Most SaaS founders use AI like a novelty.
The smart ones turn it into leverage.

Here’s a list of practical ways to use AI across your startup — each with a prompt you can test customise.

Validate and Plan

1. Validate your idea before building
AI can simulate early customer interviews so you test if your idea solves a real pain.
Try this prompt:

Act as five potential customers for [describe your idea].  
Give me blunt feedback on what feels valuable, unclear, or unnecessary.  
Summarize the top 3 objections you have.

Deep dive: How to Use AI to Find and Validate Startup Ideas

2. Find your positioning early
Use AI to explore different market positioning angles before you commit to one.
Try this prompt:

Show me five positioning statements for a B2B SaaS helping [target role] achieve [goal] —  
one aspirational, one technical, one ROI-driven, one product-led, and one emotion-based.

Deep dive: How to Use AI to Write Your SaaS Landing Page in 2 min

3. Discover your ICP’s hidden problems
Feed AI review data or Reddit threads to surface recurring frustrations in your niche.
Try this prompt:

Summarize the top recurring customer pains from these [G2/Reddit] reviews.  
Group them by theme and frequency.

Deep dive: How to Use AI to Find the Right People for Startup Feedback

4. Estimate market potential fast
AI can provide rough market sizing without hours of research.
Try this prompt:

Estimate the total addressable market for [product category] targeting [user type] in [region].  
Include assumptions for company size and spend range.

5. Turn scattered ideas into a roadmap
Drop all your product thoughts into AI and ask it to cluster them into epics or milestones.
Try this prompt:

Organize these product ideas into logical themes or milestones for an MVP roadmap.  
Highlight dependencies or overlaps.

Design and Build

6. Prioritize your MVP features fast
AI helps turn subjective debates into data-driven calls using scoring frameworks like RICE.
Try this prompt:

Use the RICE framework to score and rank these features: [list].  
Assume limited resources and prioritize quick validation.

Deep dive: How to Use AI for MVP Feature Prioritization

7. Write your landing page copy in minutes
Turn your notes into structured messaging that converts.
Try this prompt:

Write a landing page outline for a SaaS that helps [user type] solve [problem].  
Include a hero headline, 3 benefits, and 1 CTA.

Read next: How to Use AI to Write Your SaaS Landing Page in 2 min

8. Create wireframes from text
Describe the screens you need — tools like Lovable or v0.dev can generate layouts.
Try this prompt:

Generate wireframes for a SaaS dashboard with these key screens: [list].  
Focus on clean UX, minimal steps to first value.

9. Design your onboarding flow
AI can map onboarding steps from your user journey to ensure activation.
Try this prompt:

Design an onboarding sequence for [your product or feature] that helps new users reach their first success in under [X minutes].  
List each step and the user’s motivation at that point.

10. Prototype user flows
Tools like Lovable or v0.dev can generate screen ideas from prompts.
Try this prompt:

Create 5 UI layout options for a [feature name] screen in a [your product]. Make them minimal, data-focused, and clear at a glance.

11. Write microcopy for UI elements
Attache a screenshot to your prompt and AI can adapt tone and clarity to match your product’s context.
Try this prompt:

Review this screenshot of [your app screen or page].  
Suggest clearer and more human microcopy for all visible buttons, tooltips, and empty states.  
Keep tone [choose tone: friendly / confident / professional].

Market and Grow

12. Create unconventional marketing ideas
Use the “Just Evil Enough” method to break patterns in your niche.
Try this prompt:

Suggest 5 unconventional but ethical marketing ideas for a SaaS that helps [target audience] with [main problem].  
Each idea should challenge a common industry norm while staying aligned with [your brand values or tone].

Deep dive: How to Use AI for Disruptive Startup Marketing

13. Draft social content fast
Summarize updates or insights into post variations.
Try this prompt:

Turn this product update into 3 LinkedIn posts —  
one storytelling angle, one data insight, and one quick tip.  
Here’s the update: [paste your product update text].  
Keep each post under 150 words and relevant to [your target audience].

