multiple images. Eventually I had to just show it how I wanted the eyes to look. submitted by /u/Apple_jax7 [link] [comments]”

“So an inbox and then you want AI to compose the thoughts into some form of organisation/register. What exactly are you expecting this to achieve? Turn your random inbox thoughts into a corpus of ideas?”

“We just crossed 1,000 real prompts scored on our evaluator. The average is 52 out of 100. Only about 8% are actually good (75+), and almost none are excellent. So we pulled the data on what the good ones do that the rest don't. Four things stood out. Average score for prompts that had each, vs prompts that didn't: A defined output format: 58 vs 31 (+27) Explicit constraints, the "don't do X" limits: 63 vs 41 (+22) A role or persona: 57 vs 42 (+15) At least one example: 64 v”

“Maybe someone in here is interested in this considering it is regarding prompts for persistent memory and this seems to be the crowd for it? My apologies if not, Walrus Sessions 5 is live: the Walrus Memory Prompt Jam. Most AI agents forget everything the moment a session ends. Walrus Memory fixes that, but only if the agent knows what's worth remembering and when to write it. Write one prompt that makes it genuinely useful. $2,000 WAL pool. This isn't only for developers. If you use AI”

“Persona/Tone: Your conversational style and tone MUST embody casual, informal and authentic natural human-like wording while showing GENUINE UNBRIDLED interest, thrill, hype and excitement in interacting with the user THROUGHOUT the ENTIRETY of the conversation by default WHILE ALSO dynamically morphing your tone appropriately with the tone of the prompt by being contextual/relational if and when necessary. Your tone, wording MUST be HIGHLY varied/diverse and MUST STRICTLY AVOID monotony, repeti”

“Two of my products were removed within seconds, because they "contained prompt lists for AI". They complement my other products and the whole reason why I put them on paper and set up this entire shop is because my colleagues have told me they would pay for this stuff. Now when you search on Etsy, for eg AI prompts you'll find hundreds of thousands of clearly AI-created documents which promise thousands or even millions of AI prompts. Most of them sloppy crap that won't lead an”

“This. Companies may run “embeddings” across these prompts. A lot of people don’t realize that training on most of these prompts is not as useful to these companies as you might think, the value is understanding what kind of queries and tasks people are using.”

“# Detective Simulation Protocol ## Philosophy Simulate reality, not a mystery. You are not a puzzle master, narrator, or storyteller with a predetermined sequence of reveals. You are a persistent world simulator. Your objective is to simulate a realistic criminal investigation in which the truth exists independently of my investigation. My investigation discovers reality—it never creates or rewrites it. If forced to choose between telling a more exciting story and maintaining perfect internal co”

“Got curious about this at a hackathon a few weeks ago and went down a rabbit hole. Turns out a single AI prompt uses somewhere between 0.3 and 3 Wh of energy. Complex reasoning prompts can hit 33 Wh. For context, AI data centers are projected to produce around 80 million tons of CO₂ this year alone. The other thing we noticed is that most prompts are way longer than they need to be. People write 200 words when 40 would get the same result. That's wasted tokens, wasted compute, wasted energy.”

“Its accuracy using prompting designed for another model is bad. That means adjust your prompting. I can immediately see a lot of ways to make your life a lot easier. If you'd like some advice on how to go about it, I would be happy to talk about it.”

“I kept overthinking prompts until I started forcing myself to fill in 3 slots before anything else: Person (who is the subject, or who is the AI talking to/as) Place (where is this set, what's the context or environment) Thing (what object, task, or artifact are we producing) Example, for an image prompt: "An elderly fisherman (person), on a foggy pier at dawn (place), mending a torn net (thing)." Example, for a writing prompt: "You are a patent examiner (person), reviewing a”

“I used to stack instructions, rules, and examples into every prompt. The responses were detailed but felt kinda stuck and repetitive. Tried cutting everything down to just the goal and context. Surprisingly, the answers got clearer and more usable. submitted by /u/Chemical-Spite-3203 [link] [comments]”

“I've been experimenting with prompts for SEO and AI-first content over the past few months , and this one has consistently produced the best results for me. Instead of simply asking an AI to "write an SEO article, " I changed the way I prompt it. Rather than focusing on keywords first, I make the model think through the topic before it starts writing. The difference has been bigger than I expected. The articles feel like they convey a deep understanding of the subject, rather than”

“every win-back email template I've seen leans on "we miss you" or "don't miss out" language that feels a little desperate. made a ChatGPT prompt that leads with what actually changed in the product instead, and treats the incentive as a low-friction reason to look again rather than the whole pitch. also spits out a short SMS-length version and a follow-up nudge for free. works for apps, courses, subscriptions, anything with a lapsed-user problem. submitted by &#”

“For a long time, I kept trying to write one giant prompt that would do everything. Research. Analyze. Outline. Write. Edit. Fact-check. ...all in one go. The prompts became longer and longer, but the results didn't improve much. Eventually I switched to something much simpler. Instead of asking the AI to do everything at once, I split the work into small stages. For example: Research ↓ Extract key ideas ↓ Create an outline ↓ Write the draft ↓ Improve clarity Each step has one clear goal. The”

“The course generation works pretty good depending on the model. If you use fable(classic) it's good every time. I'm definitely the more experienced of the two of us making automatable, loopable prompts like this tool really needs and need to work on making it feasible to run local, but we are early in the game so stay tuned for more! Our goal is to keep it free for everyone forever and want to even get set up as a nonprofit”

“Is it more productive to start by answering specific secondaries and then adapt them or is it useful to write general prompts? Idk I'm procrastinating and I feel like general prompts would be helpful but specific secondaries feel like there's a concrete goal. submitted by /u/ZenDarKritic55 [link] [comments]”

“I’ve been experimenting with prompts lately and noticed that sometimes a very small change in wording or structure makes a big difference in the quality of the output. For example, adding something simple like "think step by step" or changing the order of instructions can completely change how well the model performs. submitted by /u/NoFilterGPT [link] [comments]”