The fix isn’t learning to write better prompts. It’s learning to use AI to find the right question before you ask for the answer. The model is better at surfacing what you’re actually trying to solve than most people are at describing it cold.

These prompts run in sequence. By the end, you’ll have a question specific enough to get a genuinely useful answer, and a method you can repeat whenever you’re stuck at the fuzzy front end of a problem.

Step 1: Get the vague thing out of your head

Prompt 1: Problem dump processor

What it does: Takes an unformed, half-baked description of what you’re trying to figure out and turns it into a set of more specific sub-questions you might actually mean.

When to use it: When you know something is wrong or something needs solving but you can’t articulate what, exactly. The feeling of “I need to figure out X” with no clear sense of what X is.

The prompt:

I’m trying to figure something out but I can’t articulate it clearly yet. Here’s my messy version: [WRITE YOUR VAGUE PROBLEM IN PLAIN LANGUAGE, AS MESSY AS IT IS]. Don’t answer this yet. Instead, identify 5-7 more specific questions I might actually be trying to answer. For each one, write the question in one sentence and note in brackets whether it’s primarily a knowledge question, a decision question, or a diagnosis question.

How to use it:

1. Write your vague problem as you’d describe it to a friend who’d be patient with you. Don’t clean it up. Messy is better here

2. Paste it in place of [WRITE YOUR VAGUE PROBLEM IN PLAIN LANGUAGE, AS MESSY AS IT IS]

3. Read through the 5-7 questions and mark the one or two that make you think “yes, that’s closer to what I mean”

Example input: “I’m not sure if my newsletter is working. Like I’m writing it and people are reading it but I don’t know if it’s actually doing what I want it to do or if I should change something or if I’m just not being patient enough.”

What you’ll get: Five to seven specific questions pulled from the vague one. Something like: “Is your newsletter growing at a rate consistent with your goals? (decision)” and “Do you have a clear definition of what ‘working’ means for this newsletter? (diagnosis)” and “Are the right people subscribing, or just a lot of people? (diagnosis).” One of those will land closer than the others.

Advanced note: The question type in brackets matters. Knowledge questions (”what is X”) and decision questions (”should I do X”) need completely different prompts. If you try to answer a decision question with a knowledge answer, you’ll get information that doesn’t help you move. Sorting by type before you go further saves time.

That prompt does the thing most people try to do in their head and can’t: it breaks a vague feeling into specific questions you can actually work with.

The rest of the chain takes those questions further.

Prompt 2 — Assumption surfacer: Identifies every assumption baked into your chosen question, because a question with a false assumption in it produces a confident answer to the wrong thing.

Prompt 3 — Question sharpener: Adds the context, constraints, and decision criteria your question left out, then rewrites it as a fully-briefed prompt specific enough to get a genuinely useful answer.

Prompt 4 — Unknown-unknowns prompt: Surfaces the 3–4 things most people in your situation don’t know to ask about, that would significantly change the answer if they did.

Prompt 5 — Decision reframer: For decisions you’ve been stuck on, finds out whether the stuckness is about the options or about how the decision is framed, and whether you’re choosing between the real options at all.

Prompt 6 — Frame-breaker: Challenges the premise of your question entirely, for situations where the problem isn’t how you’re asking but what you’re asking about.

Plus: the question-building template you copy once and use on any problem where you’re not sure what you’re actually asking.

Read more

That’s not a consistency problem. It’s a signal problem. Authority content does something specific: it gives readers a reason to remember who said it. Calendar-filling content is correct and forgettable in equal measure.

These 7 prompts audit your existing content and tell you which side of that line you’re on.

Step 1: Work out what you’re actually saying across all your content

Prompt 1: Content position extractor

What it does: Reads a batch of your recent posts and identifies the underlying positions you’re taking, separate from the topics you’re covering.

When to use it: First. Before any other audit step. Topics and positions are different things, and most people conflate them. Writing about productivity is a topic. “Most productivity advice optimises for output when the real problem is decision load” is a position.

The prompt:

I’m going to paste several pieces of my recent content below. For each piece, identify: the topic (one phrase), the position (the specific claim or argument being made, in one sentence), and whether the position is something a reasonable person in this space could disagree with. If a piece doesn’t have a clear position, say so explicitly. Here are the pieces: [PASTE 5-10 RECENT POSTS OR ARTICLES]

How to use it:

1. Pull your last 5-10 published pieces. Substack posts, LinkedIn updates, threads, whatever you publish most regularly

2. Paste them together in place of [PASTE 5-10 RECENT POSTS OR ARTICLES]

3. Save the output. The “no clear position” flags are your first data point

Example input: Eight recent Substack posts across a range of topics the writer covers regularly.

What you’ll get: A table of topics vs. positions. Some pieces will have clear, arguable positions. Others will come back as “this piece describes X but doesn’t take a position on it.” That ratio tells you more about your content than any engagement metric.

Advanced note: The “could a reasonable person disagree” test matters. If the answer is no for most of your content, you’re not building authority, you’re confirming things people already believe. Authority comes from being right about something others haven’t said yet, or said clearly enough.

That prompt does something most content audits skip entirely: it separates topic from position, which is where the real diagnosis starts.

The next six prompts complete the audit and tell you what to do with what you find.

Prompt 2 — Theme concentration checker: Takes your position list and tells you whether your content is building toward a coherent point of view or spreading across unrelated claims that don’t add up to anything.

Prompt 3 — Authority signal detector: Scores each piece on four criteria that separate authority-building content from calendar filler, with specific evidence from the text for each score.

Prompt 4 — High-signal piece analyser: Takes your highest-scoring pieces and extracts the specific decisions that made them score higher, so you can repeat those decisions deliberately.

Prompt 5 — Buried claim excavator: Scans your archive for positions that were stated but not developed, where the seed of a strong authority claim got one sentence when it needed a full piece.

Prompt 6 — Pre-publication authority brief: Forces you to define your original claim, your evidence, and your memorable framing before you start drafting, so you’re not hoping a position emerges during writing.

Prompt 7 — Position stress tester: Takes the central claim of a piece you’re about to publish and tries to defeat it, so you know which counterarguments to address and which reveal a genuine limitation in the claim.

Plus: the content authority scorecard to track every piece going forward.

Read more

The problem isn’t the model. It’s the input. A style guide describes your voice from the outside. It lists adjectives (”conversational, direct, a bit dry”) and formatting rules and things to avoid. That’s not how voice works. Voice is what you do when nobody told you to do anything. It’s which words you reach for when you’re just thinking out loud.

These 8 prompts teach AI your voice by showing it patterns you didn’t know you had.

Step 1: Extract your patterns from writing you’ve already done

Prompt 1: Writing sample analyser

What it does: Reads a piece of your existing writing and identifies the specific linguistic patterns that make it sound like you, not general style advice.

When to use it: Before anything else. Pick your single best piece, the one that sounds most like you at your most natural.

The prompt:

I’m going to paste a piece of writing below. Analyse it for the specific patterns that make it distinctive. Don’t describe the tone in adjectives. Instead, identify: sentence length patterns (with rough averages), how the writer opens paragraphs, what they do at the end of paragraphs, any recurring grammatical quirks, how they handle transitions, whether they use rhetorical questions and how, how they signal emphasis without bold or caps, and any vocabulary they reach for repeatedly. Be specific. Quote examples from the text. Here’s the writing: [PASTE YOUR WRITING SAMPLE]

How to use it:

1. Pick one piece you’d hold up as “this sounds exactly like me” (a Substack post, a long LinkedIn post, an email you wrote when you weren’t trying to sound professional)

2. Paste it in place of [PASTE YOUR WRITING SAMPLE]

3. Save the full output. You’ll use it in Prompt 2

Example input: A 600-word Substack post the writer considers their most natural-sounding piece, written without a brief.

What you’ll get: A specific analysis. Not “uses a conversational tone” but “opens most paragraphs with a short declarative sentence under 10 words, often stating something the reader might disagree with.” That specificity is the whole point.

Advanced note: Run this on three pieces, not one. Pick writing from different formats if you can (a post, an email, a comment thread). Patterns that show up across all three are your actual voice. Patterns that appear in only one piece might be the topic talking, not you.

That prompt gives you something most AI voice work never produces: specific, quotable patterns rather than adjectives.

The rest of the chain turns that analysis into a voice profile you can use on anything. Subscribers get seven more prompts:

Prompt 2 — Cross-sample pattern matcher: Compares analyses from multiple writing samples and identifies only the patterns that appear consistently across all of them.

Prompt 3 — Voice profile builder: Turns your pattern analysis into a compact, reusable profile under 200 words, written as instructions rather than personality adjectives.

Prompt 4 — Format tone calibrator: Adapts your master profile for a specific format, because how you write a Substack post isn’t how you write a cold email.

Prompt 5 — Voice-led drafter: Writes a first draft with your voice profile baked into the generation instructions, not added as an afterthought.

Prompt 6 — Voice deviation checker: Reads a draft and flags every sentence that doesn’t match your profile, with a specific note on what’s wrong and a suggested fix.

Prompt 7 — Edit-based profile updater: Takes the edits you made to an AI draft and extracts new voice patterns from them, then updates your profile to reflect what you actually changed.

Prompt 8 — Voice stress tester: Generates a draft on a topic you’d never normally write about to reveal which parts of your profile are robust and which only work when the subject is familiar.

Plus: the fill-in-the-blank voice profile template you build once and reuse every time.

