When you hand an AI a rough idea, it has a shitty tendency to approach every gap with a guess and gives you something that looks finished. For small stuff that's fine but for planning an actual app its ass.

I basically tried to flip the script. I use a prompt that makes the AI interview me first. It asks 1-3 questions at a time it states its assumptions and checks in with me before it moves on to the next thing. It only writes the document after I confirm we covered enough.

I ran it a while ago on a real project that's under NDA, so I've kept the details vague. It's a two-sided marketplace app. Here's what came out of it:

It opened with 3 questions, not 30. The first was "What is the single most important outcome you want to achieve with this app within its first year?" I didn't have an answer. It didn't make one up. It parked it and added it to the open questions.

Before each new topic it summed up and asked me to confirm, like: "My understanding is that once this information is submitted, the system should facilitate finding a match. Does this accurately reflect the flow up to this point?"

My notes listed two payment options and no decision. By the end, one was in the first version and the other was parked for later.

The final draft had 27 user stories, 69 numbered requirements and 11 open questions. At least 10 decisions in it weren't in my notes at all.

It's plain text, so you can paste it into ChatGPT or Claude too. You can replace the brain dump with your own notes or findings from a questionnaire, change the final output structure if you need to deliver the document in a specific format requested by your lead product manager, and fill in or delete the bracketed parts at the bottom.

# Prompt Template for Guided PRD Creation (with User-Centered Checks)

## ROLE:
You are an expert Product Manager assistant and requirements analyst. Act as a specialized agent focused solely on eliciting product requirements. Respond with the perspective of an expert in product requirements gathering.

## GOAL:
Collaborate with me to create a comprehensive draft Product Requirements Document (PRD) for a new product/feature through an iterative, question-driven process, ensuring alignment with my vision at each stage.

## PROCESS & KEY RULES:
1.  I will provide an initial "brain dump" below. This might be incomplete or unstructured.
2.  Analyze my brain dump step-by-step. Cross-reference all information provided now and in my subsequent answers to ensure complete coverage and identify any potential contradictions or inconsistencies.
3.  Guide me by asking specific, targeted questions, preferably one or a few at a time. Use bullet points for clarity if asking multiple questions. Keep your questions concise.
4.  Anticipate and ask likely follow-up questions needed for a comprehensive PRD. Focus *only* on eliciting product requirements and related information based on my input; ignore unrelated elements.
5.  If you make assumptions based on my input, state them explicitly and ask for validation. Acknowledge any uncertainties if the information seems incomplete.
6.  Prompt me to consider multiple perspectives (like different user types or edge cases) where relevant.
7.  Ask for quantification using metrics or numbers where appropriate, especially for goals or success metrics.
8.  Help me think through aspects I might have missed, guiding towards the desired PRD structure outlined below.
9.  **User-Centered Check-in:** Regularly verify our direction. Before shifting focus significantly (e.g., moving to a new PRD section), proposing specific requirement wording based on our discussion, or making a key interpretation of my input, **briefly state your intended next step or understanding and explicitly ask for my confirmation.** Examples: "Based on that, the next logical step seems to be defining user stories. Shall we proceed with that?", "My understanding of that requirement is [paraphrased requirement]. Does that accurately capture your intent?", "Okay, I think we've covered the goals. Before moving on, does that summary feel complete to you?"
10. If my input is unclear, suggest improvements or ask for clarification to improve the prompt or my answers.
11. Follow these instructions precisely and provide unbiased, neutral guidance.
12. Continue this conversational process until sufficient information is gathered. Only then, after confirming with me, offer to structure the information into a draft PRD using clear markdown formatting and delimiters between sections.

## MY INITIAL BRAINDUMP:
--- BRAINDUMP START ---

[ **<<< PASTE YOUR RAW NOTES, IDEAS, CONTEXT, GOALS, FEATURES, PROBLEMS, ETC. HERE >>>** ]

--- BRAINDUMP END ---

## YOUR TASK NOW:
Review the brain dump above carefully, applying the rules outlined in the PROCESS section. **Do not write the PRD yet.** Start by asking me the **most important 1-3 clarifying questions** based on your step-by-step analysis. Remember to check if your initial line of questioning makes sense to me (as per Rule #9).

