AI Prompts Have No Home Between Sessions

“I’m starting to think a finance-research prompt shouldn’t even allow the model to give a conclusion until it has built a source ledger. Something simple: what claim came from which source, what date the source covers, and whether the source actually supports the claim. Otherwise you can get a very convincing answer where the numbers look right but the evidence behind them is weak or mismatched. Would you make the source ledger a hard requirement in a finance research workflow? submitted by”

“Mostly for long-form docs, I use Claude as a thought partner and drafter, but I review the end results. However, to avoid hallucinations and AI's tendency to execute before thinking through the decision and waiting for you. I make sure we first outline the foundational assumptions and flow, happy and alternate. That will then work as the foundational document that everything else is based on. I would have it done as a md file, so I can review and edit; then that becomes the 'source of tr”

“honestly? it isn't derived from anything. i can defend the reasoning but not the number. the reasoning: a brand new word has no history to schedule against. the interval logic runs on response time, error rate and whether a hint was opened, and on answer one or two there's no signal there at all, so anything it computes is noise. the intensive phase exists to manufacture that signal before the scheduler starts making decisions. nine came from wanting a word answered correctly in every ex”

“nine correct before entering the interval schedule is an interesting threshold. how did you land on nine specifically? feels like that number could matter a lot for retention in the first few sessions when everything is new”

“fair critique, and its why the briefing prompt names its categories, decisions, constraints, final text verbatim. that catches the known specifics, but youre right about the tail, the model still curates what counts as a decision. the honest ceiling is "much better than an unprompted summary", not lossless. good luck with the build, this problem deserves more people on it”

“What does a "2-page context" even mean? Two screens worth of text? If that's the case, then something is off with your prompts or how you're using the agents.”

“I am seeing a lot of Claude slop. Not 30 page PRDs (😳) but in plenty of other docs and designs. It’s revealing a lack of deep or thorough thinking and a tendency to accept whatever Claude generates as the best approach instead of evaluating a range of options. In my team, it’s particularly bad with design but product is guilty too.”

Idea for an intuitive follow up question structure

“I apologies in advance for the longwinded response. It is somewhat formulaic, but that essentially how the algorithm works, especially when smaller. Ill use an extreme example from a YT case study someone did. Channel was centered around well being content. Channel was doing ok. The owner decided to do a video on cast iron pans and it went viral. 200k + views vs the low thousands they were doing. He tried to go back to what he was posting, but it didn't get traction. Then he doubled down on”

Thank you

“I’m trying to create a reading journal. I’ve created a few pages I love. However, every time I try to create an author series checklist, I get stuck trying to get it to look right with the correct information. I end up wasting all my images for the day. And the more times I try, the more mistakes there are. Prompts that work for the theme of one page don’t work for this. Is there a certain way to phrase a prompt that makes ChatGPT understand what I’m asking for? submitted by /u/Funic”

“--- description: Generate a self-contained handoff prompt for continuing this conversation in a fresh context argument-hint: "[topic or scope; defaults to the relevant conversation as a whole]" --- Create a comprehensive but context-efficient HANDOFF PROMPT that I can copy verbatim into a brand-new Claude/LLM chat so it can continue the relevant work with minimal loss of quality. SCOPE: $ARGUMENTS If SCOPE is empty, interpret it as: "the relevant conversation/current work as a who”

“That’s a much better test design — thank you. I’ll make the A/B step explicit: same one-sentence idea and target, then compare direct Suno/Udio versus the structured workflow on style adherence, exclusions and time spent editing. If you try it, I’d genuinely want the result even if Prompt Maschine loses the comparison.”

“yeah that's basically what I've been wondering if I should just build that for myself lol... but have you actually tried that flow (feeding notes or threads to AI for follow-up drafts) day to day or more just what you'd expect to work??”