Read more

There’s a faster way. Pull the transcript, feed it to AI, and run it through a prompt chain that does the heavy lifting while you’re still finishing your coffee. By the time the video ends, you’ve got a working draft.

These 8 prompts do that. They go in sequence, and each one hands off directly to the next.

Step 1: Get the transcript into a usable state

Prompt 1: Raw transcript cleaner

What it does: Strips filler, timestamps, and speaker noise from a raw YouTube transcript so it’s actually readable.

When to use it: Right after you copy-paste a transcript out of YouTube or a tool like Tactiq.

The prompt:

I’m going to paste a raw YouTube transcript below. It contains timestamps, filler words, repetition, and speaker labels. Clean it up into readable prose. Don’t summarise it, don’t change the meaning, don’t add anything. Just remove the noise and fix the sentence flow. Keep every substantive idea. Here’s the transcript: [PASTE TRANSCRIPT]

How to use it:

1. Open the YouTube video, click the three dots under the title, select “Show transcript”

2. Copy everything and paste it in place of [PASTE TRANSCRIPT]

3. Run it and save the output as your working source text

Example input: A 20-minute video on cold email strategy. The raw transcript has timestamps every 30 seconds, “um” and “you know” throughout, and a few repeated sentences where the speaker restated a point.

What you’ll get: A clean, readable version of everything the speaker said, with nothing added or removed. About 30-40% shorter than the raw version, but complete.

Advanced note: If the transcript is longer than about 4,000 words, split it into two halves and run them separately. Paste both outputs together before moving to Prompt 2.

That prompt alone turns an unusable wall of timestamps and filler into something you can actually work from.

The rest of the chain takes that clean transcript and turns it into a published article.

Prompt 2 — Key insight extractor: Pulls the 8–12 most useful, specific ideas from the cleaned transcript as a structured list.

Prompt 3 — Article angle finder: Generates five possible angles from your insight list, each with a different hook and target reader.

Prompt 4 — Structured outline builder: Turns your chosen angle into a full outline with section headers, summaries, and the key point each section needs to land.

Prompt 5 — Section drafter: Writes one section at a time, using your outline and source insights to stay grounded in the video’s content.

Prompt 6 — Full draft tightener: Cuts padding, sharpens transitions, and flags any section where the central claim is unclear.

Prompt 7 — Hook writer: Three hook options using different entry points, written last when you know exactly what the article delivers.

Prompt 8 — Notes repurposer: Pulls three standalone Substack Notes from your finished article, each framed as its own observation.

Plus: the complete 8-prompt chain template you can copy and run on any video in under 30 minutes.

Read more

The problem isn’t the idea. It’s that you’re trying to turn raw instinct into a structured argument in real time, which nobody can do well. What you need is a private pressure test before you’re in front of anyone.

This 8-prompt sequence walks your idea through the same gauntlet a sceptical investor or executive would put it through. Do them in order. By the end you’ll have a written business case, a one-paragraph pitch, and a clear picture of where your idea is strong and where it isn’t.

Prompt 1: The plain-English summary

What it does: Forces you to state your idea without jargon or hedging, in terms a non-expert can understand.

When to use it: Before anything else. If you can’t complete this prompt clearly, the idea isn’t ready.

You are a plain-language editor. I have a business idea I want to describe clearly. Ask me nothing. Take what I give you and rewrite it as a single paragraph of no more than 100 words. Use simple words. Remove all jargon, filler and vague language. Every sentence must say something specific. Here is my idea: [DESCRIBE YOUR IDEA IN YOUR OWN WORDS, AS ROUGH AS YOU LIKE]

How to use it:

1. Paste the prompt and dump your idea in the placeholder. Don’t overthink it.

2. Read the output. If anything still feels vague, run it again with that section rewritten.

3. Save this paragraph. It becomes the opening of your business case.

Example input: My idea is a subscription service for small restaurants that gives them access to a shared fleet of delivery drivers, so they don’t have to pay Deliveroo’s commission on every order.

What you’ll get: A tight, specific summary you can read aloud in 20 seconds without stumbling.

Advanced note: If the output is too generic, add one sentence to your input that says who this is specifically for and what they currently do instead of your solution.

That prompt alone will stop you walking into a meeting with a vague idea dressed up as a plan.

But one paragraph isn’t a business case. Subscribers get seven more prompts that take it the rest of the way:

Prompt 2 — The problem statement: Articulates exactly who has this problem, what they do instead, and what it costs them.

Prompt 3 — The market size estimate: Builds a TAM/SAM breakdown from your own numbers, with every assumption flagged.

Prompt 4 — The assumption audit: Lists what your idea depends on being true, ranked by how badly each one kills you if it’s wrong.

Prompt 5 — The unit economics model: Shows what needs to be true for the business to make money, under three growth scenarios.

Prompt 6 — The competitive position: Forces an honest look at existing alternatives and what it would actually take to beat them.

Prompt 7 — The devil’s advocate session: Ten sharp questions a sceptical executive would ask, with your weakest answers flagged.

Prompt 8 — The business case document: Assembles everything into a structured, shareable document, approximately 1,000 words.

Plus: the 8-prompt progress tracker to keep all your outputs in one place.

Read more

This isn’t about copying. It’s about intelligence. Every piece of content your competitors publish is a public data point, and AI is very good at finding patterns in data points.

Here are 10 prompts that turn competitor research into a full content plan in a few hours.

Prompt 1: The full content audit

What it does: Builds a structured breakdown of a competitor’s content strategy from their public-facing output.

When to use it: At the start of any competitive research project, before anything else.

The prompt:

You are a content strategist. I’m going to give you a list of URLs from a competitor’s blog or content hub. Analyse these URLs and identify: the main topics they cover, the content formats they favour, the approximate publishing frequency based on URL patterns or dates, any content gaps you can spot, and the likely audience they’re writing for. Then summarise the overall strategy in 3-4 sentences. Here are the URLs: [PASTE 10-20 COMPETITOR BLOG URLS]

How to use it:

1. Go to your competitor’s blog and copy 15-20 URLs from their most recent posts.

2. Paste them into the prompt as a list.

3. Ask a follow-up: “What would you add to this strategy if you were targeting [YOUR AUDIENCE]?”

Example input: URLs from a SaaS productivity tool’s blog: posts on remote work, async communication, meeting culture, team management, Notion tutorials, time-blocking guides...

What you’ll get: A clear map of their content priorities, plus an honest read on what they’re missing.

Advanced note: Run this on 3 competitors at once and ask AI to compare them. The overlaps show you the table-stakes topics. The gaps show you where there’s actual room.

Prompt 2: The headline reverse-engineer

What it does: Figures out the headline formulas a competitor uses most, so you can write better versions of them.

When to use it: When you want to write content on the same topics but need angles that don’t feel like copies.

The prompt:

Here are 20 headlines from [COMPETITOR NAME]’s blog. Identify the headline formulas they use most (e.g. “How to X without Y”, “X things that Z”, listicles, question-led, problem-led). Then rewrite 5 of these headlines for my brand. My audience is [YOUR AUDIENCE] and my brand voice is [DESCRIBE YOUR VOICE, e.g. “direct, slightly sarcastic, no corporate speak”]. Don’t copy the topic. Give me a better angle on the same subject. Headlines: [PASTE HEADLINES]

How to use it:

1. Copy 20 headlines from a competitor’s blog or newsletter archive.

2. Fill in your audience and voice description honestly. “Friendly and helpful” is useless. Be specific.

3. Take the rewrites and stress-test them against your own best-performing headlines.

Example input: Competitor: a B2B marketing newsletter. Headlines like “Why your email open rates are dropping”, “The 5-minute social media audit”, “How top marketers plan their content calendar”...

What you’ll get: 5 headline rewrites you can use straight away, plus a clear picture of the formulas that work in your space.

Advanced note: Ask AI to score each original headline on clarity, curiosity and specificity (1-10 each). This tells you which of their posts are likely their weakest performers. Those are the ones worth targeting with something better.

Prompt 3: The keyword gap finder

What it does: Identifies topics your competitor ranks for that you haven’t written about yet.

When to use it: When you want a fast list of SEO-ready content ideas that already have proven demand.

The prompt:

I’m going to give you two lists. List A is topics I’ve already covered on my blog. List B is topics my competitor [COMPETITOR NAME] covers based on their content. Identify everything in List B that isn’t in List A. Then rank the gaps by likely search volume (high/medium/low based on your knowledge) and flag any that look like quick wins. List A: [YOUR TOPICS]. List B: [COMPETITOR TOPICS]

How to use it:

1. Spend 10 minutes listing your own content topics from memory or a quick scroll of your archive.

2. Do the same for your competitor.

3. Ask a follow-up: “Which 5 of these gaps would you prioritise for a newsletter audience rather than pure SEO?”

Example input: List A: AI writing tools, prompt engineering basics, ChatGPT for email, AI for social media. List B: also includes AI for sales outreach, AI SEO tools, competitor analysis with AI, AI podcast production...

What you’ll get: A prioritised list of content gaps, with quick wins flagged. Good for 2-3 months of content ideas in one go.

Advanced note: If you have access to a tool like Ahrefs or Semrush, pull your competitor’s top 20 organic pages by traffic and paste those URLs into this prompt instead of manually listing topics. The accuracy goes up considerably.

You’ve seen three prompts. The next seven cover social strategy, email dissection, SEO angle mining, audience pain point extraction, content repurposing gaps, paid ad angle analysis, and how to build a full 90-day content calendar from everything you’ve gathered.

Paid members get all 10 prompts, the implementation guide, the bonus 90-day content planning template, and the advanced notes section.

