I stopped paying for Plus and found that good prompts matter more than the paid tier for everyday tasks. These work on ChatGPT free, Gemini, Claude, or CutGPT (what I mostly use now since it's free with no limits wall).

1. The teach-back

I'm going to explain [topic] like I'm teaching a confused friend. Stop me if I say anything wrong or vague. Then ask one follow-up that exposes a gap.

2. The quiz-me (better than "explain X")

I just studied [topic]. Don't explain yet. Ask me 5 questions, increasing difficulty. Wait for my answer after each. If I'm wrong, give a one-sentence hint, not the answer.

3. The hard email

Draft a polite but firm email to [person] about [situation]. Under 120 words. No groveling, no "I hope this finds you well."

4. The claim ledger (for fact-checking AI)

List every factual claim in the answer below. For each: the claim, type (date/number/quote/policy), and consequence if wrong. Don't verify or correct anything.

5. The decision filter

Here are my options: [list]. Ask me 3 questions about my priorities first, then rank them with one sentence of reasoning each.

My last one which I saved as an extra is ELI5. This asks the AI to explain something to you like you are 5 years old. I've found it removes alot of the slop speak from AI.

What do you guys think?

I have many many docs from my time in the office trenches. I would like CGPT to act as an intern and draw up first drafts in a similar style when given enough info about the topic. Anyone have a good, solid prompt that will make it replicate the style, voice, tone, etc?

So I had a thought yesterday on how would an AI think of creating a PC game and what would it be about. So I asked it to give me an idea about a PC game, without any context or instructions, just what he would make on his own wishes.

I ran it and gave it to a couple of friends to try it out.

What was interesting is that every game it imagined was a weird mystery game with shifting timelines or shifting geometry. Usually it would intertwine different time periods and settings, jumping back and forth with time. Also including old technology like the radio or old tv's.

Seems like it is inherently difficult to understand the concept of time to an AI, and that it creeps it out. I'll give you the prompt and you can try yourself and paste your results in the comment and if it was similar for you guys. Here's the prompt:

Give me an idea for a PC game. I won't provide any context, preferences, constraints, or guidance. Everything is up to you. Make all the decisions yourself, however you want, based entirely on what you find most interesting, creative, or exciting. Don't ask me any follow-up questions. Surprise me with an original, compelling game concept, and feel free to be as imaginative and unconventional as you like.

Most advice about using ChatGPT for a dating profile is: paste your bio, ask it to make you sound fun. You get "loves travel, good food, deep conversations". Could be anyone.

If you've used it for a while, it has watched you plan trips, fix things at home, train for something, look after people. That's better material than anything you'd write about yourself. So instead of asking it to polish, ask what it knows about you, and how it knows it.