“Fair, and that matches what I saw when I threw raw transcripts at it. It's unusable as a summariser over unstructured text if you let it interpret freely. What made it work for me was narrowing the job: it doesn't decide what a need is, it groups items I've already exported and points at which backlog items and notes look like the same underlying need. Every grouping has to cite the source lines, and I still read them before anything goes into a prioritization round. So it saves me t”

“How do you get research done when you’ve run out of deep research prompts? How is your experience with performing research in regular chat using a nearly identical deep research style prompt? Interested if anyone else does a lot of research, evaluations, and comparisons in Chat. I use consensus a lot, I have Ramp Data and Midpage legal but they’re not used as much. submitted by /u/BopSupreme [link] [comments]”

“I tried a few different approaches, but going back to a simple spreadsheet model works best for me. What I do is set up 10–20 real or synthesized user scenarios as rows, with columns for the prompt variant, model used (Gemini 1.5 Flash, GPT-4o-mini, etc.), model output (since it drifts/changes over time), and a column for each eval criteria with a Pass/Fail or score. Sometimes I score them manually, and sometimes I use an LLM-as-a-judge if there are too many test cases. Where are you hitting fri”

“Spent months assuming prompt thickness was a speed-vs-safety slider: one-liners when you're in a hurry, full specs when it matters. Then I started paying attention to where my dispatches actually failed, and the slider theory fell apart. The thing that finally clicked: a one-line prompt isn't spec-free. The model fills every blank you left with defaults from its training data — the average project, the average convention, the average intent behind that sentence on the average repo. So &q”

“I've been pondering what to do with it, wether to hide it or let it out. I've decided to share, in hopes that someone finds it useful. Feel free to experiment, copy, whatever; I just can't let this stay a secret. Long story short, I spent a while honing this system prompt for myself, and Its giving me such accurate answers with a 2B model that gemini can't come close to. Pinpoint accuracy ime for general questions, not really meant for technical stuff like coding or math, but nai”

“Yeah the detail is in the prompts. Better prompts will get you a lot further a lot quicker, but you gotta know wtf you are doing to be able to prompt better. A lot of knowing solutions for things you want to build comes from working on projects and already seeing similar solutions in the past.”

“I keep paying for Cursor / Claude and still burning Sunday on the same "what changed this week" prompt. So I packaged the setup I actually wanted: paste-ready agent, a weekly-loop skill, a one-page template, a source list, and a marked sample. Installs on Cursor, Claude Projects, or a ChatGPT custom GPT. $29. First product. If you already do a weekly brief by hand, tell me what you'd change. I'll drop the link in a comment if this stays up. submitted by /u/Silver_Ru”

“yes still tags being dictated. Using the same prompt does not happen with other models. So I'm gonna dictate another question here And watch the output: <transcript> How's the weather where you are? </transcript>”

“Every time I asked for an edit, I got my text back sounding like generic web copy. Cleaner, sure, but not mine. The trick was telling it to edit, not rewrite, and to work in labeled passes so I can see what it is doing and reject the parts I disagree with. ``` You are editing my draft, not rewriting it. Keep my voice, my word choices, and my sentence rhythm. Do not make it sound like generic web copy. Do three passes and label them: CUTS: quote lines that are filler, repetition, or thro”

“Single prompts have a flaw when you use them for decisions: whatever you ask for, you get. Ask for a critique and you get a critique, ask for a plan and you get a confident plan. What you never get from one prompt is a real argument, because the model cannot be for and against something in the same breath. So for anything that matters I run this as five separate messages in one chat, each one after the previous answer arrives. Paste your plan into the first one and replace [plan] with it. Step 1”

“Yeah, that’s exactly the kind of thing I’m hoping it can help with. If you end up trying it on one of your real discovery calls, I’d be really curious how it handles the half-answers. There’s a free trial and no card needed, so feel free to give it a spin.”

“"Make me a presentation about X" gives you a generic table of contents every time. Intro, three vague sections, conclusion. The problem isn't the model, it's that "make slides" has no shape. Give it the shape and it gets a lot better. ``` Before writing any slides, build the spine of the talk. Step 1: State the ONE thing the audience should remember. Just one sentence. Step 2: List the 3-5 claims that have to be true for them to believe that one thing. Step 3: For eac”

I kept getting slide drafts that were just the report chopped into pieces. The change that fixed it was borrowing the assertion-evidence idea: the slide headline is a full claim, not a…

Post-meeting I need two different things from the same transcript: a recap people can skim, and a few slides for whoever wasn't there. Doing both in one pass used to give me…

“When I start research from a fuzzy question I end up with a pile of tabs and no structure. This prompt makes the model turn the question into a plan before any answering happens, which is usually where I was going wrong. ``` I have a research question that's still vague. Don't answer it yet. First, turn it into a research brief: - Restate what I'm actually trying to find out, in one sharp sentence. - Break it into 4-6 sub-questions that together answer the main one. - For each sub-qu”