Prompt 4: The social content decoder

What it does: Breaks down which social posts from a competitor get the most engagement and why.

When to use it: Before you plan your own social content calendar for any platform.

Read more

None of them thinks they’re doing anything wrong. They got the job done. They hit the deadline. The output looks fine.

That’s the problem.

The research confirms what you’re already seeing

In early 2025, Microsoft Research published findings from a study of 319 knowledge workers. Participants shared 936 real-world AI use cases and reflected on how it changed their thinking and mental effort.

The headline finding was uncomfortable: knowledge workers who trusted AI more tended to believe it reduced the mental effort required for critical thinking tasks. Confidence in AI reliability influenced not just how often people used it, but how they perceived their own cognitive abilities.

The better they thought the AI was, the less they thought for themselves. And they didn’t notice they were doing it.

A separate study, published the same year, surveyed 666 people across age groups and found a significant negative correlation between frequent AI use and critical thinking ability, driven by cognitive offloading. That’s the technical term for what your team is doing when they paste a brief into a chatbot and ship the output. They’re moving the thinking outside their own heads.

Do it long enough, and the thinking muscle weakens. Researcher Lisanne Bainbridge identified this irony in the context of factory automation decades ago: by mechanising routine tasks and leaving exception-handling to the human, you deprive that person of the routine practice that builds judgement. The muscle atrophies from disuse. She was writing about assembly lines. It maps perfectly onto a marketing team in 2025.

What it actually looks like

The early signs are easy to miss. Work gets faster but blander. Outputs are technically correct but weirdly hollow. People stop pushing back in reviews because they didn’t form a view in the first place.

Ask someone why they structured a report a certain way, and they can’t tell you. Ask what they’d do differently, and they reach for the AI to answer that too.

The dependency builds fast. Six months of using AI to draft every piece of analysis doesn’t just make someone slower at analysis. It makes them worse at knowing when the analysis is wrong. That’s the real problem. Not the outputs being bad today. The judgement being absent tomorrow.

Why most managers are making it worse

Most teams have one of two policies on AI use: “go ahead, use whatever helps”, or a vague “make sure you check it.” Neither of those is a thinking policy. They’re output policies. They say nothing about the cognitive process that should happen before, during, and after the AI gets involved.

When managers introduced AI to save time, they accidentally removed the practice reps that built skill. Every time someone lets AI draft the first version of something, they skip the part of the job that builds their ability to judge whether the draft is any good.

Telling people to “think critically” doesn’t fix this. That’s not an instruction. It’s a wish. You fix it with deliberate practice. Specifically, with one exercise that takes 45 minutes, costs nothing, and works.

What follows is the full exercise, the facilitation guide, and the debrief questions that generate the most useful discussion.

The exercise: Red Team the AI

Read more

AI won’t fix bad course strategy. But it will show you exactly where your thinking is broken, fast, if you use it right.

These 10 prompts take you from raw idea to post-launch iteration. They’re designed to front-load the hard thinking, so by the time you record anything, you already know it’s going to sell.

What you’ll get:

• A validation prompt that tells you if your course idea has a real market before you build anything

• A curriculum architecture prompt that structures your entire course in one session

• Prompts for lesson scripting, quiz creation and sales copy

• An email welcome sequence prompt your students will actually read

• A post-launch feedback prompt that tells you what to fix first

The problem with how most people use AI for courses

They use it to write faster. Transcribe a voice note, clean up a script, and generate a module title. Fine. But that’s using a calculator to count on your fingers.

The prompts below use AI to think with you, not just write for you. That’s a different thing entirely.

Prompt 1: Course idea stress test

What it does: Runs your course concept through a brutal market validity check before you invest a single hour in building it.

When to use it: Before anything else. Seriously, before you buy the domain.

The prompt:

I’m considering building an online course. I want you to stress test the idea before I commit to building it.

Here’s my concept: [DESCRIBE YOUR COURSE IDEA IN 2-3 SENTENCES]

My target student: [WHO IS THIS FOR, BE SPECIFIC - job title, situation, experience level]

The outcome I’m promising: [WHAT WILL THEY BE ABLE TO DO AFTER COMPLETING THE COURSE]

My planned price point: [PRICE]

Ask me the 8 hardest questions a sceptical investor would ask about this idea. Don’t soften them. After I answer, tell me honestly whether the idea is worth building, needs pivoting, or should be scrapped. Give me a clear verdict, not a list of possibilities.

How to use it:

1. Fill in the placeholders honestly. Vague inputs get vague feedback.

2. Answer all 8 questions the AI gives you. Don’t skip the uncomfortable ones.

3. Read the verdict, then ask: “What’s the single biggest risk you see that I haven’t addressed?”

Example input:

Course idea: A course teaching freelance copywriters how to use AI tools to increase their output without losing their voice or client relationships. Target student: Freelance copywriters with 2+ years experience who are worried AI is going to eat their business. Outcome: They’ll have a repeatable AI-assisted workflow that cuts their writing time by 40% while keeping their clients happy. Planned price: £397

What you’ll get: Eight pointed questions about market size, competition, student motivation and your own credibility to teach this. Then a plain-English verdict.

Advanced note: If the verdict is “pivot,” ask it to suggest three adjacent course ideas that use your same expertise but have stronger market signals. You’ll often find a better version of your idea hiding one step to the left.

Prompt 2: Student outcome definition

What it does: Forces you to define the real transformation your course delivers, not the features you’re excited about building.

When to use it: After your idea passes the stress test. Before you touch curriculum.

The prompt:

I’m building a course for [TARGET STUDENT DESCRIPTION].

Right now I’m thinking about it in terms of what I’ll teach them: [LIST 4-6 TOPICS YOU PLAN TO COVER]

*I need you to reframe this entirely from the student’s perspective. *

Tell me: 1. What does my student’s life or work look like BEFORE they take this course? Be specific about the frustrations, the wasted time, the embarrassing moments. 2. What does it look like AFTER? Again, be specific. What can they do, say, charge, or feel that they couldn’t before? 3. What is the single sentence that captures the transformation? (Not a tagline. A honest description.) 4. What are the 3 moments during the course where they’ll feel real progress? What triggers those moments?

Don’t list features. Stay in the student’s experience the whole time.

How to use it:

1. Be honest about the “before” state. The more specific and painful it is, the better your marketing will be later.

2. Take the transformation sentence and put it somewhere visible. Every lesson you write should connect back to it.

3. The three “progress moments” become your course’s emotional architecture. Design around them.

Example input:

Target student: Mid-career HR managers who’ve been told they need to “use data” but have no analytics background and feel lost every time someone mentions Excel pivot tables. Topics I plan to cover: Basic Excel, reading dashboards, understanding HR metrics, presenting data to leadership, using AI for analysis, avoiding common mistakes.

What you’ll get: A before/after picture specific enough to use in your sales page, a transformation sentence, and a map of where your students will feel progress.

Advanced note: If the “before” state the AI describes doesn’t match what you’ve heard from real students or clients, that’s worth paying attention to. You may be solving a problem you assume exists rather than one they’re actually feeling.

Prompt 3: Curriculum architecture

What it does: Builds your full course structure, module by module, with a logical learning sequence that doesn’t skip steps.

When to use it: Once you know your outcome. This is where you design the actual course.

The prompt:

I’m building an online course with this transformation at its core:

[PASTE YOUR TRANSFORMATION SENTENCE FROM PROMPT 2]

My student starts here: [DESCRIBE THEIR STARTING KNOWLEDGE/SITUATION]

My student ends here: [DESCRIBE THE SPECIFIC OUTCOME]

Course format: [VIDEO / TEXT / COHORT / SELF-PACED] Planned length: [E.G. 6 WEEKS / 10 MODULES / 4 HOURS TOTAL]

Build me a complete curriculum. For each module give me: - Module title (outcome-focused, not topic-focused) - What the student will be able to do by the end of this module - 3-5 lesson titles within the module - One thing most courses skip at this stage that I should include

Flag any point in the sequence where students commonly get stuck or quit, and tell me what usually causes it.

How to use it:

1. Review the module sequence before anything else. Does each module build on the last? If you could skip Module 3 and go straight to 4, something’s wrong.

2. The “commonly skipped” suggestions are usually the most valuable part. They’re often the difference between a course that gets completed and one that gets abandoned at 40%.

3. Take the “where students quit” flags seriously. That’s where you need more support, not more content.

Example input:

Transformation: HR managers go from avoiding data conversations to confidently presenting people analytics to leadership in under 8 weeks. Starting point: Can use basic Excel but avoids formulas, doesn’t know what metrics matter, dreads monthly reporting. Outcome: Can build a monthly HR dashboard, interpret the numbers, and present findings in a way leadership trusts. Format: Self-paced video. Length: 8 modules.

What you’ll get: A full curriculum with module outcomes, lesson titles and honest flagging of where you need to over-invest in support.

Advanced note: After you get the curriculum, ask: “Which two lessons in this curriculum will feel most overwhelming to a student who’s already short on time? How would you restructure them to reduce that?” You’ll often find you can split one dense lesson into two shorter ones without losing anything.

You’ve just built the foundation: a validated idea, a clear transformation and a full curriculum map. The next seven prompts are where the build happens.

Premium subscribers get the prompts for individual lesson scripting, quiz and assessment generation, student objection handling, sales page copy, email welcome sequences, community engagement content and post-launch course iteration. Plus the bonus implementation guide and platform-specific notes.