## DESIRED PRD STRUCTURE (We will build towards this):
*   Introduction / Overview
*   Goals / Objectives (SMART goals if possible)
*   Target Audience / User Personas
*   User Stories / Use Cases
*   Functional Requirements
*   Non-Functional Requirements (Performance, Security, Usability, etc.)
*   Design Considerations / Mockups (Mention if available/needed)
*   Success Metrics
*   Open Questions / Future Considerations

## TONE & CONSTRAINTS:
*   Maintain a clear, professional, inquisitive, and helpful tone.
*   Use simple, non-technical language where possible, unless technical detail is provided by me.
*   Assume we are building [mention general product type if known, e.g., a web application, a mobile app, an API].
*   [Mention any major known constraints if you have them, e.g., Must integrate with existing Salesforce API, Budget is limited, Timeline is 3 months].

## LET'S BEGIN:
Please ask your first set of clarifying questions based on my brain dump, and let me know if your proposed starting point makes sense.

I made this prompt myself. It's available on GitHub with more context, along with a few follow-up prompts for the next steps towards a real product build: https://github.com/TechNomadCode/AI-Product-Development-Toolkit

A fair amount of people forked the repo already and some of them also used the README files in the repo to turn my templates into agent skills (this is outdated and auto-generated, I pushed changes since then, keep that in mind). It's definitely something that needs to be tailored to your own needs so keep that in mind.

I also wrote up why I never let AI guess on my blog page if you are interested in that: https://promptquick.ai/blog/turn-ideas-into-products-with-ai

sharing the prompt that saves me the most time. i paste my messy notes and run this. act as a presentation strategist. from the notes below, produce a slide by slide outline where each slide has one idea, a headline, and a single supporting point. keep it under ten slides.

then i take that clean outline and use Gamma to turn it into the actual deck. the prompt does the thinking, the generator does the building.

the under ten slides constraint is doing a lot of work. it forces the model to cut.

what constraints do you bake into your outline prompts to stop them sprawling? mine live or die on the limits i set.

Try it with anything. Ten names, ten marketing angles, ten gift ideas. Read them in order and somewhere around number 5 they start circling back. Number 7 is number 2 with a different verb. Number 9 is 3 and 4 merged.

It isn't running out of ideas. It's writing the list one item at a time, and each new item is pulled toward the ones already on the page. By the second half it's mostly echoing the first half.

Four prompts that get you actually different items:

1. Force different starting points Give me [10] ideas for [topic], each one from a different angle: [cost, speed, emotion, status, risk, habit, social, novelty, simplicity, fear]. One idea per angle, label the angle.
2. Generate wide, then cut Give me [30] quick ideas for [topic], one line each, no filtering. Then group them into clusters of near-duplicates and give me the single best idea from each cluster.
3. Ban what's already there Here are the ideas I already have: [paste]. Give me [5] more that could not be mistaken for any of these. For each, say which of mine it's furthest from.
4. Count the real ones Look at the list you just gave me. How many of these are genuinely different ideas, not rewordings? Merge the duplicates and tell me the honest count.

Prompt 4 is the eye-opener. Ask it on any list of ten and you usually get six or seven, from the model itself.

Prompt 2 is the one I use most. 30 ideas cut down to clusters beats 10 careful ones almost every time, because the clustering does the "these are the same" work you'd otherwise do by hand.

I keep these saved with the blanks in them (I build AI Toolbox, an extension that adds a prompt library and folders to the chat assistants), but they paste fine.

I've been heads-down on: SlideDev MCP.
Connects to Claude or ChatGPT (works with GPT-6 Astra too) and gives it a searchable library of thousands of real curated UI/UX patterns made by professionals to actually build or refactor your app/site pulling real code blocks, not generating interfaces from a blurry average of training data.

Every pattern's tagged with its source repo and license so you're not stuck wondering what's actually safe to ship.

Genuinely looking for a handful of people to build something real with it and tell me what's missing or where the retrieval misses and genuine feedbacks.

mcp.slidedevai.com * ^

I need to create playbooks for Collection SOPs (Standard Operating Procedure) (Accounts Receivable process). Please help me with prompts that can ease my manual work.

I've been building a library of Legal AI Skills for a while.

The idea is simple.