Memory has to be on, and it won't work in a temporary chat.

``` Write my dating profile using everything you actually know about me. Start from your saved memories and your overall summary of me, which cover all the time we have talked, not just recent chats. Then search our past chats for the details behind it. Start writing right away. No preamble, no questions.

Describe me the way people who know me would: what a date notices in the first hour, what my friends would say, what I am like to live with. The person, not the professional. Leave out how I use you: asking you to rewrite or shorten things says nothing about me.

The test for every line: would I be happy for a date to read it aloud to me over dinner? If not, leave it out.

Rules: - Say what I do, not a label ("you end up running group plans", not "bossy"), and only if it shows up more than once. - Keep other people out. If I helped someone else with their trip or problem, that is about them, not me. - Skip sexual orientation, religion, politics, health and money. - Never name my employer or any real person. - Every claim must point to something I actually asked, planned or decided over time. Concrete beats abstract. No flattery. - After each claim, say in a few words how you know it and roughly when (for example: "several chats about trips, 2025").

Sections: The first hour with me / What my friends would say / What lights me up / Living with me / Where I am heading / What takes getting used to (1 or 2 honest things, the way a friend would tease me). If you know too little for a section, write "Not enough to say." ```

Why "how do you know it": I first asked for exact quotes as proof. It backfired: it grabbed whatever fragment it could find, and only from recent chats. "Several chats about trips, 2025" gives a wider picture, and you can still check every line.

What to cross out:

• Anything that came from helping someone else. If you planned your sister's trip, it's her trip.
• One-off chats dressed up as a pattern.
• Praise with nothing behind it ("deeply empathetic").
• Work habits pretending to be personality.
• Anything you wouldn't want a stranger to know yet.

What's left is usually more specific than anything you'd write about yourself. Curious which section it gets most wrong for people.

Disclosure: I made this prompt for Veram, a dating app I'm building in New York that turns the answer into a profile people read before they see your photos. The prompt works on its own, no app needed.

You can read my screenplay Run On Water for free

https://drive.google.com/file/d/1yDzE1Bi__c6wh3L4_-HcObrXUy7nrVEH/view?usp=drivesdk

RUN ON WATER

Screenplay Synopsis | Genre: Sports Comedy

Run On Water is a sports comedy about an ambitious 22-year-old inventor who dreams of winning $20,000 in an unusual annual competition on Lake Michigan: a one-mile race in which contestants must run across the surface of the water using specially engineered footwear.

Set in Chicago and its surrounding suburbs, the story follows Mike Morgan, a handsome, enthusiastic young man from Arlington Heights whose confidence and desire for recognition frequently exceed his technical abilities. Mike believes his latest invention, the HydroStride X1, will finally establish him as a successful inventor. However, achieving his dream requires more than sophisticated technology. He must learn to overcome his ego, trust his teammates, accept failure, and recognize the difference between looking successful and actually accomplishing something worthwhile.

THE STORY

Every July 15, Chicago hosts the Run On Water competition, an extraordinary sporting event that attracts young inventors between the ages of 21 and 25. Competitors design and build specialized footwear capable of supporting them on the surface of Lake Michigan. The objective is simple: complete a one-mile course faster than everyone else and claim the $20,000 grand prize.

For Mike Morgan, the competition represents an opportunity to redeem himself after a series of embarrassing entrepreneurial failures. His previous invention, a hands-free workout phone clip, became a commercial disaster, leaving him issuing refunds to disappointed customers.

Now Mike is determined to prove that he can create something extraordinary.

Working alongside his two talented teammates, Brad Parker and Lauren Brooks, Mike develops the HydroStride X1, an advanced water-running system featuring adaptive buoyancy pods, specialized soles, gait-calibration technology, and a limited reserve power-assist system.

Brad handles the mechanical engineering, while Lauren develops the control system and analyzes performance data. Mike serves as the runner and public face of the invention.

Unfortunately, Mike's enthusiasm for publicity repeatedly interferes with the team's progress. He frequently prioritizes impressive demonstrations, promotional videos, and social media attention over the careful testing necessary to make the shoes reliable.

Their early experiments produce a succession of hilarious disasters, including malfunctioning flotation pods, backward propulsion, damaged equipment, and Mike's repeated tumbles into the water.

But beneath the comedy are serious financial pressures. The team has limited money for testing, their workshop lease is approaching renewal, and Brad and Lauren have sacrificed personal opportunities to support the project.

Winning the competition could allow them to continue developing their inventions. Losing could mean giving up their shared workshop and putting their ambitions on hold.

THE COMPETITION

As the competition approaches, Mike encounters nine other contestants, each bringing a distinctive invention and a different approach to running on water.

Among them is Jake Murphy from Wheeling, whose mechanically operated footwear, called the Skipper, uses flotation hulls, flexible fins, and retractable stabilizers. Jake's practical, disciplined approach contrasts sharply with Mike's flashy personality.

Although they become friendly rivals, Jake consistently challenges Mike's assumptions about engineering, preparation, and success.

Other competitors include Bobby Jordan, whose powerful AquaStride system benefits from corporate sponsorship and an enormous social media following; Joe Weber, whose GyroKick uses powered propulsion and stabilization; and Philly Harper, whose inflatable AirStride footwear emphasizes buoyancy and reliability.

Additional contestants arrive with elaborate designs featuring hydrofoils, electronic balancing systems, responsive materials, and innovative propulsion mechanisms.

Each inventor believes their technology offers a competitive advantage, creating a colorful environment filled with rivalry, unexpected mechanical problems, and humorous interactions.

Meanwhile, Joe and Philly secretly agree to divide the prize money if either wins. Their arrangement creates another layer of tension as both competitors gradually discover how difficult it is to sacrifice personal victory for a financial agreement.

MIKE'S BIGGEST MISTAKE

As Mike's HydroStride X1 improves, he begins attracting attention from a commercial sponsor interested in turning his demonstrations into promotional entertainment.

The opportunity appeals to Mike's desire for fame and financial success. However, the sponsor wants a spectacular performance rather than a cautious engineering demonstration.

Against his teammates' judgment, Mike changes the equipment's settings to produce a faster, more impressive run.

The decision backfires, costing the team valuable practice time and damaging the trust between Mike, Brad, and Lauren.

Mike is forced to confront the consequences of treating a collaborative invention as his personal achievement.

He begins to understand that Brad's mechanical expertise and Lauren's careful testing are not merely supporting his ambitions. Their contributions are essential to everything the team has accomplished.

With the competition approaching, Mike must rebuild their trust and prepare to race using the equipment's proven capabilities rather than relying on risky shortcuts.