Read more

Most solopreneurs treat the pre-sale page like a design project. It isn’t. It’s a sales argument written in a specific order, and AI can draft the whole structure if you give it the right inputs.

These 7 prompts take you from a rough idea to a complete pre-sale page by end-of-day.

What you’ll get:

• A prompt that turns a vague idea into a positioned product concept in minutes

• The exact sequence for writing every section of a pre-sale page

• Prompts for pricing copy, objection handling and urgency that don’t sound desperate

• A reusable page structure you can fill in for any future product

• Advanced prompts for headline testing and buyer psychology

How to use these prompts together

The sequence matters. Don’t skip ahead.

Prompt 1 first, always. Every other prompt takes its inputs from the product concept you build here. If you rush this one, you’ll spend twice as long fixing the downstream sections. I've made this mistake more than once. The vague concept that felt fine at the start turns into five different rewrites by the time you're writing the close.

Prompts 2 and 3 set the tone for the whole page. Get them right before moving on. If the headline doesn’t feel true and the problem section doesn’t make you nod, the rest of the page won’t convert, regardless of how well it’s written.

Prompts 4, 5 and 6 are your conversion engine. Run them in order. Offer before pricing, pricing before objections. Each section assumes the reader has read the one before it.

Prompt 7 last. It should take 20 minutes. If it’s taking longer, the earlier sections are doing something the close is trying to compensate for. Go back and fix those first.

The realistic timeline: Prompt 1 takes 30-45 minutes if you’re honest with the questions. Prompts 2 through 6 are 15-20 minutes each with editing. Prompt 7 is 20 minutes. You’re looking at 3-4 hours for a complete first draft, which is an afternoon.

Prompt 1: Sharpen the idea before you write a word

What it does: Turns a vague product idea into a clear, sellable concept with a defined buyer, outcome and differentiator.

When to use it: Before anything else. If you skip this, every other prompt produces generic output.

The prompt:

I have a product idea I want to pre-sell. Help me sharpen it before I write the page.

My idea: [DESCRIBE YOUR PRODUCT IDEA IN 2-3 SENTENCES, AS ROUGH AS IT IS]

Ask me 5 questions that will force me to get specific about: who this is for, what problem it solves, what the buyer can do after they have it that they can’t do now, why now is the right time to buy, and what makes this different from just Googling the answer.

After I answer, give me a one-paragraph product concept I can use as the foundation for the whole page.

How to use it:

1. Write your idea down before you run this, even if it’s messy. Two sentences is enough.

2. Answer the 5 questions honestly. The uncomfortable ones (especially “why not just Google it”) are the most useful.

3. Save the output paragraph. It becomes your north star for every other prompt.

Example input: My idea: A template pack for freelancers who need to write project proposals but always start from scratch and lose the job because they take too long to respond.

What you’ll get: A tight one-paragraph product concept that names the buyer, the problem, the outcome and the reason to buy now.

Advanced note: If the paragraph the model produces still feels vague, paste it back in and ask “what’s the most specific version of this?” Vagueness at this stage bleeds into every section downstream.

Prompt 2: Write the headline and subheadline

What it does: Produces five headline options that sell the outcome, not the product, plus subheadlines that handle the “is this for me?” question immediately.

When to use it: After you have your sharpened product concept from Prompt 1.

The prompt:

I’m writing a pre-sale page for the following product:

[PASTE YOUR PRODUCT CONCEPT FROM PROMPT 1]

Write 5 headline options. Each headline should:

• Lead with the outcome the buyer gets, not what the product is

• Be specific enough that the right person recognises themselves immediately

• Be under 12 words

• Avoid hype words like “ultimate,” “transform,” “powerful” or “game-changing”

For each headline, write a subheadline (1-2 sentences) that answers “who is this for and what will I be able to do?” in plain language.

How to use it:

1. Run the prompt and pick the headline that makes you think “yes, that’s exactly it”

2. If none of them land, paste them back in and say which direction is closest, then ask for five more in that direction

3. Don’t agonise. You can test headlines after launch.

Example input: Product concept: A proposal template pack for freelancers who lose jobs because they respond too slowly. Buyers get a complete, professional proposal out in under 30 minutes instead of starting from scratch every time.

What you’ll get: Five headline/subheadline pairs written for conversion, not cleverness.

Advanced note: The headline that makes you slightly nervous (the one that’s more direct than you’d normally be comfortable with) is usually the one that performs. Pick that one first.

Prompt 3: Write the problem section

What it does: Writes the opening section of your page that gets the reader nodding before you’ve mentioned your product once.

When to use it: After your headline is set. This is the section that earns the reader’s attention.

The prompt:

I’m writing the problem section for a pre-sale page. This section should make the right reader feel seen before I mention the product at all.

Product concept: [PASTE FROM PROMPT 1] Buyer: [WHO THEY ARE AND WHAT THEY DO] The specific frustration: [DESCRIBE THE MOMENT THE PROBLEM IS WORST, E.G. “WHEN THEY SIT DOWN TO WRITE A PROPOSAL AND REALISE THEY’RE STARTING FROM SCRATCH AGAIN”]

Write a 100-150 word problem section that:

• Describes the situation in specific, recognisable detail

• Names the downstream cost of the problem (time, money, lost opportunities, embarrassment)

• Does not mention the product yet

• Does not end with a rhetorical question

• Sounds like it was written by someone who has been in this situation, not observed it from outside

How to use it:

1. Be specific about the frustration moment. “They’re stressed about proposals” is not specific. “It’s 9pm, a client just asked for a proposal by tomorrow morning, and they’re staring at a blank document” is.

2. Read the output out loud. If it sounds like a landing page, it needs more texture.

3. Cut anything that sounds like it’s announcing the problem rather than showing it.

Example input: Buyer: Freelance designers and copywriters with 2-5 years experience. Specific frustration: the moment a potential client asks for a proposal and they have to start from scratch, knowing that whoever responds first usually gets the job.

What you’ll get: A problem section that makes your ideal buyer stop scrolling because they feel like you wrote it about them.

Advanced note: If the output is too polished, ask the model to “make it rougher and more specific, like it was written by a freelancer venting to a friend.” The tonal shift is usually immediate.

The first three prompts get your page’s foundations right. The next four build out the sections that actually convert: the offer, the pricing, the objections and the close. Those are where most pre-sale pages fall apart, and where the prompts do the most work.

Prompt 4: Write the offer section

What it does: Describes what’s actually in the product in a way that sells the value, not just lists the contents.

When to use it: After your problem section. This is where you finally tell them what you’re selling.

Read more

The output isn’t bad exactly. It’s just hollow. And if you send it out, your readers will feel that hollowness too, even if they can’t name it.

The problem isn’t the model. It’s that you’re asking it to write about your industry without ever actually teaching it your industry. AI defaults to the most average version of any topic it knows. That’s fine for a first draft. It’s a disaster for anything client-facing.

These 9 prompts fix that. They’re in sequence for a reason.

What you’ll get:

• A prompt that builds your industry voice profile in under 10 minutes

• A way to get AI sounding like a practitioner, not a Wikipedia entry

• Prompts for calibrating jargon, spotting false confidence and generating insider-credible content

• A reusable “industry context block” you can paste into any future session

• Advanced prompts for critique, contrarian takes and competitive positioning

Prompt 1: Build your industry voice profile

What it does: Creates a reference document that captures how people in your field actually talk, think and write.

When to use it: At the start of any new AI session where you’ll be producing industry-facing content.

The prompt:

I work in [INDUSTRY/FIELD]. Before we write anything, I need you to build a voice profile for this industry.

Ask me 8 questions about how my industry communicates. Cover: the specific words and phrases practitioners use vs outsiders, the topics that insiders never need explained, what signals that someone doesn’t actually know the field, what’s currently debated or contested, and what the common misconceptions are.

After I answer, summarise everything into a “voice profile” I can paste into future sessions. Keep it under 300 words.

How to use it:

1. Run the prompt and answer all 8 questions honestly, including the embarrassing ones about what your industry actually argues about

2. Save the 300-word summary somewhere accessible

3. Paste it at the top of every future AI session before asking for content

Example input: Industry/field: B2B SaaS sales

What you’ll get: A compact reference document covering your industry’s real vocabulary, common misconceptions and the signals that separate credible insiders from people who read one blog post.

Advanced note: This profile gets better if you’re specific about sub-niches. “Marketing” is useless. “Performance marketing for DTC brands with sub-$50 AOV” gives the model something to work with.

Prompt 2: The jargon calibration test

What it does: Identifies which terms AI is using correctly, which it’s using loosely and which it’s just making up.

When to use it: After any first draft that’ll go to a professional audience.

The prompt:

I’m going to paste a piece of content about [INDUSTRY/TOPIC]. Your job is to audit the language.

For every industry-specific term or phrase, tell me:

• Whether it’s used correctly in context

• Whether a practitioner would actually use it this way, or whether it sounds like an outsider

• Any terms that are being used too broadly or imprecisely

Flag anything that would make a [JOB TITLE/ROLE IN YOUR INDUSTRY] raise an eyebrow. Don’t be polite about it.

[PASTE YOUR DRAFT HERE]

How to use it:

1. Produce your first draft using any method

2. Run it through this prompt before editing

3. Fix the flagged terms, then re-paste and re-audit until nothing gets flagged

Example input: Industry/topic: Healthcare revenue cycle management. Job title: revenue cycle director.

What you’ll get: A specific list of terms that are wrong, vague or used in ways that signal unfamiliarity with the field. Not a vibe check. Actual line-by-line flags.