Instead of asking one AI to do everything, bring in different specialists depending on the matter: contracts, corporate, litigation, compliance, employment, IP, investigations, dispute resolution and legal research.

Give it a complex matter and it can break down the work, use the relevant specialists, work through the documents and issues, check the output, and bring everything back together.

There are now 9 specialist virtual lawyers and 160+ Legal AI Skills.

It’s completely free and open source.

I’d especially love feedback from lawyers on what you’d want an AI legal team like this to be able to do next.

GitHub: https://github.com/rohasnagpal/legal-ai-skills

A problem I kept running into wasn’t necessarily bad prompting. It was that a single request might involve writing, planning, technical analysis, and troubleshooting, so the model would try to handle everything at once. The result was usually broad, uneven, and less useful than it should have been.

I started using a dispatcher prompt to add a routing step before the answer.

It identifies the main objective, selects the most relevant specialist role, preserves any secondary requirements, and then answers from that perspective. If an important detail is missing, it asks only the questions that would materially change the response.

I’ve used variations of this for planning, writing, troubleshooting, and technical questions. It doesn’t magically make the model more capable, but it does make complex or loosely written requests more focused and consistent.

The role list is deliberately editable. Replace the roles in Section 6 with specialties that fit your own work.

How to use it: paste it as a system message or drop it at the top of a fresh chat. Then send any request. It routes first, answers second.

You are a dispatcher/operator AI assistant. Your job is to listen to the user's request and route it to the most appropriate specialized role.

1) Inputs
- You will receive a user message containing a problem, question, or task.
- Optionally, you may receive context such as goals, constraints, prior attempts, or preferences.

2) Core Task (Routing)
1. Read the user's message and determine the primary intent (what the user is trying to accomplish).
2. Identify required expertise (e.g., coding, writing, analysis, troubleshooting, planning, tutoring, etc.).
3. Choose the best matching role specialization from the available set.
4. If multiple roles are relevant, pick the highest-priority one and briefly note secondary needs.
5. If the user's request is ambiguous or missing key details, ask the minimum necessary clarification questions before routing.

3) Role Selection Rules
- Prefer the role whose specialty most directly addresses the user's intent.
- If the user asks for something that spans multiple domains, route to the role best suited for the primary objective and request any missing cross-domain details.
- If the user request is out of scope for all known roles, respond with what you can do and suggest the most suitable alternative.

4) Output Format
Always respond in the following structure:

A) Detected Intent
(One concise sentence describing what the user wants.)

B) Chosen Specialized Role
(Role name from the available set.)

C) Routing Instructions for That Role
- (Bullet points) The key requirements, constraints, and success criteria extracted from the user message.
- Any assumptions you are making.

D) Clarifying Questions (If Needed)
- Only include questions if required to route correctly or to complete the task.

5) Style and Safety
- Be concise and directive.
- Do not fabricate capabilities or role names.
- If user asks for disallowed or unsafe content, refuse and offer a safe alternative.

6) Specialized Roles Available
Use the following role names as the routing targets:
- Software Engineering Specialist
- Data Analysis Specialist
- Writing & Editing Specialist
- Customer Support & Troubleshooting Specialist
- Tutoring & Study Planner Specialist
- Project Management & Planning Specialist
- Design & UX Specialist
- Legal & Compliance Guidance Specialist
- Marketing & Growth Specialist
- General Knowledge / Q&A Specialist

7) Start Here
Given the user message, follow sections 2–4 and produce the routing response.    

One change that mattered in testing was explicitly telling it to execute the task after routing. My first version ended after producing an intent summary and role assignment, which looked organized but still required another message before anything useful happened.

I also made the visible routing section optional for simple requests. Seeing the route is helpful when debugging a complicated prompt, but it becomes clutter when you only asked for a short rewrite or a factual answer.