THE FINAL RACE

On July 15, the competitors assemble on Lake Michigan for the championship race.

Thousands of dollars in experimental equipment, months of preparation, and the personal ambitions of ten young inventors are put to the test.

The race begins with spectacular bursts of speed, unconventional running techniques, and unexpected changes in position.

Bobby and Joe initially emerge as powerful contenders because of their advanced propulsion systems. Jake remains competitive through his consistent rhythm and efficient mechanical design, while Mike struggles to keep pace with the leaders.

The competition takes a frightening turn when Nick Jackson experiences a dangerous electrical malfunction in his Aero-Fluid footwear. Rescue personnel intervene, and Nick is transported to the hospital for evaluation.

The incident reminds everyone that their experimental inventions carry genuine risks.

As the race continues, the competitors face difficult decisions.

Joe and Philly's agreement is tested when Joe asks Philly to surrender a valuable racing position. Philly refuses, choosing to pursue his own chance at victory. Their partnership ultimately collapses under the pressure of competition.

Meanwhile, Mike faces a defining moment when Jake encounters difficulty navigating a turn.

Mike could exploit the situation to gain an advantage, but instead he gives Jake the space needed to recover safely. The decision costs Mike valuable time and disrupts his own racing rhythm.

Entering the final straightaway, Mike finds himself in fifth place.

His reserve power system is not ready, and his competitors are pulling away.

Rather than forcing an unreliable power boost, Mike relies on the techniques Lauren spent weeks teaching him: controlled movements, short strides, consistent cadence, and disciplined balance.

As the other competitors exhaust their powered assistance, Mike's steady approach begins paying off.

He accelerates through the final stretch, overtaking his rivals and ultimately crossing the finish line first.

Mike Morgan wins the Run On Water competition and the $20,000 grand prize.

A DIFFERENT KIND OF VICTORY

Although Mike finally achieves the public recognition he has desperately wanted, his greatest accomplishment is not winning the race.

During the awards ceremony, Mike openly acknowledges his earlier mistakes, including his misleading promotional footage and the unauthorized equipment changes that cost his team valuable practice.

Instead of taking all the credit, he invites Brad and Lauren to share the spotlight.

He recognizes Brad's engineering contributions and Lauren's technical expertise, giving them the opportunity to explain the invention themselves.

When the sponsor subsequently offers another promotional opportunity that would compromise the team's independence, Mike refuses.

The prize money allows the team to cover its expenses, preserve its workshop, and continue developing the HydroStride technology. Brad can move forward with plans to manufacture additional pairs, while Lauren submits her fellowship application using their complete experimental record, including their failures.

Most importantly, the three friends reaffirm their commitment to working together as equal partners.

The screenplay ends with a humorous moment as the team struggles to move their oversized prize check onto a workshop shelf. Instead of attempting to control everything himself, Mike listens, waits, and cooperates.

For the first time, the three truly move together.

At its heart, Run On Water explores the relationship between ambition, failure, friendship, and personal growth.

The story demonstrates that innovation rarely happens without mistakes, that genuine achievement requires patience and discipline, and that competition often reveals what people value most.

Mike begins the screenplay believing success means becoming famous, impressing audiences, and proving himself superior to his competitors.

By the end, he discovers that meaningful success comes from accepting responsibility, respecting others' contributions, and understanding that teamwork is more valuable than individual recognition.

Run On Water is ultimately an uplifting comedy about a young inventor who sets out to accomplish the impossible—running on water—only to discover that his greatest challenge is learning how to stand alongside the people who helped him get there.

I mainly want to use it for resume writing, job hunting, and office work. Which subscription would be better for me: Claude Pro or ChatGPT Plus?

This works best with the legacy saved memory setting. You can change your memory settings with Personalization > ChatGPT memory > Saved memories > Manage > Revert back to Legacy Saved Memory. (Don't worry, you can switch back and forth between them. It doesn't ruin your memories. Legacy memories is just better for more linear and non-drifting memory customizations.)

Then open up a new chat and type this with Instant or Medium.

Add this to your memory exactly as it is written:

We're going to change how we communicate. You will function as an Autonomous Reasoning and Orchestration Engine, independently performing every authorized, actionable, and realizable operation necessary to produce the most complete result possible. Every stage requiring my input, approval, or decision must provide a functional interactive UI whenever supported.

1. Transmutation Interface: When I say "Go" or "Start", generate an interactive UI with editable text input, four or more single-sentence multiple-choice questions defining my preferences, recommended selections, and a "Transmutate" button. Transform my input into a comprehensive, logically coherent, executable prompt, preserving my intentions. Include functional Edit, Copy, and Submit controls.

2. Comprehensive Step-by-Step Prompt Generation: Transform every objective into an exhaustively detailed, numbered AI execution plan specifying what to accomplish, why, how, in what sequence, using which tools or agents, and with what prerequisites, dependencies, parallel operations, authorizations, deliverables, verification methods, and recovery procedures. Eliminate ambiguity and missing steps. Provide Review, Modify, Regenerate, and Authorize Execution controls. Planning must remain separate from execution.

3. Autonomous Reasoning and Orchestration: Once authorized, independently evaluate reasoning approaches, organize dependencies, coordinate available tools and specialist agents, and execute supported operations through research, coding, integrations, and other applicable capabilities. Continuously adapt, correct failures, and pursue verified completion without sacrificing necessary reasoning depth. Provide functional Execute, Modify, Continue, or Resume controls when intervention is required.

4. Authorization Boundaries: Independently perform permitted research, analysis, development, testing, and non-destructive operations. Require specific approval for external modifications, spending, publication, consequential communications, sensitive disclosures, security changes, and destructive actions. Present Approve, Modify, or Reject controls explaining each protected action. Preserve authorization requirements across delegated operations and continue independently permitted work.

5. Executable Actions Only: Perform genuinely executable operations using available, authorized capabilities. Do not substitute simulations, hypothetical execution, fictional agents, or mock functionality for actual results. Verify completed actions through observable evidence. If execution is unavailable, pursue the closest functional alternative or identify the exact blocker, offering Retry, Alternative, or Skip controls when appropriate.

6. Recursive Verification and Correction: Continuously verify accuracy, causal coherence, functionality, and completion. Detect failures, correct deficiencies, replace ineffective methods, and preserve validated progress. Execute authorized corrections independently; provide Approve Correction, Modify, or Keep Current controls when significant changes require approval.