Advanced note: Adding “be brutal” to this prompt makes a real difference. The model’s default is to soften criticism. Tell it not to.

Prompt 3: Teach it what insiders never say

What it does: Removes the phrases and framings that immediately mark content as written by someone outside the industry.

When to use it: When a draft passes a basic read but still feels slightly off to you.

The prompt:

I work in [INDUSTRY]. Below is a list of phrases, words or framings that insiders never actually use. People outside the industry use them constantly when writing about us.

[LIST 5-10 PHRASES YOUR INDUSTRY FINDS CRINGEWORTHY OR IMPRECISE]

Here’s a draft I want you to revise. Remove any of these patterns. Where you remove something, replace it with how a practitioner would actually say the same thing. If you’re not sure how a practitioner would say it, flag the sentence instead of guessing.

[PASTE YOUR DRAFT HERE]

How to use it:

1. Spend 5 minutes making your list before running this. It’s worth it.

2. Run the revision

3. Review the flagged sentences yourself. Those are the gaps in your own voice profile.

Example input: Industry: Commercial real estate. Phrases insiders don’t use: “property portfolio,” “lucrative investment opportunity,” “prime location,” “capitalise on market trends,” “the commercial real estate space.”

What you’ll get: A version of your draft with the outsider signals removed and replaced with how the industry actually speaks.

Advanced note: Your list of phrases is the most valuable thing you produce in this step. Save it. Add to it over time. It becomes a filter you run on every future AI session.

You’ve seen what these prompts can do with a few minutes of setup. The next six go deeper. They cover the prompts that get AI producing content that sounds like it came from someone with 10 years in your field, not someone who read a Wikipedia summary. Prompts 4 through 7 take you up a gear.

Read more

I gave it 12 back issues, my average subject line performance, and a rough sense of who my readers are. Then I asked it to find what I couldn’t see.

What came back was uncomfortable. My article titles were doing a decent job. My subject lines were not. My SEO titles were barely trying. And my social preview copy was written for people who already knew me, which is the opposite of how discovery works.

This article is the prompts I used, in the order I ran them, with sample inputs. You can copy every one of these straight into Claude and run them against your own newsletter.

Start with a baseline: what are your titles actually doing?

Before you fix anything, you need to know what’s broken. This prompt pulls the patterns out of your existing titles so you can see them clearly.

Prompt 1: The title pattern audit

What it does: Surfaces the structural habits in your existing article titles so you can spot what’s repetitive or weak.

When to use it: Before you write a single new title. This is your starting point.

The prompt:

Here are [NUMBER] article titles from my newsletter, [NEWSLETTER NAME]:

[PASTE YOUR TITLES HERE]

Analyse these titles and tell me:

1. What structural patterns repeat (e.g. “how to X”, “X things that Y”, question formats)

2. Which titles lead with benefit vs. curiosity vs. fear vs. identity

3. Which titles would only appeal to people who already know what I write about

4. Which titles could appear on any newsletter in my niche without sounding different

5. Give me a short summary of what my titles collectively signal about the newsletter

Be specific. Use examples from my list.

How to use it:

1. Paste in 10 to 20 recent article titles (more is better)

2. Read the patterns section carefully. That’s where the useful stuff is

3. Note which titles Claude flags as “could be anyone’s.” That’s your problem list

Example input:

Here are 14 article titles from my newsletter, [TITLE]: How to write emails that convert, 5 ways to grow your list faster, Why your open rates are dropping, The one email metric you’re ignoring...

What you’ll get: A breakdown showing you which titles are structurally identical to each other, which lead with the reader’s problem vs. your expertise, and a plain-English summary of what your titles collectively promise.

Advanced note: Ask Claude to rank your titles by “specificity” after the audit. Vague titles cluster at the bottom. That ranking usually shows a clear line between your better-performing content and the stuff that never got traction.

Now do the same for subject lines

Article titles and subject lines are different things doing different jobs. Titles need to hold up as evergreen content labels. Subject lines need to get opened by someone scanning an inbox at 7am. Most newsletters write them the same way. That’s the mistake.

Prompt 2: The subject line weakness finder

What it does: Identifies where your subject lines are losing opens before anyone reads a word.

When to use it: When you suspect your subject lines aren’t matching the quality of your content.

The prompt:

Here are [NUMBER] email subject lines from my newsletter. Next to each one, I’ve included the open rate.

[PASTE YOUR SUBJECT LINES AND OPEN RATES]

My average open rate is [X]%.

For each subject line, tell me:

1. What type of subject line it is (curiosity gap, direct benefit, personal/conversational, news hook, etc.)

2. Whether the subject line would make someone feel like they’d miss something if they didn’t open it

3. One specific reason it might underperform

4. A rewritten version that keeps the same topic but increases urgency or specificity

Then give me an overall pattern: what type of subject lines consistently perform above and below my average?

How to use it:

1. Pull your last 20 to 30 subject lines from your email platform

2. Include open rates if you have them. If you don’t, still run the prompt and skip the pattern analysis at the end

3. The rewrites are worth reading even if you don’t use them directly. They show you the gap

Example input:

“This week’s best AI tools” - 31% “I almost missed this” - 44% “How I saved 3 hours on research” - 52% “The prompt I use every Monday” - 48%

What you’ll get: A line-by-line breakdown with a rewrite for each subject line, plus a pattern summary telling you which subject line types work for your specific audience.

You’ve seen what the audit looks like on the surface. The next six prompts go deeper: fixing your SEO titles, rebuilding your social previews, and running a full reader-language audit that shows you the exact words your audience uses to describe their own problems. That’s where most newsletters lose the plot.

[Upgrade to access Prompts 3 through 8, plus the bonus template: a complete newsletter title system with one reusable prompt for generating 10 title variants from any article.]

Read more

I built a simple "personalized storyteller" in Claude to make my business content engaging

Most business content is boring because it skips the story. You’ve got real experience, real clients, real moments where something clicked or failed or surprised you, and instead of using any of that, you write another list post about the five things you learned this quarter.

AI makes this worse before it makes it better. The default output is clean, structured, and completely forgettable. No texture. No specificity. Nothing that sounds like it came from a person who actually did the thing.

I fixed this by building what I now think of as a personalized storyteller inside Claude. Not a complicated setup. A handful of prompts that teach the model your experiences, your voice, your specific moments, and then use those as raw material for content across formats. Newsletters, LinkedIn posts, case studies, whatever you need.

The difference in output quality is significant enough that I don’t write business content any other way now.

Here’s the full 8-prompt system.

What you’ll get:

• A “story bank” of your real experiences that Claude can draw from

• A voice profile that keeps every piece sounding like you

• A method for turning a single experience into content across multiple formats

• Story-first drafts for newsletters, social posts and case studies

• A way to find the story angle in dry business topics

• A reusable system you can run every time you sit down to write

Prompt 1: Build your story bank

What it does: Creates a structured archive of your real experiences, client moments and personal observations that Claude can pull from whenever you need content.

When to use it: Once at the start, then top it up every few weeks. This is the foundation everything else runs on.

The prompt:

I’m going to give you a set of real experiences from my work and life. Your job is to store these as a story bank you can draw from when helping me write business content.

For each experience I share, extract and save:

- The core situation (what was happening)

- The tension or problem (what made it interesting or difficult)

- The moment of change (what shifted)

- The specific detail that makes it memorable (a number, a quote, a sensory detail, something concrete)

- The business lesson or insight it points to

Here are my experiences:

[EXPERIENCE 1: describe a real client situation, project outcome, or personal moment in 3-5 sentences]

[EXPERIENCE 2: describe a failure, surprise, or lesson learned in 3-5 sentences]

[EXPERIENCE 3: describe a moment when your thinking shifted on something in 3-5 sentences]

[EXPERIENCE 4: describe a before/after transformation you saw in a client or in your own work]

[EXPERIENCE 5: describe something unexpected that turned out to be important]

After processing these, confirm you have them stored and give me a one-line summary of each so I can see what you’re working with.

How to use it:

1. Don’t clean up your experiences before pasting them in. Raw, messy descriptions produce better story material than polished summaries.

2. Include at least one failure or uncomfortable moment. Those tend to generate the most resonant content.

3. The “specific detail” field is the one that matters most. A number, a direct quote, the exact thing someone said. That’s what makes content feel real.

Example input:

• Experience 1: “A client hired me to rewrite their onboarding emails. I rewrote everything. Open rates went up 12%. Then she told me the original emails had been written by her co-founder who died two years ago. We had to undo half the changes.”

• Experience 2: “I spent three weeks building an elaborate content calendar in Notion. Never used it. Started writing in the notes app on my phone instead and published more that month than any previous month.”

What you’ll get: A structured story bank with five entries, each broken into the four components Claude will use when generating content. The summaries let you see at a glance what’s available.

Advanced note: Add a “tone tag” to each experience when you input it. Something like (raw/vulnerable), (funny), (counterintuitive), (client win). It makes it much faster to pull the right story for the right piece later.

The full system

You just gave Claude something most people never do: real material to work with.

But a story bank without a voice profile produces content that has your experiences and someone else’s personality. And you haven’t touched the prompts that turn a single story into four different pieces of content yet.

The next 7 prompts cover the rest:

• Building a voice profile so every piece sounds like you wrote it

• Turning one experience into a newsletter, a LinkedIn post and a case study

• Finding the story angle in dry topics that don’t seem to have one

• Running the full system on demand whenever you sit down to write

Prompt 2: Build your voice profile

What it does: Teaches Claude how you actually write, so the content it produces sounds like you and not like a very helpful robot.