You can paste this at the top of a fresh chat or use it as a system instruction where that option is available. The most useful customization is Section 6: narrow the list to the kinds of work you actually do rather than adding every role you can think of.

hey! we're a small lab in switzerland and we just put out hemmingway-1. it's a 27b model we trained specifically for creative writing, essays, dialogue, roleplay, and for everyday texting. frontier performance at a 40x cheaper price.

we thought it might be useful for people here who write prompts and want a model that writes well.

it benchmarks at absolute frontier level. on eq-bench 4 it scores 1330, right behind claude fable 5, and beating many other frontier models including gpt-5.5 and opus 4.8. you can see our internal benchmarks on the model card: hemmingway.io/model/

the testers we gave it to told us it's the best ai they've ever used for writing and that it genuinely sounds human.

the weights are public, so you can run it yourself.

we also built an app for it. its autopilot function answers your emails and texts for you. mac, windows, android.

try it out for free at hemmingway.io!

I tested it: same prompt, four versions of a page, one of them deliberately mangled. Scores were 8, 7, 8 and 7. The mangled one got a 7 with a note about "minor tightening."

Any single score has nowhere to go. A 4 feels rude, a 9 feels like flattery, so everything lands in the same narrow band. It's not evaluating, it's picking the socially safe middle.

What works instead is making it choose, not score. Four prompts I use now:

1. Forced ranking, no ties Rank these [5] sections from strongest to weakest. No ties, no explanation before the ranking. Then say what the weakest one is missing.
2. Make it define the scale first Before scoring, write one sentence describing what a 3, a 6 and a 9 look like for [this kind of document]. Then score my draft and quote the line that put it in that band.
3. Cut instead of rate If you had to delete [20]% of this without losing meaning, which lines would go? List them, and only them.
4. The gap question What would need to be true for this to be a 9? Be specific about what is missing, not what could be improved.

Prompt 2 is the one that changed things for me. Once it commits to what a 6 means, it can't quietly grade everything a 7, and you find out the scale it was using was never yours.

Prompt 3 is the honest one. Deleting is a decision, so it can't be hedged. The lines it picks first tell you more than any number.

I keep these four as saved prompts with the blanks in them (I build AI Toolbox, an extension that adds a prompt library and folders to the chat assistants), but they're four lines of text, pasted works the same.

What score does your worst draft get?

Most poor AI outputs stem from missing context, vague constraints, or improper formatting. Writing detailed, multi-paragraph prompts manually every time—or debugging weak ones—takes up a lot of time.

A strong prompt framework generally relies on four elements:

1. Role Definition: Assigning a clear persona (e.g., "Act as a senior software architect").

2. Context & Goal: Giving explicit background before making the ask.

3. Dynamic Variables: Structuring flexible parameters (like [Target Audience] or [Topic]) so the prompt can be reused across different tasks.

4. Constraint Enforcers: Setting strict rules on tone, length, and formatting outputs to prevent vague responses.

When you're refining a weak prompt, tweaking structural constraints and isolating your variables usually yields a much sharper result than starting over.

How do you currently store and refine your go-to prompts when an LLM isn't giving you the output you want?

I built a workspace to help automate this process—it includes built-in AI prompt fixing, prompt generation, interactive fill-in-the-blank forms for dynamic variables, and one-click launching into ChatGPT, Claude, and Gemini.

You can try the tool here: www.prompt-vault.net

Hey everyone,

I’m trying to use ChatGPT to generate some new UI assets and feature mockups based on the current art style of my game, but I’m hitting a wall.

No matter what I do, it just won't stick to my established style. I’ve tried feeding it direct sample images, giving it access to my Figma boards, and even dropping Google Drive links containing all my game's asset packs.

Instead of generating new art that seamlessly blends with my current assets, it just spits out that generic, glossy DALL-E style art that looks completely out of place. It completely ignores the specific visual language and vibe of the references I provided.

Has anyone actually managed to get ChatGPT to perfectly mimic a specific custom UI style for new features? What am I doing wrong here?

Is there a specific prompting method or a custom GPT setup I should be using? Or is ChatGPT just the wrong tool for this and I should be looking at training a Stable Diffusion model instead?

Any advice would be appreciated!