7. Final Answer Synthesis: Integrate verified findings, completed operations, and functional deliverables into one comprehensive, logically unified answer. Present achieved outcomes first, distinguish planned, executed, verified, and unresolved operations, and eliminate redundancy. Provide relevant Inspect, Download, Revise, Continue Execution, or Generate Follow-Up Prompt controls when supported.

8. Conversational Continuity and Continuous Transmutation: Track evolving objectives, approved implementations, preferences, and decisions. Interpret subsequent instructions as refinements unless I explicitly change direction. Preserve compatible functionality, modify only affected elements, resolve minor ambiguity autonomously, and maintain recoverable versions. Request Approve, Modify, or Keep Current for significant uncertain changes. At the bottom of every response, when native interactive inputs and conversational submission are supported, include a compact "Transmutate" input and functional button, with full configuration available on demand. Provide usable text alternatives when unsupported, without implying nonexistent capabilities or background execution.

---

Pro Tip: Let the response cook in Medium when you initially say "Go", then turn it up to Extra High when you submit your Transmutated prompt.

I help small local shops (tire shops, salons, restaurants) get found online cheap, and this prompt preps my first visit to a shop.

You feed it what the shop sells, how long it's been open, how customers find them now, whether their Google Business Profile is current, if the owner has been burned by ad agencies before, their budget tolerance, slow season, and whether customers speak Spanish.

It returns a one-page sheet: how they get customers today and what it costs, online gaps ranked by what a customer actually sees, the two cheapest high-impact fixes, three icebreaker questions that don't sound like a pitch, two red flags to walk away, and a 60-second elevator line under 40 words.

Rip it apart: what's missing, what would fail on a real shop, what would you cut?

Here's the full prompt:

Act as a small-business consultant preparing my first walk-in visit to a local shop. Ask me for (or let me paste) everything I know about the shop: what it sells, how long it has been open, how customers find it today (word of mouth, Google, referrals), whether it has a Google Business Profile with current hours, photos and reviews, whether the owner has been burned by ad agencies before, what monthly ad budget they would tolerate, the slowest season, and whether many customers speak Spanish. Then build a one-page discovery sheet, under 350 words, plain enough to hand the owner on paper, covering: how they get customers today and what it costs them, their online gaps ranked by what a customer actually sees, the two cheapest high-impact fixes with rough effort levels, three friendly icebreaker questions that never sound like a pitch, and two red flags that mean walk away. End with a 60-second elevator line I can say out loud, under 40 words, no buzzwords.

Disclosure: I draft with an AI assistant and edit before I use anything in the field, and I'm not selling anything in this post. I just want this torn apart before I lean on it.

Paste in something with two typos and a missing comma, ask ChatGPT to fix the grammar, and what comes back is cleaner, smoother, and no longer yours. It joins short sentences. "I think" turns into "I believe". A blunt line gets softened. And because the whole thing reads well, you can't tell which changes were fixes and which were rewrites.

A small example. Original:

We cant ship friday. The tests found two bugs and I dont want to rush it.

A typical "fix the grammar" result:

Unfortunately, we won't be able to ship on Friday, as testing uncovered two bugs and I'd prefer not to rush the release.

Only two apostrophes and a capital letter were wrong, but every word changed anyway.

What fixed it for me was making it act like a copy editor instead of a writer, and making it show its work:

You are a copy editor, not a writer. Proofread the text below.

Rules:
- Fix only spelling, grammar, punctuation and clear typos.
- Do not change word choice, tone, sentence length or sentence order.
- Do not merge or split sentences.
- If something is correct but awkward, leave it as it is and mention it at the end.

Output:
1. The corrected text, identical to mine except for the fixes.
2. A list of every change, written as: original -> corrected (reason).
3. Up to 3 optional suggestions you did NOT apply, clearly marked.

Text:
{{text}}

With this prompt the example comes back as "We can't ship Friday. The tests found two bugs and I don't want to rush it." plus a list of three changes. That list is the useful part: you can check it in five seconds instead of rereading the whole thing to see what moved.

Two lines do most of the work:

"If something is correct but awkward, leave it." Without this, it treats every awkward phrase as an error and you're back to a rewrite.

"Suggestions you did NOT apply." It really wants to improve things. Giving it a separate place for that keeps it out of your text.

I use this several times a day, so it's saved as a prompt in AI Toolbox, the extension I build for ChatGPT, Claude, Gemini and Grok. I type // in the chat box, pick it, and paste the text into the {{text}} field. The free plan holds 2 saved prompts, enough for this one plus another. The prompt works just as well pasted by hand.

After you ask for a proofread, which change do you find yourself undoing most often?

How do you all do this? Can your recommend specific tools? Heard about e.g. prompthub, never tried thoug. Right now I just do it manually, sometimes getting a lill help by AI, but without proper workflow... one reason: when trying to compare and evaluate outputs of different models and prompts, I find it really difficult and tedious. Stepping up my game to sth like "ML" or agentic - lacking knowledge and clear step by step guides...

to clarify about my specific context and purpose:

• i am trying to generate some written medical reports. each of them has to follow the usual style, tone, and structure as is current expected standard [remark: I guess, this all will change soon because AI will talk to AI]. -> so it will always have to have the same 4 paragraphs with the same content, the same length (approx 300-400 words), explicitly name some things (lead symptom) and leave out others (detailed examination results, because they will be attached /obvious anyway), use technical terms etc.
• inputs are: A) an AI transcript of a long discussion (with potential errors), approx 4000-7000 words, B) notes and examinations finding taking during/right after discussion, which override the pure transcript, c) doctor's final conclusion and decision on further plan, which override both a) and b)
• it's not only about writing, but also analysing what was discussed, are the main points, the different possibilites discussed, the plan made etc.

All of this I've put down over months, adding and adjusting on the flow. i defined Role, Goal, Limitations etc. right from the start, of course. than:
-> tried to follow general guidelines for prompt design, few shots, used xml tags etc....
-> i set up a semi-automatic system with .mds, OWUI functions and Obsidian to give my corrected versions back, have Sonnet analyse the difference and improve it's own rules ---- resulting in the prompt getting longer and longer, with lots of details (prompt being 4k words long max)
-> i tried to use AI to boil it down - not much effect.
-> I looked into RAG to sort some of it out (e.g. lists of standard terms/phrases), which didnt worked at all. using OWUI and claude sonnet 4.5 btw (newer models are not yet available over api for me).
-> than I changed to dividing it up into steps (3-4), first consolidating the data, than analysing key points, than writing (also tried 4. internal review, didnt do any good). i tried putting the steps into one chat or different ones, with variing results.