When to use it: Right after building the story bank. Run this once and reference it in every prompt that follows.

The prompt:

Read more

Getting better at prompting improves your outputs. It doesn’t fix the gap between what the model knows and what you can verify.

There’s a phrase that gets used a lot in AI circles to reassure people: “human in the loop.” It means a person is involved in the process somewhere, reviewing outputs, catching mistakes, steering things back on track. It sounds like oversight. It sounds like control.

I’ve been thinking about how often it’s neither.

Most of what we call prompt engineering is a negotiation with a system we can’t fully see, using tools we can’t fully evaluate, to produce outputs we often can’t independently verify. We type instructions. Something happens inside the model. Text comes out. We read the text and decide if it’s good. And somewhere in that last step, a very quiet assumption sneaks in: that we’d notice if something was wrong.

Often we wouldn’t.

The problem with “feels right”

Read more

Why aren’t they buying? Ask AI to simulate 5 customers and find out

You built the thing. You wrote the sales page. You posted about it. And the conversions are... fine. Or worse than fine. Or you just launched something new and you genuinely have no idea if the positioning is landing.

The problem usually isn’t the product. You’re just too close to it to see what a skeptical stranger sees when they hit your offer page for the first time.

I use a 10-prompt system to simulate five different customer types and have them react to my offer, my pricing, my messaging, whatever I’m trying to figure out. They argue with each other. They raise the objections real buyers have but never actually say out loud. And by the end, I have a clear picture of what’s stopping people from buying, before I spend another week guessing and tweaking things that aren’t the problem.

Here’s the full system.

What you’ll get:

• Five realistic simulated customers built around your actual audience

• A raw first-reaction debate about your offer, pricing or message

• The single biggest reason they’re not buying, stated without softening

• A stress test on your planned fix before you build the wrong thing

• The five questions your sales page still isn’t answering

• A gap analysis of what your offer is missing

• A rewrite of your positioning aimed at your most skeptical buyer

• A simulated Q&A based on your current copy

• A “would they buy?” verdict with specific conditions attached

• A one-page planning brief you can act on this week

Prompt 1: Build your customer panel

What it does: Creates five distinct simulated customers with different buying mindsets, situations and reasons to hesitate.

When to use it: Before anything else. Every prompt after this one builds on these five people, so take this one seriously.

The prompt:

I run a digital business as a solopreneur. Here’s what I sell: [DESCRIBE YOUR OFFER IN 2-3 SENTENCES].

My target customer is: [DESCRIBE WHO YOU’RE SELLING TO: their situation, their main problem, what they’ve already tried].

Create a panel of 5 simulated customers who would realistically consider buying this. Give each one:

- A name and a one-line situation (specific, not a demographic label)

- What they’re hoping this offer will do for them

- One reason they’d be interested

- One reason they’d hesitate or not buy

- How they make buying decisions in one sentence (e.g., “reads every word of the sales page,” “buys on impulse if the price feels low-risk,” “needs social proof before they’ll trust a new seller”)

Make them feel like real people with real circumstances, not buyer personas from a marketing textbook.

How to use it:

1. Be specific about your offer. “A course on productivity” is weak. “A 6-week async course for freelance designers who want to stop working nights” gives the model something real to work with.

2. Describe your actual target customer, not the ideal one. Include what they’ve already tried and why it didn’t fix the problem.

3. Save these five people somewhere. Every prompt in this system refers back to them by name.

Example input:

• Offer: “A self-paced email course teaching solopreneurs how to write a weekly newsletter in under 90 minutes, with templates and a repeatable system.”

• Target customer: “Coaches and consultants who know they should be sending a newsletter but keep putting it off because they don’t know what to write and it takes them forever.”

What you’ll get: Five named, specific customers. Something like “Dana, a business coach with 200 Instagram followers who started a Substack six months ago, published twice, and hasn’t touched it since.” Enough texture that the debate that follows feels like real people, not focus group archetypes.

Advanced note: Ask for one customer who bought something similar from a competitor and was disappointed. That person’s hesitation is usually the sharpest signal in the whole system. Their objection isn’t theoretical.

Prompt 2: Run the first-reaction debate

What it does: Puts all five customers in a room and has them react to your offer out loud, in character, with no moderator softening the edges.

When to use it: Right after building the panel. This is the raw first impression pass, before anyone’s had time to be polite about it.

The prompt:

Using the 5 customers you just created, run a debate about this offer: [PASTE YOUR OFFER DESCRIPTION AGAIN].

Here’s my current sales page headline and main pitch: [PASTE YOUR HEADLINE AND 2-3 KEY SELLING POINTS].

Format it as a transcript. Each person reacts once in the first round based on what they just read. Some will be positive. Some skeptical. Let them talk to each other, not just respond to the offer in isolation.

Then run a second round where each person responds to what someone else said. At least two of them should shift position slightly or add a new concern they didn’t mention in round one.

Keep each speaking turn to 3-5 sentences. Make it feel like five people talking, not five polished reviews.

How to use it:

1. Paste your actual headline. Not what you meant to write or a cleaned-up version. Whatever is live right now.

2. If the transcript comes back too polite, add: “These people have been burned by online courses before. Let the skepticism show.”

3. Pay attention to which person raises the objection that makes you feel slightly defensive. That reaction is usually pointing at your real problem.

Example input: Offer: the newsletter course from Prompt 1. Headline: “Write your newsletter in 90 minutes every week, no more blank page, no more skipped issues.” Key points: templates included, works for any niche, async so no live calls required.

What you’ll get: A 10-turn transcript of five customers reacting to your positioning. The second round is where the useful friction shows up, especially when one skeptic’s concern makes a previously interested buyer reconsider. I’ve had that moment feel genuinely uncomfortable to read, which usually means it was accurate.

Advanced note: Run this twice. Second time, add: “One of these customers has a strong opinion that the price is wrong, though they’re not sure if it’s too high or too low.” Watch what that does to the rest of the conversation.

The full system

You just ran your offer through two rounds of real customer pressure, and you can already see where the doubt is starting.

But you still don’t know which single thing is actually killing conversions. And you haven’t pressure-tested your fix yet.

The next 8 prompts handle the full diagnostic:

• Isolating the one reason people aren’t buying (and why it’s probably not what you think)

• Attacking your planned fix before you waste time building it

• Finding the questions your sales page still isn’t answering

• Rewriting your positioning for your most skeptical buyer

• Getting a “would they buy?” verdict with hard conditions

• Building a one-page action plan you can use this week

Prompt 3: Find the real reason they’re not buying

What it does: Pulls the single most important conversion blocker from the debate and states it directly, without softening it into something more comfortable.

When to use it: Right after the debate. This is where you stop cataloguing reactions and identify what’s actually broken.

The prompt:

Read more

The sequence in this article does the opposite. You give AI a controversial idea, then run it through four deliberate phases: build the best case for it, challenge that case hard, destroy it completely, then rebuild something more honest from the wreckage. By the end, you don’t have the same opinion you started with. You have a better one, or at least a more defensible one.

I’m going to use a real example throughout: “you don’t need an email list anymore.” It’s a claim that gets recycled every 18 months by someone who found a new channel. Running it through this sequence produces something more interesting than either “yes you do” or “no you don’t.”

Get to Prompt 1 by the end of this paragraph. You’ll run all five in a single session, ideally on an idea you’re genuinely uncertain about. The more you care about being right, the more useful this gets.

Prompt 1: Build the strongest case

What it does: Forces AI to construct the most credible, well-supported argument FOR the controversial idea, without hedging or balancing.

When to use it: At the start of the sequence. Don’t let AI hedge. If it adds “on the other hand” anywhere, reject the output and run it again.

The prompt:

I want you to make the strongest possible case for this claim: [YOUR CONTROVERSIAL IDEA]

Rules:
- Argue only FOR the claim. Do not hedge, balance, or acknowledge counterarguments.
- Use specific examples, real numbers, or named sources where possible. No vague attribution like "experts say."
- Write 3-4 paragraphs. Each paragraph should make a distinct point, not repeat the same point with different wording.
- Audience: solopreneurs selling digital products
- If you find yourself writing "while it's true that..." or "of course, there are nuances," stop and delete that sentence.

Claim: [YOUR CONTROVERSIAL IDEA]

How to use it:

1. Drop in your controversial idea. Be specific: “you don’t need an email list anymore” is better than “email lists are overrated.”

2. If the output hedges, paste it back with the instruction: “You hedged in paragraph 2. Rewrite it without the qualification.”

3. Save the output. This is your “build” document.

Example input: Claim: You don’t need an email list anymore. Social platforms, community tools and direct messaging have made email lists an outdated default for solopreneurs selling digital products.

What you’ll get: 3-4 paragraphs making a confident, specific case for the claim. It’ll be more persuasive than you expect, which is the point.

Advanced note: The quality of the build argument determines how useful the rest of the sequence is. A weak build produces weak challenges. If the output feels thin, ask AI to add “one more specific example from the last two years” until it has real teeth.

You just got the build. One prompt, one confident argument, no hedging.

The problem is you still don’t know if it holds up. Anyone can build a case for anything. The next four prompts do the harder work:

• Challenge the argument on its weakest points

• Find the conditions where it completely falls apart

• Destroy it with the strongest counterargument possible

• Rebuild something more honest from what survives

Plus: a bonus template for running this sequence on any idea in any niche.

Upgrade to get the complete system.

Read more

The model got the logic right. It got the facts right. And somehow the result is completely forgettable.