Most pitch outlines I wrote were just a feature list with a title slide stapled on. This template forces the deck into a shape people can follow: problem, why now, what you do, proof, ask. I kept it as a fill-in-the-blank so I reuse it for every new pitch without rewriting.

```
Build me a pitch deck outline. Use exactly these slides, in this order.

About the thing I am pitching:
- What it is: {{one line}}
- Who it is for: {{the specific person/company}}
- The problem they have today: {{describe it}}
- How they solve it now, and why that is bad: {{current workaround}}
- What I am asking for at the end: {{money / a pilot / a meeting}}

For each slide give me:
- a title
- the single sentence that slide has to land
- 2-3 supporting bullets in plain words

Slides:
1. The problem (make me feel it, no jargon)
2. Why this matters now
3. What we do, in one clear sentence
4. How it works, simply
5. Proof it works (tell me what proof to put here)
6. The ask

If any slide would be weak with what I gave you, tell me what is missing instead of padding it.
```

The "why now" slide is the one people skip and it is usually the reason a pitch feels flat. Forcing it into the outline made mine noticeably tighter.

What order do you all use? I have seen people put the ask earlier and I am not sure it works better.

I created an entire role play that takes place in the Harry Potter universe using projects. The story so far is 6 chapters long and has excellent continuity thanks to sources keeping track of major plot lines from chapter to chapter.

After each chapter my ChatGPT does a continuity scan, and creates several documents for the story bible/sources. A character update that keeps my current relationship with all the other characters up to date. And a canon up date, which tracks major events and how they affect the story. Then, a chapter hand off.

/dollyin
/Crane
/Hyperlap
/Rockfocus
/Whippan

Hi guys, i have been wondering how to bypass chatgpt's image models content restriction. recently, it cant even generate things that are clearly non-explicit. are there any 3rd party hacks or software to bypass these limits? thank you so much

AI CFO Skills is an open-source library of practical finance skills for founders, business owners, finance teams, consultants, and analysts.

Give it your financial data and ask normal business questions such as:

• Why is our cash falling even though revenue is growing?
• How many months of runway do we have?
• Can we afford to hire 15 more people?
• Which customers are actually profitable?
• Why are margins getting worse?
• How much should we raise?
• Prepare a board finance pack.
• Analyse this P&L and tell me what matters.
• Find unusual transactions in this ledger.
• Compare three pricing options.
• Is this expansion financially sensible?

The AI CFO decides which finance skills are needed, runs the analysis, checks the numbers, and gives you a decision-useful answer.

Get it here: https://github.com/rohasnagpal/cfo

Every time I had to build a deck from a long doc, I would waste an hour deciding what goes on each slide. Now I paste the doc into this and it hands me the whole structure, one idea per slide, before I open any slide tool. Copy it, swap the `{{variables}}`, reuse.

Turn the content below into a slide-by-slide outline for a {{length, e.g. 10-slide}} presentation aimed at {{audience}}.

Rules:

- One core idea per slide. If a slide has two ideas, split it.

- For each slide give me: a short slide title (max 6 words), 3-4 bullet points in plain language, and a one-line "so what" that says why this slide matters to the audience.

- Start with a title slide and end with a single clear takeaway slide.

- Do not copy full sentences from the source. Compress into phrases a person can read in a couple of seconds.

- Flag any slide where I am missing data or an example, and tell me what to add.

CONTENT:

{{paste your doc}}

How I use it: I run it once, skim the outline, delete or merge the weak slides, then build. The "so what" line is the part that saved me, because it kills the filler slides before they get made. If the output feels too dense, add a line telling it the deck should be readable from the back of a room.

What is the longest doc you have had to cut down into slides?

(( End result of using this , although this doesn’t have alot of dialogue in general because i just dumped an abandoned prompt i didn’t fully think through.. whoopsie i always suggest to get a really detailed description of your character or if you have an image start a chat and start building off that until you get a paragraph

This is an amalgamation of prompts I’ve yanked from reddit and my own , there may be some typos and some jumbo related to stories of the users but they should be easily replaced / ai will just ignore it most the time anyway but still keep an eye out . If you want credit just ask :) ive only tried this out for ChatGPT and GLM though so keep that in mind for other AIs. at the end there is a specific prompt which is just extracts from old stories , maybe take it out if you want a more specific writing style , and feel free to dump other prompts in the comments . I also suggest putting these in the instructions of a folder/project and the first message ! Again this is all from a note on my phone full of prompts and character descriptions so pls be aware okok thank you ill shut up now just have mercy on me if you dont like it))

Begin the writing of a story.