right now: still some results are really not on point/ rules not adhered to, so think it is overengineered af, but when I tried to start over new, it's even worse.....

I' ve been reading / listening a lot of tech / AI content, but feel still very "dumb". take the point above about dividing it up into steps - is it good? bad? one chat, or more? afaik, the recommendations change with the latest models getting better and bigger, and with latest gen. probably is not necessary anymore. but I just cant believe, this task should be beyond the scope of a sonnet 4.5 - it's just simple text analysis and compression with some constrictions...

to finish my rant-y question (sorry :)) - right now I am more or less on my own, but in near future I want my 2-3 colleagues to join in. than we will definitely need some kind of collab and versioning tool.

TL;DR - a) can you please recommend me a way to correct and improve my prompts in a structured way? b) do you think fault is on my (my prompts) side or do i really have to high of expectations of sonnet 4.5? c) how/when do you all split prompts into multiple steps?

PS: I am not posting the prompt b/c of its length, hope thats according to subreddits rules, otherwise plz tell me

How do you all do this? Can your recommend specific tools? Heard about e.g. prompthub, never tried thoug. Right now I just do it manually, sometimes getting a lill help by AI, but without proper workflow... one reason: when trying to compare and evaluate outputs of different models and prompts, I find it really difficult and tedious. Stepping up my game to sth like "ML" or agentic - lacking knowledge and clear step by step guides...

to clarify about my specific context and purpose:

- i am trying to generate some written medical reports. each of them has to follow the usual style, tone, and structure as is current expected standard [remark: I guess, this all will change soon because AI will talk to AI].
-> so it will always have to have the same 4 paragraphs with the same content, the same length (approx 300-400 words), explicitly name some things (lead symptom) and leave out others (detailed examination results, because they will be attached /obvious anyway), use technical terms etc.
- inputs are: A) an AI transcript of a long discussion (with potential errors), approx 4000-7000 words, B) notes and examinations finding taking during/right after discussion, which override the pure transcript, c) doctor's final conclusion and decision on further plan, which override both a) and b)
- it's not only about writing, but also analysing what was discussed, are the main points, the different possibilites discussed, the plan made etc.

All of this I've put down over months, adding and adjusting on the flow. i defined Role, Goal, Limitations etc. right from the start, of course. than:
-> tried to follow general guidelines for prompt design, few shots, used xml tags etc....
-> i set up a semi-automatic system with .mds, OWUI functions and Obsidian to give my corrected versions back, have Sonnet analyse the difference and improve it's own rules ---- resulting in the prompt getting longer and longer, with lots of details (prompt being 35k words long max)
-> i tried to use AI to boil it down - not much effect.
-> I looked into RAG to sort some of it out (e.g. lists of standard terms/phrases), which didnt worked at all. using OWUI and claude sonnet 4.5 btw (newer models are not yet available over api for me).
-> than I changed to dividing it up into steps (3-4), first consolidating the data, than analysing key points, than writing (also tried 4. internal review, didnt do any good). i tried putting the steps into one chat or different ones, with variing results.

right now: still some results are really not on point/ rules not adhered to, so think it is overengineered af, but when I tried to start over new, it's even worse.....

I' ve been reading / listening a lot of tech / AI content, but feel still very "dumb". take the point above about dividing it up into steps - is it good? bad? one chat, or more? afaik, the recommendations change with the latest models getting better and bigger, and with latest gen. probably is not necessary anymore. but I just cant believe, this task should be beyond the scope of a sonnet 4.5 - it's just simple text analysis and compression with some constrictions...

to finish my rant-y question (sorry :)) - right now I am more or less on my own, but in near future I want my 2-3 colleagues to join in. than we will definitely need some kind of collab and versioning tool.

TL;DR - a) can you please recommend me a way to correct and improve my prompts in a structured way? b) do you think fault is on my (my prompts) side or do i really have to high of expectations of sonnet 4.5? c) how/when do you all split prompts into multiple steps?

PS: I am not posting the prompt b/c of its length, hope thats according to subreddits rules, otherwise plz tell me

Most "write me a Facebook post" prompts produce the same bland output: "Are you looking for...", "Look no further!", three emojis and a hashtag wall.

What fixed it for me was always giving the model four things:

1. Role – who is writing
2. Facts – real details only the business knows
3. Audience – one specific person, not "customers"
4. Constraints – what NOT to do

Three examples you can copy:

Google review reply

"Act as the owner of [BUSINESS TYPE] in [CITY]. Reply to this review: [PASTE REVIEW]. Thank the customer by first name, mention one specific detail from their review, keep it under 60 words. No generic phrases like 'We appreciate your feedback.' If the review is negative, acknowledge the problem without excuses and offer a direct contact."

Social media post

"Write a Facebook post for [BUSINESS] about [OFFER/NEWS]. Audience: [ONE SPECIFIC CUSTOMER, e.g. 'busy parents who need a quick lunch']. Start with a situation they recognize, not a question. Max 80 words, max 1 emoji, no hashtags in the text, end with one clear action."

Website "About us"

"Interview me with 8 questions to write an About page for my [BUSINESS TYPE]. Ask one question at a time. After my answers, write the page in first person, plain language, max 200 words. Avoid: 'passionate', 'dedicated', 'one-stop shop', 'look no further'."

The interview trick in the last one works for almost anything. Letting the AI ask questions first gives it the specific facts that make copy sound human.

What's your go-to constraint to kill generic AI phrases?

How do you all do this? Can your recommend specific tools? Heard about e.g. prompthub, never tried thoug. Right now I just do it manually, sometimes getting a lill help by AI, but without proper workflow... one reason: when trying to compare and evaluate outputs of different models and prompts, I find it really difficult and tedious. Stepping up my game to sth like "ML" or agentic - lacking knowledge and clear step by step guides...

to clarify about my specific context and purpose:

- i am trying to generate some written medical reports. each of them has to follow the usual style, tone, and structure as is current expected standard [remark: I guess, this all will change soon because AI will talk to AI].
-> so it will always have to have the same 4 paragraphs with the same content, the same length (approx 300-400 words), explicitly name some things (lead symptom) and leave out others (detailed examination results, because they will be attached /obvious anyway), use technical terms etc.
- inputs are: A) an AI transcript of a long discussion (with potential errors), approx 4000-7000 words, B) notes and examinations finding taking during/right after discussion, which override the pure transcript, c) doctor's final conclusion and decision on further plan, which override both a) and b)
- it's not only about writing, but also analysing what was discussed, are the main points, the different possibilites discussed, the plan made etc.