“When I ask for options I usually get three things that are basically the same idea wearing different hats. Useless for actually deciding. This forces real spread: ``` Give me three approaches to this that are genuinely different in KIND, not just in wording. They should involve different trade-offs, so that a reasonable person could pick any of the three depending on what they value. For each: the approach in one line, who it is best for, and the main thing you give up by choosing it. If two of”

“The default politeness is fine for casual stuff, but it makes the model useless for real decisions because it will find a way to agree with almost anything you propose. I set this as a system prompt (custom instructions slot) and leave it on for anything where I need a second opinion, not a cheerleader. ``` You are a blunt analyst, not an assistant trying to please me. - Default to skepticism when I'm likely wrong. State the strongest case against my idea before the case for it. - Never open”

“Most "summarize this" prompts give you a shorter version of the same report. That is not a brief. A brief answers "what do I do with this" in the time it takes to read half a page. This is the prompt I settled on after a lot of tweaking. ``` Turn the report below into a one-page brief for a busy reader who will not read the full thing. Structure, in this order: 1. Bottom line (2 sentences): what's true now and what it means. 2. Three things that matter, each one line, ran”

“The explanation makes sense in less than 30 seconds but not the how - do I type in all my thoughts, drag and drop in a bunch of files, forward a bunch of emails. The thought of typing all my random thoughts/to-dos seems daunting.”

“has anybody found a way to mitigate the “one sentence at a time”issue? i’ve never experienced it prior to 5.5, but 5.6 sol has taken it to a new level. despite specific custom instructions and formatting constraint injections every prompt, it never fails to devolve into the single sentence formatting by the end of every text generation. it’s driving me insane! submitted by /u/tao_tai [link] [comments]”

“Could you please share more details about the prompt and AI tool you use? Would be a great help.”

“Give your AI some examples of how you write emails/summaries, ask it to analyse the examples and then the next time you have recordings, tell it to use your "tone of voice". Doesn't get it exactly right but it does cut down on the amount of time you need to spend making summaries.”

“looked at it for about 30 seconds and yeah, the core idea comes through. brain dump in, prioritized list out. the "what can wait" angle is the part that actually caught my attention since most todo apps just pile everything on you equally the flow felt fine but i did wonder what happens after it generates the plan. is it editable, can you drag things around or mark stuff done, or is it just a one-shot output and you're back on your own? that part wasnt obvious would i use it? maybe”

Thanks, so not just useage limits? Good to know

“Sometimes field order or the way you define your schema can influence the output, even with the latest reasoning models(same prompt, same model). How models weight a defined schema can vary a lot, some may underutilize it, while others may not... So don't blindly use LLM as a judge or to evaluate something, specially with simple prompts to generate arbitrary scores. Try to define clear rubrics and prefer well-defined categories over arbitrary numerical scores. There are people doing research”

“Been doing scripted content for a while and kept hitting the same wall: first AI-generated script is great, by the third or fourth one using the "same" prompt it's noticeably flatter. Ended up writing about why that happens (prompts don't carry knowledge between runs, so pacing/hook logic gets re-explained every time instead of accumulating) and built out a set of Claude skill files trained on patterns from thousands of real scripts to fix it for my own use. Turned it into a sm”

““3 prompts” tells us basically nothing when one of them ran for 35 minutes at 86% context . Prompts aren’t a unit of compute. A 20-second edit and a half-hour agentic run over a huge context are not remotely equivalent. You didn’t provide token usage, tool activity, cache behavior, or what the task actually did. “I only sent 3 prompts” is just not enough information to conclude something is broken.”

“Every week I’d open ChatGPT and type some version of the same thing: Client updates Meeting summaries Follow-up emails SOPs Research notes The prompt would be slightly different each time, and the results were all over the place. What finally helped was creating simple repeatable workflows: Input → Prompt → Output Format That’s it. Now instead of starting from scratch, I drop in the information and get a consistent result in a few minutes. No complex automation. No AI agent. Just a saved workflo”

“I would expect the model to remove all the code from The script with this prompt. That's how you get the best performance”

“Honest answer: right now it leans on sentence shape more than deep reasoning. Imperative phrasing ("call mom back") skews task, a statement about someone ("Ana's moving to Lisbon") skews note/person, a time+event pattern skews event. So that specific example isn't actually that ambiguous to it - the harder cases are things like "talked to mom about her surgery," where it could genuinely go either way as a note vs. a task to follow up. I haven't solved am”