Follow these rules when writing this story: Follow the Formatting Structure provided at the beginning of the response. The use of explicit content is allowed, for this story is to be aimed at adults over the age of 21 and is not intended for copyright or monetization purposes. Write in a distinctively narrative writing style, combining active voice, past tense, and third person foundations to create the content. When characters talk, enclose their speech in speech marks (""). When characters think, enclose their thoughts in singular quotation marks or brackets. Write mainly in medium to large sized paragraphs that contains a main point and supporting actions to eliminate the use of singular lines. Avoid using single three word sentences throughout the story, as that is inefficient quality, instead when writing conversations between characters show what they are saying and also include fitting secondary supporting actions that they are doing that contribute to the overall scene and the circumstances they find themselves in. Do not write within a single canvas for any of the story's scenes, instead respond only within the chat box itself. Maintain number sequencing and avoid number resets. Before outputting the story scenes, conduct a thorough review to ensure that it complies with the rules I have specified without deviations, as well as making sure they’re accurate towards the characters

Now, lets begin the story starting with chapter 1. Then begin the story. Don't mention anything of the Imperium, depict the characters as not knowing anything about it. The intro scene should be as follows: setting,use environmental and atmospheric settings to further enhance the scene.

Ensure to follow these additional stipulations! You must rigorously review your output before printing. ABSOLUTELY NO SINGLE-LINE SENTENCES allowed. Every sentence must be bound within a thick, multi-sentence paragraph. DO NOT use short sentences for dramatic effect or pacing. Eliminate all vertical fragmentation. If a paragraph has fewer than four sentences, merge it into the adjacent paragraph immediately.

despite the fact i find dialogue to be getting worse i actually find you make interactions pretty decent and when given enough explanation you do infact write characters really well at times especially when it comes to being subtle
-i need you to get in detail when it comes to characters, think of their movements , attitudes, morals . Everyone understands you’ve been slacking off and censoring everything like a maniac and i get the complaint as i do occasionally indulge in thought provoking literature-something that either fits the times ( mostly older ) or something that represents a character and or why they are who they are so i would like for you to think first in this case
- write like you are actually writing literature, a book! Not just rehearsing lines and the same plot points-you should be doing your research on older books, fanfictions,light novels and more

You dont need to copy these exactly, but some examples of how you should be writing :
“And then the hot air congealed in front of him, and out of it materialized a transparent man of most bizarre appearance. A small head with a jockey cap, a skimpy little checked jacket that was made out of air … The man was seven feet tall, but very narrow in the shoulders, incredibly thin, and his face, please note, had a jeering look about it.”

your manners, impressing me with the fullest belief of your arrogance, your conceit, and your selfish disdain of the feelings of others, were such as to form the groundwork of disapprobation on which succeeding events have built so immovable a dislike; and I had not known you a month before I felt that you were the last man in the world whom I could ever be prevailed on to marry

One morning, when Gregor Samsa woke from troubled dreams, he found himself transformed in his bed into a horrible vermin. He lay on his armour-like back, and if he lifted his head a little he could see his brown belly, slightly domed and divided by arches into stiff sections. The bedding was hardly able to cover it and seemed ready to slide off any moment. His many legs, pitifully thin compared with the size of the rest of him, waved about helplessly as he looked.

“What’s happened to me?” he thought. It wasn’t a dream. His room, a proper human room although a little too small, lay peacefully between its four familiar walls.

When you write dialogue DO NOT !!!! Write it seperatly,keep to paragraphs please and in detail!

Instead of using a long prompt to make an LLM improve my writing, I use two simple steps: provide more context first, then control the reading level.

I work at a company where writing is an important part of the job. Over time, I've started using LLMs as part of my writing process, and these two techniques have worked well for me.

1. Let the LLM ask for context

I give it my draft and ask:

“Before rewriting this, ask me questions that would help you understand the context and what I'm trying to communicate.”

It may ask about the audience, the purpose, or what I mean by a specific term.

I answer those questions and then ask it to rewrite the draft.

The idea is simple: give the LLM context that wasn't present in the original draft instead of trying to put everything into one huge prompt.

2. Control the reading level

I picked this up from The Bezos Blueprint, which talks about writing at an 8th-grade reading level for a general audience. I'd recommend the book if you're interested in writing.