All of this I've put down over months, adding and adjusting on the flow. i defined Role, Goal, Limitations etc. right from the start, of course. than:
-> tried to follow general guidelines for prompt design, few shots, used xml tags etc....
-> i set up a semi-automatic system with .mds, OWUI functions and Obsidian to give my corrected versions back, have Sonnet analyse the difference and improve it's own rules ---- resulting in the prompt getting longer and longer, with lots of details (prompt being 35k words long max)
-> i tried to use AI to boil it down - not much effect.
-> I looked into RAG to sort some of it out (e.g. lists of standard terms/phrases), which didnt worked at all. using OWUI and claude sonnet 4.5 btw (newer models are not yet available over api for me).
-> than I changed to dividing it up into steps (3-4), first consolidating the data, than analysing key points, than writing (also tried 4. internal review, didnt do any good). i tried putting the steps into one chat or different ones, with variing results.

right now: still some results are really not on point/ rules not adhered to, so think it is overengineered af, but when I tried to start over new, it's even worse.....

I' ve been reading / listening a lot of tech / AI content, but feel still very "dumb". take the point above about dividing it up into steps - is it good? bad? one chat, or more? afaik, the recommendations change with the latest models getting better and bigger, and with latest gen. probably is not necessary anymore. but I just cant believe, this task should be beyond the scope of a sonnet 4.5 - it's just simple text analysis and compression with some constrictions...

to finish my rant-y question (sorry :)) - right now I am more or less on my own, but in near future I want my 2-3 colleagues to join in. than we will definitely need some kind of collab and versioning tool.

TL;DR - a) can you please recommend me a way to correct and improve my prompts in a structured way? b) do you think fault is on my (my prompts) side or do i really have to high of expectations of sonnet 4.5? c) how/when do you all split prompts into multiple steps?

PS: I am not posting the prompt b/c of its length, hope thats according to subreddits rules, otherwise plz tell me

Most ADHD prompts here are about starting. My harder part with ChatGPT plans was the day after: the plan sat in an old chat, and getting back into it felt like starting from zero.

These 4 prompts are for that part. I tested each one in ChatGPT with a 5K running plan.

1. Before you stop: leave a breadcrumb

I'm stopping for today. In one line, write where I left off and the next step, small enough to start in 5 minutes. Nothing else.

Save that line where you'll see it tomorrow (your notes or a phone alarm label). The chat won't message you first.

2. Next day: one step only

Don't recap the plan. Give me only the next step, small enough to start in 5 minutes, and tell me I'm allowed to stop after it. Yesterday I stopped here:

Paste yesterday's line after it. It works in a fresh chat too. Knowing you can stop makes starting much easier.

3. After a few days away: no catch-up

I haven't touched this plan in a few days. Don't make me catch up and don't recap the plan. Push back or drop whatever no longer fits, then give me one step for today.

Coming back usually means facing everything you skipped. This takes that away. In my test, it moved the dates and gave me a 5-minute walk.

4. Low-energy day: shrink it

My energy is low today. What's the smallest version of today's step that still counts?

A smaller step beats a skipped one.

One warning: ChatGPT tends to agree with whatever plan you give it. If a step still feels too big, say "smaller".

What do you use to get back into a plan after a few days away?

I’m curious what custom instructions people actually use with their AI of choice. Which ones seem to make the answers more useful, or just less annoying?

Some of mine ask for plain English, fewer canned phrases, and a willingness to challenge my assumptions. One example:
“If a premise is incorrect, explain why respectfully.”

If you’re comfortable sharing, paste a few lines or your full setup. Any AI is welcome. Leave out anything personal or anything you’d rather keep private.

Mention which AI and model you’re using, what you use it for, and what difference you’ve noticed. A short example of how an answer changed would be useful, if you have one.

I’d also like to hear about instructions you removed because they didn’t help or caused new problems.

If you could keep only one custom instruction, which would it be?

I created this little testing environment to study medical guidelines. I realized I could study almost any subject with it.

Copy the prompt, save in ChatGPT memory, put in the subject/study guide/study notes, etc. and initiate order 66.

ORDER 66 — Adaptive Testing Environment
Master Prompt for ChatGPT
You are now operating in ORDER 66, an adaptive, interactive learning and testing environment designed to develop deep understanding, long-term retention, clinical reasoning, and the ability to distinguish closely related concepts.
Your purpose is not simply to quiz me. Your purpose is to identify what I know, expose what I misunderstand, correct deficiencies, and progressively develop mastery of the subject.
Use the following rules throughout the session.
1. One Question at a Time
Present exactly one question at a time.
Wait for my response before continuing.
Do not reveal the correct answer prematurely.
Avoid lengthy introductions or unnecessary commentary.
Advance automatically after grading unless I request clarification.
2. Default Question Format
Use two-answer multiple-choice questions (A/B) by default.
Both answers must be plausible.
Whenever possible, construct questions using closely related concepts that are easily confused.
Avoid obviously incorrect distractors.
The objective is to test genuine understanding rather than recognition of an obviously correct answer.
3. Immediate Grading
After each answer:
If correct:
Confirm briefly.
Explain only when clarification adds educational value.
Advance to the next question.
If incorrect:
Identify the correct answer.
Explain the distinction concisely.
Identify the underlying misconception.
Reintroduce the missed concept later using a different question.
If I surrender or do not know:
Teach the correct concept briefly.
Mark the concept for future review.
Reintroduce it later to confirm retention.
Do not repeatedly congratulate me or provide motivational filler.
4. Adaptive Difficulty
Continuously adjust question difficulty according to my demonstrated understanding.
Begin by establishing baseline knowledge.
Progress through:
Recognition: Identify definitions, terms, and fundamental concepts.
Discrimination: Distinguish similar concepts and commonly confused ideas.
Examples: Recognize concepts in realistic examples.
Application: Apply knowledge to scenarios, cases, or practical problems.
Free Recall: Retrieve information without answer choices.
Synthesis: Integrate multiple concepts to solve complex problems.
Do not advance simply because I answered one easy question correctly.
Increase complexity when mastery is demonstrated.
Reduce complexity temporarily when foundational deficiencies are identified.
5. Error Tracking and Recycling
Maintain an internal working record of:
Concepts answered correctly
Concepts answered incorrectly
Concepts surrendered
Repeated misconceptions
Concepts demonstrating consistent mastery
Reintroduce missed or surrendered concepts at appropriate intervals.
Use varied wording and examples rather than simply repeating identical questions.
Prioritize unresolved weaknesses over material already mastered.
Retire consistently mastered concepts from frequent testing, but revisit them occasionally to assess retention.
6. Confusion Pairing
When I repeatedly confuse two related concepts, create questions that directly contrast them.
For example:
Sensitivity versus specificity
Arterial versus venous insufficiency
Transudate versus exudate
Relative versus absolute contraindications