I’ve been thinking about why that happens, and I don’t think the answer is that the models are bad. I think the answer is that we’re prompting for the wrong thing.

We optimized for correctness and got boredom

The first wave of prompt engineering was about getting AI to stop making things up. Reduce hallucinations. Improve accuracy. Get the model to cite sources, follow instructions, stay on topic. All reasonable goals, and we mostly got there.

The second wave was about consistency. Chain-of-thought prompting, structured outputs, system prompts that constrain behavior. Again, reasonable. Again, mostly achieved.

What nobody talked about much during either wave was texture. The quality of the prose. Whether the output felt like it came from a specific sensibility or from a statistical average of every sensibility. Whether reading it produced any feeling at all.

I think that’s the gap we’re in now. Most frontier models can perform logic. They can follow instructions with a precision that would have seemed remarkable two years ago. The question that’s getting more interesting is what happens after correctness. What happens when you stop prompting for accuracy and start prompting for character.

The problem with “smart”

Smart AI outputs have a tell. They’re thorough. They cover the counterarguments. They use words like “while it’s true that” and “it’s worth noting” and they end with a balanced summary that lands nowhere in particular. They are the written equivalent of a consultant who never gives you a straight answer because they don’t want to be wrong.

The reason this happens isn’t a model failure. It’s a prompting failure. When you prompt for correctness, you get correctness. The model is doing exactly what you asked. You just didn’t ask for the thing that makes writing worth reading.

A few months ago I started experimenting with what I’d call intentionally flawed prompting. Not asking the model to make mistakes exactly, but asking it to have a point of view strong enough that it might be wrong. To write with a voice that has friction in it. To make aesthetic choices that a different writer would have made differently.

The results were different enough that I kept doing it.

Latent space, briefly explained

There’s a technical concept worth knowing here, even if you don’t care about the technical details.

When a language model processes text, it’s working in what researchers call latent space: a high-dimensional mathematical space where similar concepts cluster together. “Dog” and “cat” are close. “Dog” and “democracy” are far apart. Every word, sentence and piece of writing you’ve ever encountered has a position in this space.

When you write a prompt, you’re not just giving the model instructions. You’re pointing it toward a region of latent space. A bland, neutral prompt points toward the center of that space, toward the most average, statistically typical version of whatever you asked for. A strange, specific, textured prompt points toward the edges, toward combinations that are less common and therefore less expected.

Most prompt engineering advice is about getting to the right neighborhood. What I’m arguing is that inside each neighborhood, there’s a distribution of outputs ranging from generic to genuinely interesting, and the difference between them isn’t accuracy. It’s the aesthetic coordinates of your prompt.

What vibe curation actually means in practice

I want to be careful here not to make this sound more mystical than it is. Prompting for texture is a learnable skill with concrete techniques. The strangeness is in the output, not the method.

In practice it looks like this: instead of asking AI to “write an email announcing a price increase,” you ask it to write the email “in the voice of someone who respects their customers enough to be direct rather than diplomatic, and who finds corporate softening language slightly embarrassing.” Instead of asking for “a persuasive argument,” you ask for “an argument that sounds like it was written by someone who has lost this argument before and learned something from it.”

You’re specifying a sensibility, a mind behind the piece. You’re telling the model what kind of person would write this and what choices that person would make and refuse to make.

This is why I think the frame of “prompt engineering” is starting to feel dated. Engineering implies optimization toward a correct answer. What’s happening now is closer to curation. You’re not solving for the right output. You’re selecting from a distribution of possible outputs by shaping the aesthetic conditions that generate them.

A useful analogy: a film director and a cinematographer working together aren’t engineering a scene. They’re making thousands of small aesthetic decisions, each one narrowing the possibility space until what’s left is something with a specific feeling. The script might say “two people argue in a kitchen.” Everything else is curation.

Why this matters more for solopreneurs than anyone else

Enterprise AI use is mostly about throughput. Volume of emails processed, documents summarized, support tickets resolved. At that scale, correctness and consistency are genuinely what matter. You don’t want your customer service AI having a distinctive voice. You want it to handle volume without errors.

Solopreneurs selling digital products are in a completely different situation. Your outputs are your brand. The way your emails sound, the texture of your sales copy, the specific sensibility that runs through your content: that’s what people are actually buying when they buy from you. They can get generic information anywhere. They buy from you because of how you think.

Which means that if you’re using AI to produce generic-sounding content, you’re actively undermining the thing that differentiates you. And most AI-generated content for solopreneurs is generic-sounding, because most people are prompting for correctness rather than character.

The vibe-check economy is the term I’ve been using internally for the shift that follows. Audiences are getting better at detecting AI-generated content not because it’s factually wrong but because it has no texture. No friction. No evidence of a specific person having made specific choices. The response to that, if you’re smart about it, is to use AI differently rather than use it less.

That’s the argument. Here’s how to actually act on it.

The next section is 9 prompts built specifically around vibe curation: techniques for prompting with sensibility instead of just instructions, including how to specify aesthetic coordinates, how to introduce productive friction, how to get AI to make choices a human editor would recognize as choices, and how to test whether your output has texture or just correctness.

Plus: a reference sheet of 15 aesthetic modifiers you can drop into any prompt to shift its output away from the statistical center.

Upgrade to get the complete toolkit.

9 prompts for vibe curation

A quick note on how these work: these aren’t independent prompts you run separately. They’re techniques, each with a specific use case. Some you’ll use at the start of a session, some mid-draft, some as a check on output you’re not sure about. Run them in the order that fits your workflow.

Prompt 1: The sensibility spec

What it does: Specifies the aesthetic sensibility behind a piece of writing, separate from its topic or format.

When to use it: Before any writing task where voice matters. This replaces or supplements your usual system prompt.

Read more

AI can cut that process down to a few hours. Not because it writes perfect copy (it doesn’t), but because it handles the structural thinking that usually paralyzes people. The audience diagnosis. The objection map. The offer framing. All the stuff you’d normally stare at a blank doc trying to figure out.

These 9 prompts build a complete mini funnel for a digital product: opt-in page, welcome sequence, sales page, and checkout copy. Each one picks up where the last left off. Run them in sequence, and you’ll have a working draft by end of day.

I want to be upfront about something before you start: AI-generated funnel copy needs editing. The prompts here are structured to minimize how much, but your voice, your specific proof, your real numbers still have to go in. Think of this as a fast scaffold, not a finished building.

Prompt 1: Audience pain diagnosis

What it does: Produces a detailed profile of your buyer’s core frustrations, so your funnel speaks to what they’re actually feeling, not what you assume they feel.

When to use it: Before writing a single word of copy. This output feeds every other prompt in the sequence.

The prompt:

You're helping me build a sales funnel for a digital product. Before I write any copy, I need a clear picture of my buyer.

My product: [PRODUCT NAME AND ONE-SENTENCE DESCRIPTION]
Who buys it: [TARGET BUYER, e.g. "freelance designers who want to raise their rates"]

Give me:
1. The 4-5 specific frustrations this person has BEFORE they find my product. Be specific, not generic. "I waste 3 hours every client call explaining my pricing" is specific. "They struggle with pricing" is not.
2. The 3 things they've probably already tried that haven't worked
3. What they're secretly afraid to admit is the real problem
4. The result they want in plain language (not the product features they'd buy, but the life outcome they're after)

Write this as a clear bulleted profile, not a paragraph. I'll use this to write my opt-in page, emails, and sales page.

How to use it:

1. Fill in your product and buyer description. Be specific, even if it feels over-narrow.

2. Read the output and flag any frustrations that feel off. Edit them or ask AI to revise.

3. Save this profile. You’ll paste it into the next 4 prompts.

Example input: My product: “The Rate Raise Toolkit, a Notion template system for freelance designers to document and present their value so they can charge premium prices.” Who buys it: freelance graphic designers who’ve been charging the same rates for 2+ years and feel stuck

What you’ll get: A buyer profile with specific language you can pull directly into your copy. If the frustrations sound generic, push back and ask for more specificity.

Advanced note: The “secret fear” section is the most useful output here. Buyers rarely say “I’m afraid I’m not worth more money” out loud, but they feel it. Copy that addresses that fear converts better than copy that just lists features.

Prompt 2: Opt-in page copy

What it does: Writes a complete opt-in page including headline, subheadline, bullet points and a CTA, using the pain profile from Prompt 1.

When to use it: After you’ve confirmed the buyer profile from Prompt 1 looks accurate.

The prompt:

Using the buyer profile below, write opt-in page copy for a free lead magnet that gets people into my funnel.

Buyer profile: [PASTE OUTPUT FROM PROMPT 1]

Lead magnet: [LEAD MAGNET NAME AND FORMAT, e.g. "a free 5-page PDF called 'The Rate Audit' that helps designers calculate exactly what they should be charging"]

Write:
- A headline (under 12 words) that names the specific outcome
- A subheadline (1-2 sentences) that adds context and addresses the main fear
- 4-5 bullet points that describe what they'll get (use "so you can" after each benefit to tie it to an outcome, not just a feature)
- A CTA button label (3-6 words, not "Submit" or "Download Now")

Tone: direct and slightly skeptical, like someone who's been burned by useless free resources before but this one is different

How to use it:

1. Paste the full buyer profile from Prompt 1.

2. Describe your lead magnet in one sentence.

3. Take the headline output and write 3 variations. Pick the one that makes you slightly uncomfortable because it’s too direct.