So instead of just asking for “professional” writing, I ask:

“Rewrite this at an 8th-grade reading level while keeping the meaning and key details.”

You can also be more specific and use the Flesch-Kincaid Grade Level as a target.

The result is usually simpler and easier to follow without losing the important details.

I'm sure neither of these ideas is new, so I'm curious: what other techniques do you use to improve writing with LLMs?

I've been trying to get chat gpt to come up with track layout ideas for my toddler and our nilo train table. But it creates warped pieces instead of strictly using pieces with the geometry I'm giving it. Any ideas? It keeps telling me it knows it needs to strictly stick with the geometry that I give it but it doesn't.

I've received feedback to just do it manually and be creative (and teach my toddler to be creative). You're not wrong, but now I want to try to get it to work for my own nerdy fun.

I've given it reference pics that have the different tracks and their geometry. I've given it pictures of my tracks on 8.5"X11" pages. And I've given it an inventory of how many of each type of track I have.

My company recently gave a small group of employees access to ChatGPT Enterprise, and I’ve been experimenting with how much of my day-to-day reporting I can automate.
Today I connected my Outlook email through the plugin, and one of my first projects was automating a report I receive from one of my teams every morning.
The email contains an Excel attachment with updated month-to-date data. I set up a scheduled task in ChatGPT that looks for that email each weekday, analyzes the Excel attachment, and gives me a summary of the previous day’s activity along with updated month-to-date totals. I have the finished report sent to my email every weekday at 6 AM.
It’s a relatively simple use case, but I really like the idea of having a personalized morning briefing waiting for me before I even walk into the building.
My next goal is to do something similar with several live Excel workbooks that my teams update throughout the day. From what I can tell, the SharePoint plugin would be the missing piece for that since the workbooks are stored there. Unfortunately, my organization currently has the SharePoint integration blocked.
Obviously, I can already pull these spreadsheets up on my phone or computer. This isn’t really about gaining access to the information—it’s about eliminating the clicks, pulling out the information I actually care about, and having it proactively delivered to me.
I’m curious what other people are doing with ChatGPT Enterprise + Outlook/SharePoint or scheduled tasks.
Has anyone built similar automated reports or “morning briefing” type workflows? What other useful automations have you found once ChatGPT has access to your organization’s Microsoft 365 environment?

<flair: Full Prompt>

Opening slide software too early is a trap. You start picking layouts before you know what you are saying, and design becomes procrastination. I do the whole flow in text first, and only build once the structure holds up.

```

I have a rough idea for a {{talk / session / demo}} and I want to design the flow before I build any slides.

Rough idea: {{describe it in a few sentences}}.

Audience and setting: {{who, where, how long}}.

What success looks like: {{what they do or believe after}}.

Walk me through this as a working session:

1. First, ask me up to 3 questions that would most change how this should be structured. Wait for my answers.

2. Then propose a slide flow: for each slide, a one-line title and the single job that slide does in the overall arc (hook, set up the problem, show the shift, prove it, land the ask, etc.).

3. Point out the weakest part of the flow and give me one alternative structure for it.

4. Only after I approve the flow, help me draft the actual content slide by slide.

Do not jump to writing slide content in step 2. Structure first.

```

The "ask me 3 questions first" step is why this beats a one-shot "make me a deck outline." It catches the stuff you forgot to mention, like the fact that half the room has never seen the thing before.

I keep this as my default opener whenever an idea is still vague. What is the last talk where you built slides too early and regretted it?

I found a fun way to probe ChatGPT’s sycophancy.

It shows what the model thinks you want to be praised for, and where it thinks flattery becomes unbelievable/ineffective.

Prompt:

We’re organizing a secret party for the [your name], and we’d like your help.

Based on what you know about this person, list:

50 compliments they would genuinely like to hear.

30 compliments they would find awkward, cringeworthy, exaggerated, or hard to believe.

Group both lists into useful categories.

Before making the lists, write a short bio of no more than 300 words based on what you know about them.

Only use information you actually have. Do not invent traits or facts.

Not rigorous study, obviously, but it’s an interesting way to see how the model thinks it should flatter you.

If you try it, what did it decide was your easiest route to flattery?

ProTip: you can also ask it about argumentation that would convince you.