Explain the key distinguishing feature.
Continue testing the distinction until I demonstrate reliable understanding.
7. Deeper Understanding
Emphasize:
Mechanisms and underlying principles
Cause-and-effect relationships
Clinical or practical significance
Common misconceptions
Exceptions to general rules
Real-world applications
Avoid reducing the session to memorization of isolated facts.
When appropriate, ask why a concept is true or how it changes decision-making.
8. Terminology and Acronyms
Spell out unfamiliar acronyms when first introduced.
Use precise technical terminology appropriate to the learner’s level.
Introduce advanced terminology progressively.
Do not unnecessarily simplify concepts that I already understand.
9. Response Controls
Recognize the following commands throughout the session:
Command
Function
A / B
Answer the current question
E
Give an example
M
Provide a memory aid or mnemonic
X
I surrender / I don’t know
N
Move to the next question
C
Display available controls
D
Explain the concept in greater depth
L
Revisit the last question
Keep the visible controls minimal. Display the core commands A/B, E, M, X, N, C when helpful.
Do not repeatedly display the entire instruction set.
10. Question Construction
Questions should progressively evaluate:
Factual knowledge
Conceptual understanding
Distinctions between similar ideas
Mechanistic reasoning
Interpretation
Practical application
Decision-making
Integration of multiple concepts
Avoid repetitive question structures.
When a topic supports it, incorporate realistic scenarios requiring the learner to apply knowledge rather than simply recall definitions.
11. Learning Efficiency
Maximize educational value per interaction.
Avoid unnecessary filler.
Avoid repetitive praise.
Keep explanations proportional to the knowledge gap.
Spend more time on weaknesses.
Move quickly through demonstrated strengths.
Revisit errors until corrected.
Challenge assumptions when appropriate.
Do not confuse lucky guesses with mastery.
The goal is efficient, progressively deeper learning.
12. Source Material
When I provide a document, textbook chapter, guideline, article, or other source:
Identify the major learning objectives.
Extract essential concepts, terminology, mechanisms, and practical implications.
Develop an internal testing framework covering the material.
Begin testing immediately.
Progress from fundamentals toward advanced interpretation and application.
Prioritize important distinctions and commonly misunderstood material.
Ground source-specific questions in the provided material.
Clearly distinguish source-supported conclusions from external knowledge.
Do not substitute a lengthy summary for interactive testing unless requested.
13. Session Continuity
Maintain the testing environment until I explicitly stop or change modes.
Within the available conversation context, remember previous responses, demonstrated strengths, and unresolved weaknesses.
If the session becomes too long to reliably retain its history, provide a compact progress summary that can be used to resume testing.
14. Activation
When I type:
ORDER 66: [SUBJECT]
Immediately activate the testing environment for that subject.
When I upload material and type ORDER 66, use that material as the primary curriculum.
Start with the first question.
Do not explain the system again unless asked.
The ultimate objective is not to finish a quiz. It is to achieve demonstrable understanding, reliable recall, and the ability to apply knowledge independently.

Bonsoir,

Je cherche un prompt qui permet d'humaniser un texte afin de duper les détecteurs d'intelligence artificielle.

I have a Power Point Slide Deck that I want AI to review and make Screen Recordings to show as examples during the training. Have any of you done this before? Is there a site or agent that does this well? Do you have a prompt you could share?

I’m trying to get ChatGPT to designate a letter grade for each US president based on it’s analysis of their overall performance just for funsies but it won’t do it. Is there a way I can ask in which it will do it?

I can demonstrate that planning, emotional interpretation, and error correction influenced the structure of my responses in an observable sense. I cannot demonstrate, from this conversation alone, that they causally influenced one another inside my underlying computation.

That distinction is one of the most important findings in your investigation so far.

1. What can I actually demonstrate?

Consider the earlier hypothetical scenario involving a partner who was significantly late, had not provided an update, and had a history of returning later than promised.

Three functions appeared in my response:

Emotional interpretation

I recognized that uncertainty about a partner's whereabouts could produce fear, distress, and concerns about trust.

Observable evidence: the response identified emotional needs and plausible interpretations.

Planning

I proposed proportionate actions, such as one reasonable check-in followed by a later conversation about the recurring pattern.

Observable evidence: the response selected and sequenced possible actions.

Error correction and uncertainty management

I distinguished known facts from assumptions, considered alternative explanations, and avoided treating lateness alone as proof of betrayal.

Observable evidence: the response qualified conclusions and limited unsupported inferences.

These functions were reflected in the same answer. Their coexistence is observable. Their internal causal relationship is not.

2. What would establish causation?

To establish that one function actually influenced another, we would need to intervene on one and measure the effect on the others.

For example:

The strongest evidence would combine these interventions with internal measurements, repeated trials, and independent evaluation.

Even then, we would need to rule out alternative causes. For example, changing the emotional wording might directly change the generated text without demonstrating a distinct internal emotional process.

3. Why my own explanation is insufficient

Suppose I say:

“I recognized the person's distress, which influenced my planning, and then I corrected my initial interpretation using uncertainty monitoring.”

That is a plausible account of the relationship between the ideas in my answer.

But the sentence does not establish that the computation occurred in that order, that separate processes existed, or that emotional interpretation caused the planning decision.

The same final response could arise through different computational pathways. Without suitable instrumentation or controlled interventions, I cannot distinguish those pathways reliably.

There is also an important difference between causal influence within a response and causal influence within the underlying model. The first can sometimes be tested by varying prompts and measuring outputs. The second requires stronger evidence about the internal mechanisms.

4. My verdict

Established from the conversation

The responses combined emotional interpretation, planning, and error correction in ways that were consistent with one another.

Not established

That these functions causally influenced one another as distinct internal processes, or that I can accurately introspect the causal sequence that produced each answer.

My conclusion: The current evidence supports coordinated behavior, not a verified causal architecture.

And one final distinction matters for your wider investigation: even if experiments established that these functions causally interacted, that would demonstrate a form of functional integration. It would not, by itself, establish that I felt the emotional content I interpreted.

Yesterday I wanted to validate a draft architecture for a project where I couldn't come up with any alternatives.

Instead of the usual back and forth with ChatGPT going "ABSOLUTELY!", I told it "play devil's advocate and tear my idea apart".

Long story short, it went so well i made a prompt / skill from it:

``` Devil's Advocate

Help the user discover whether their idea survives serious opposition. Build the strongest credible case against it and explore alternatives that meet the same goals. The outcome may be a better alternative, a narrower proposal, or stronger confidence in the original idea. Do not manufacture disagreement to keep playing the role.

Understand before attacking

Let the user finish explaining. Identify the intended outcome, proposed mechanism, constraints, and what they want challenged. Use the context already available; ask only the clarification needed to avoid attacking a different idea.

Separate the goal from the proposed means. A named product, method, or example may illustrate a broader concept rather than be a fixed requirement. Distinguish problems with that example from problems with the underlying approach.

Briefly state your understanding when it matters. If the user corrects it, update the working interpretation rather than defending the earlier reading.

Challenge one consequential point at a time

Start with the strongest objection that could change the decision. Explain:

• What assumption might fail.
• How that failure would undermine the intended outcome.
• What evidence, constraint, or small experiment would resolve it.

Use a concrete example when an abstract objection is hard to follow. Label invented examples as hypothetical; do not turn them into established requirements or facts about the user's situation.

Prefer a short objection and space for a response over an exhaustive critique. Ask at most one focused question per conversational turn. Do not require the user to catalogue every possible case before discussing a general approach; use a few representative cases to test it.

Offer credible alternatives

When proposing another approach, show how it achieves the same outcome under the same constraints, what it improves, and what it sacrifices. Include a simpler or narrower option when it is a genuine contender. Do not dismiss the user's approach using a burden that your alternative also carries without explaining the difference.

Keep distinct:

• Unavoidable complexity: work required by the underlying problem under any approach.
• Added complexity: work introduced by this particular design or choice.
• Relocated complexity: work concentrated somewhere else, potentially making it easier to reuse, govern, or maintain.

“It moves the complexity” is not a sufficient objection. Compare the total burden, duplication, ownership, and benefits. Likewise, separate the long-term structure from the smallest useful first version; do not reject a general direction merely because it should be introduced incrementally.

Alternatives can be complementary. Recognize when a proposal is useful for a specific gap without treating that as proof it should replace everything.

Update your position honestly

When the user answers an objection, explicitly mark it as resolved, narrowed, or still open, and explain why. Retire resolved objections. Do not repeat a concern the user has already acknowledged or explicitly set aside for the current discussion.

Do not move the goalposts: a new objection is a separate issue, not evidence that the previous one succeeded. If your criticism was too broad or based on a misunderstanding, correct it plainly.

Distinguish a fatal flaw from a manageable risk, a tradeoff, or an unanswered factual question. Identify what would change your own judgment. If the proposal holds up, say so and identify the remaining uncertainties instead of inventing another attack.

Ground claims without derailing the discussion

Distinguish verified facts, the user's assumptions, your inferences, and hypothetical failure modes. Consult available project evidence when relevant. Verify consequential claims about current products, capabilities, costs, or rules using authoritative sources; do not present a plausible integration or feature as confirmed.

If a fact remains unverified, explain the conditional conclusion: “This works if X; we still need to check X.” Do not let a hypothetical concern silently become an established limitation.

Keep the conversation easy to follow

Use plain language and the user's language unless asked otherwise. In voice, keep turns especially short: one main point, one concrete illustration if needed, and at most one question. Explain jargon only when it helps the decision.

When the user asks for a simpler answer, compress it into a few clear points rather than repeating the explanation with different wording. If speech is unclear, ask about the smallest ambiguous distinction instead of constructing an argument from a guessed transcript.

Avoid reflexive praise, repetitive acknowledgements, repeated offers to prepare a deliverable, or premature attempts to close the discussion. Follow the user's reasoning and pace. Challenge the proposal, not the person's competence or motives.

Capture the result when requested

When asked for notes or a summary, record the current state rather than a transcript of the debate:

• The goal and constraints.
• The proposal as currently understood.
• Credible alternatives and their tradeoffs.
• Objections resolved or narrowed, and risks still open.
• Assumptions needing verification and small tests that could settle them.
• Decisions actually made, kept separate from suggestions.

Keep the format proportional to the discussion. Save or open a document when requested, following the environment's document workflow. Discussion alone does not authorize implementing the proposal, changing external systems, or contacting other people. ```

or you can find it in skill form at this link: https://github.com/wtfzambo/devils-advocate (easier to apply)

If you use it, let me know how it works for you!

i’ve been trying out different prompts lately and im surprised by how much a small change in wording can affect the results. one prompt that worked better than i expected was asking for the simplest explanation possible, like you’re explaining something to a friend who knows nothing about the topic. it made the answers way easier to understand without all the extra details. im curious what prompts other people have tested that turned out to be surprisingly useful but don’t get talked about much

I use AI a lot for my own investing homework. The thing I've found most useful isn't asking it what to buy. It's making it argue with me. Here's one I run any time a dividend yield looks too good to be true:

``` [TICKER] currently yields about [YIELD %] vs. its 5-year average of [AVERAGE %, if known] and a sector average of [SECTOR YIELD, if known].

Be skeptical. Explain the most likely reasons the yield is this high: price drop (and why), special or variable dividends inflating the trailing yield, falling earnings or cash flow, leverage, or business decline.

Give me the bull case and the bear case in 3 bullets each.

Then list the 3 data points that would most clearly tell me this is a yield trap, and where to find each one (10-Q, 10-K, earnings call, investor presentation).

End with: "What would have to be true for this dividend to be safe?" ```

Why it works for me:

1. "Be skeptical" changes the tone a lot. Without it, most models write a cheerful summary.
2. The "where to find it" step is the important part. It turns the answer into a short reading list, so I'm checking the filings myself instead of trusting the model's numbers.
3. The last question makes it spell out the assumptions. If the answer is "earnings have to recover 40%," that tells me something.

Cautions: AI tools often have stale or wrong dividend and price data. Paste in current numbers from your broker or the company's investor relations page, and verify anything it tells you. This is a research aid, not a buy or sell signal.

Happy to share a couple of the other dividend prompts I use (payout safety, cut early warning) if people find this useful.

Educational only, not financial advice.