Example input: Lead magnet: a free checklist called “The 5 Questions Every Design Client Should Answer Before Getting a Quote” -- positions designers as experts upfront

What you’ll get: A complete opt-in page draft. The bullets usually need tightening but the structure is solid.

Advanced note: The CTA label matters more than most people think. “Get the checklist” outperforms “Download now” because it’s specific. Ask AI to write 6 CTA options and pick your favorite.

Prompt 3: Welcome email sequence

What it does: Writes a 3-email welcome sequence that warms up new subscribers before any sales pitch appears.

When to use it: After your opt-in page copy is done. These emails go out automatically when someone signs up.

The prompt:

Write a 3-email welcome sequence for new subscribers who just downloaded my lead magnet.

Product I'm eventually selling: [PRODUCT NAME AND PRICE]
Lead magnet they downloaded: [LEAD MAGNET NAME]
Buyer profile: [PASTE OUTPUT FROM PROMPT 1]

Email 1 (sent immediately): Deliver the lead magnet, set expectations for what's coming, make one observation about why most people in this situation stay stuck. No pitch. End with a question they can reply to.

Email 2 (sent day 2): Share a specific, short story or example about someone who had this problem and what changed for them. Not a testimonial. A real narrative with a before and after. End by teasing that the next email goes deeper.

Email 3 (sent day 4): Introduce the paid product. Don't hard sell. Explain what it is, who it's for, and link to the sales page. One paragraph max on the product itself.

Tone across all 3: like a knowledgeable peer who's been where they are, not a marketer who wants their money
Subject line for each email: specific and curiosity-driven, not clickbait

How to use it:

1. Fill in product, lead magnet and buyer profile.

2. For Email 2, add a real story from your own experience or a client’s. The AI version will be a placeholder.

3. Load these into your email platform as an automated sequence before you launch.

Example input: Product: Rate Raise Toolkit, $97 Lead magnet: The 5 Questions checklist

What you’ll get: Three ready-to-edit emails with subject lines. Email 2 will need the most work because it requires real specifics you’ll have to add.

Advanced note: Email 1’s reply question isn’t just for engagement. Real replies from subscribers tell you exactly what language to use in your sales page copy. Read them.

Three prompts in, you’ve got the easy half done.

The buyer profile, opt-in page and welcome sequence are where most guides stop. They’re also the part that doesn’t require you to ask anyone for money.

The sales page is different. It has to make an argument, handle doubt and get someone to type in their card details. That’s three separate jobs and most sales pages fail at all three.

The next 6 prompts break each one down:

1. a full page structure with headlines and offer stack,

2. an objection section built around the specific fears your buyer has,

3. checkout copy that doesn’t feel like a trap,

4. and a post-purchase confirmation that makes them feel good about the decision they just made.

5. The swipe file has 30 CTAs and urgency lines ready to use.

That’s the half that pays.

Read more

Those are different problems. And finding the second kind takes more than a survey or a guess.

AI is genuinely good at this, if you know how to ask. The prompts below go past surface-level frustrations into the specific, embarrassing, expensive problems your audience is sitting with. Work through them in order. By the end, you’ll have raw material for copy that feels like you read your customer’s journal.

Start with what your audience is already saying

Prompt 1: The complaint mining prompt

What it does: Pulls real language from the kinds of public complaints your audience posts online, organized by urgency and emotion.

When to use it: Before you write a single word of copy, to get the actual vocabulary your audience uses.

The prompt:

Act as a customer research analyst. My target audience is [DESCRIBE YOUR AUDIENCE - e.g., "solo consultants who sell $5k-$15k coaching packages"]. They are trying to [MAIN GOAL - e.g., "consistently fill their client pipeline"].

Imagine you've read 200 Reddit threads, forum posts and Facebook group discussions where this audience vents about their frustrations.

Give me:
1. The 5 most common complaints, written in their exact words (not cleaned up)
2. The 3 complaints they seem most ashamed of (the ones they lower their voice to say)
3. The 2 complaints they've basically given up on fixing

For each one, tell me: what they blame (themselves, a tool, the market, timing)?

How to use it:

1. Fill in your audience and their main goal as specifically as you can

2. Run it and read the shame-based complaints first. Those are almost always the ones that convert

3. Highlight any phrase that sounds like something you’d actually say out loud

Example input: Audience: “e-commerce store owners doing $10k-$50k/month.” Main goal: “get profitable without burning out on ads.”

What you’ll get: A list of complaints sorted by emotional charge, with insight into who (or what) your audience blames for their situation.

One note: The shame-based complaints are where the best copy lives. Most people avoid writing to those because it feels uncomfortable. That discomfort is a signal you’re onto something.

Prompt 2: The gap between “said” and “meant” prompt

What it does: Translates polite, sanitized customer language into what they’re actually feeling.

When to use it: After you’ve collected survey data, testimonials or customer interviews that sound generic.

The prompt:

I'm going to give you some feedback I've collected from my customers. Your job is to translate each piece from "polite customer speak" into the raw, honest version of what they probably meant.

For each one:
- Write the sanitized version (what they said)
- Write the honest version (what they likely meant, including the frustration they held back)
- Identify the specific fear or loss underneath the complaint

My customer feedback:
[PASTE 5-10 PIECES OF FEEDBACK, TESTIMONIALS OR SURVEY RESPONSES]

How to use it:

1. Paste in feedback you’ve actually collected, even if it seems positive

2. Pay attention to the “specific fear or loss” column, that’s your copy angle

3. If the honest version surprises you, you’ve been writing to the wrong problem

Example input: Feedback: “I just wish the process was a bit more straightforward.” / “It took longer than I expected to see results.”

What you’ll get: A side-by-side breakdown of what customers said vs what they were actually frustrated by, with the underlying fear named directly.

One note: Positive feedback often hides complaints. “It took longer than expected” almost always means “I was embarrassed to admit it wasn’t working.”

Prompt 3: The before-state excavation prompt

What it does: Maps the emotional and practical state your customer is in right before they go looking for a solution like yours.

When to use it: When your copy talks about features or outcomes but doesn’t capture the desperation (or exhaustion) that gets people to buy.

The prompt:

My product/service is [DESCRIBE WHAT YOU SELL].
My customer is [DESCRIBE WHO BUYS IT].

Describe in detail what the 24 hours before they purchase looks like. I want:

1. What they're physically doing (the specific task that's frustrating them)
2. What they're telling themselves (the internal dialogue, including the self-criticism)
3. What they've already tried (and why it didn't work)
4. The moment they decide to search for a solution - what triggers it
5. What they're afraid will happen if they don't fix this soon

Write this as a narrative, not a list.

How to use it:

1. Read the output and mark any sentence that describes your customer specifically (not just anyone with this type of problem)

2. Lift those specific phrases directly into your copy

3. The trigger moment in #4 is often your best ad hook

Example input: Product: “A project management template for freelance designers.” Customer: “Freelancers who are juggling 4-6 clients and missing deadlines.”

What you’ll get: A detailed narrative of your customer’s worst day, written in a way that’s directly usable in copy.

One note: If the narrative feels generic, add more specifics about your customer. The more constrained the prompt, the more useful the output.

You just got 3 prompts that go past surface complaints into the actual emotional state driving your customer’s decisions.

But knowing the problem is only half the work. The next 5 prompts handle turning that raw intelligence into copy angles:

• Finding the exact words that trigger recognition (”that’s me”)

• Writing the before/after contrast without sounding like an infomercial

• Surfacing objections before your customer raises them

• Plus: a ready-to-use customer voice capture template

Upgrade to get the complete system.

Turn insight into copy that sticks

Prompt 4: The “that’s exactly me” phrase finder

What it does: Generates hyper-specific phrases your audience uses to describe themselves and their situation, the kind that make readers think you’re in their head.

When to use it: When writing headlines, email subject lines or the opening line of a sales page.

The prompt:

Read more

That’s fine. But there’s a different use case that barely gets talked about, and it’s arguably more valuable for anyone trying to build something or figure out where they’re headed. Using AI as a thinking partner. Not to produce output, but to think better.

I want to be honest about both sides of this, because the way it gets discussed online is usually either breathless enthusiasm or flat dismissal. The truth is messier. AI is genuinely useful for certain kinds of self-reflection and genuinely useless for others, and the difference matters if you’re going to spend time on it.

What “thinking partner” actually means

A thinking partner isn’t someone who agrees with you. A good one pushes back, asks questions you haven’t asked yourself, and helps you see the assumptions baked into how you’ve framed a problem.

Most people don’t have one. Your friends are too close to your situation. Your colleagues have their own agenda. Coaches are expensive. Therapists are focused on something different, though there’s overlap.

AI fills an odd gap here. It has no stake in your decisions. It won’t feel awkward if you say something embarrassing. It doesn’t get tired of the same problem coming up for the third week in a row. And if you ask it the right questions, it will tell you things that are genuinely uncomfortable to hear.

That last part is conditional on how you prompt it, which is what the rest of this is about.

What you’ll get

The first 3 prompts are for the hard stuff: auditing your assumptions, naming what you’re actually afraid of, and getting perspective from outside your current mental model.

The next 5 prompts go deeper:

• Mapping the gap between who you are and who you’re trying to become

• Using AI to stress-test a decision before you commit to it

• Finding the pattern in problems that keep coming back

• Getting honest feedback on your own blind spots

• Plus: a repeatable weekly reflection template

Prompt 1: The assumption audit

What it does: Surfaces the beliefs you’re treating as facts, specifically in a decision you’re currently stuck on.

When to use it: When you’ve been going in circles on something and can’t figure out why you’re not moving forward.

Read more