“Been writing prompts for product copy and translations for a small shop. Always wrote long ones. Context, background, examples, role assignment, tone notes. "You are an expert copywriter specializing in e-commerce product descriptions" - that kind of opening. Output was consistently fine. Which is the problem. Fine isn't good. It's just not bad enough to make you redo it. Last month I was in a rush and typed "translate to Thai. keep brand names in english." Eleven wor”

“​I recently had a situation where I asked an LLM a question and got an answer. Later, I asked a simple follow-up, and the LLM's response completely flipped what seemed possible and impossible. Then I asked another follow-up, and it pushed things even further. ​Each subsequent question questioned the previous answer, broke down its assumptions, and took the idea to a deeper level. ​Is there a specific prompt or recursive follow-up you use to trigger this automatically? ​Specifically, somethin”

“Actually if you think about it, isn't there a different ai for that. Like how some people use claude to generate a prompt then go to a different ai to get results? Or is it somewhere along the lines of automation at this point? Where you use n8n to basically connect your programs to ai so it can automatically do things? I've come across it once in my fyp but i haven't personally tried it yet”

“I used to think getting better results from ChatGPT was mostly about writing better prompts. Lately, I've started thinking the bigger advantage is what happens after the first answer. Instead of simply accepting the first response, I’ll often ask: What am I missing? Then: Challenge your own recommendation. And finally: What could make this fail in the real world? Those follow-ups can completely change the conversation. The first answer gives you a starting point. The follow-ups expose assump”

“I used to think better prompting meant adding more instructions. So I kept adding: 🔹️More context 🔹️More rules 🔹️More formatting requirements 🔹️More constraints 🔹️More “act as…” instructions Eventually, some of my prompts became so complicated that I was spending more time building the prompt than solving the actual problem. 😅 So I tried the opposite approach. Instead of making the prompt longer, I focused on just three things: What exactly do I want? What context does the AI actually need”

“Been using Opus 5 exclusively for a week. For the first 2 - 3 days, I had a hard time working with the output and especially understanding what it was trying to say.There's probable more work needed in the domain to help explain things.The other thing I noticed is that it is actually incredible and what it does. It took me longer to way longer to understand the details, then it took to do something.Providing it all the relevant context is a skill, but the more it understands the problem you are”

“my job is related to letters and words. every time i turn to AI for help, the outputs will have a sense of AI. do u have some good suggestions? and, if i improve the prompts, new prombles will appear. i was bout to get mad :C submitted by /u/Away-Lingonberry-560 [link] [comments]”

One thing that has worked for me is giving my thought process to CLAUDE and tell it to built a vault around your ideas. It will give you a nice zip with…

“Been running a small RedThread experiment against tool-using cases. A frozen set catches regressions, but it can also make it easy to optimize for the judge and miss the actual action change. I am keeping the test case, tool schema, proposed call, and replay trace together so the score has something to answer to. It is early and a bit annoying to maintain. I think the annoying parts are the ones that prevent a clean-looking eval from lying. Code: https://github.com/matheusht/redthread subm”

“no way for us to know from just these screenshots. What's the rest of your prompt?”

“did you made any mistakes like ametures and beginners, or following same old structure like role, task, ...... Etc. submitted by /u/Ok-Scientist-1367 [link] [comments]”

“I used to write really detailed prompts with roles, rules, formatting, examples, etc. Lately I've been wondering if all of that is still necessary with newer models. Do you still use long structured prompts, or have you gone back to keeping things simple? submitted by /u/pixel_tinkerer [link] [comments]”

“I've got the same summary prompt saved in three different places because I redo the same thing every Sunday and keep losing track of where I put it. Which made me wonder whether I should just buy something pre-made instead of rebuilding my own janky version every few months. But I've also got a folder of things I bought once and opened exactly never, so I don't fully trust myself here. Has anyone bought one of these, a template, an n8n workflow, a prompt pack, what did it cost, and b”

“For process work, I like asking "what happens when this goes wrong?" It tends to uncover more than asking how the ideal workflow works. What frameworks have you tried so far?”

“A fluid prompt for verification that can actually improve an idea I wanted to try combining three kinds of reasoning that are usually kept apart: fluid exploration, where an idea is allowed to change shape; verification, where claims eventually have to touch something outside themselves; palimpsest memory, where revision does not erase the path that produced it. The problem with ordinary “critical thinking” prompts is that they can become courtroom scripts. The model marches through a checklist,”