14. Analyze your competitors’ messaging
Upload screenshots of your competitors’ landing pages and let AI show where you can stand out.
Try this prompt:

Review these 3 screenshots of competitor homepages or hero sections: [attach images].  
Summarize each competitor’s target user, main promise, and tone.  
Highlight what positioning gaps or differentiation opportunities you see.

Deep dive: How to Use AI for Startup Competitor Analysis

15. Build a repeatable content engine
AI can organize your posts into long-term themes and angles.
Try this prompt:

Cluster these 10 post ideas into 3 recurring content pillars.  
Here are my post ideas: [paste your list of ideas].  
Expand each pillar with 3–5 additional content ideas that fit the same theme.  
Then suggest a posting cadence and best formats for each (e.g. tweet thread, short video, case study).  
Focus on reaching [target audience].

16. Generate personalized outreach messages
Turn company data into quick, specific outreach notes.
Try this prompt:

Write a short LinkedIn message to [prospect role] at [company].  
Reference their product and tie it to our [benefit]. Keep it under 100 words.

17. Create PR or launch plans
AI can build tiered outreach and timing plans for your launch.
Try this prompt:

Create a 10-day launch plan for my SaaS tool [product name] in the [category or niche] space.  
Our goal is to [main objective — e.g., get 500 signups or attract investor attention].  
Target audience: [describe your main audience].  
Include 3 PR angles, 3 social media pushes, and 3 community tactics.  
Add a short timeline with what to do each day before and after launch.

18. Run a quick growth audit
Use AI to spot where your SaaS is leaking growth — based on your own data and context.
Try this prompt:

Act as a SaaS growth strategist.  
Here’s my context:  
- Product: [brief description of what your SaaS does]  
- Target audience: [who you serve]  
- Current metrics: [conversion %, retention %, MRR, or other KPIs you track]  
- Biggest challenges: [describe what’s not working, e.g., low trial-to-paid, churn, etc.]  

Ask me 3–5 follow-up questions to clarify my situation.  
Then summarize the top 3 growth opportunities and 3 tactical actions I can take this week to fix the weakest part of my funnel.

Deep dive: How to Use AI for a SaaS Growth Audit

Learn and Optimize

19. Run a quick CRO audit
Upload your landing page screenshot and ask for clarity feedback.
Try this prompt:

Review this landing page screenshot: [attach image].  
Identify any issues that could hurt conversion — unclear value props, weak CTAs, poor visual hierarchy, or trust gaps.  
Suggest 3 improvements to increase conversions and 3 quick A/B test ideas.  
Summarize your analysis in a short CRO checklist.

20. Summarize user feedback
Upload your exported user feedback file (CSV, spreadsheet, or survey export) and let AI surface the biggest themes.
Try this prompt:

Analyze this user feedback dataset: [attach your CSV or spreadsheet].  
Summarize the main themes and categorize comments by topic or sentiment.  
Highlight the top recurring issues, quick wins, and feature requests to prioritize.  
End with a short summary table of insights by frequency and impact.

21. Analyze churn reasons
Upload your churn survey or cancellation feedback export (CSV or spreadsheet) and let AI find the root causes behind user drop-off.
Try this prompt:

Analyze this churn dataset: [attach your CSV or spreadsheet].  
Categorize responses by churn reason (e.g., missing features, pricing, support, bugs).  
Quantify how often each reason appears and identify patterns by customer type or plan.  
Suggest 3 practical ways to reduce the top cause and improve retention.

22. Identify upsell opportunities
Upload your product usage data or export from your analytics tool and let AI find upgrade signals hidden in user behavior.
Try this prompt:

Analyze this feature usage dataset: [attach your CSV or spreadsheet].  
Identify which user actions or patterns correlate most with plan upgrades or higher spend.  
Group these behaviors by user segment (e.g., active vs. churn-risk).  
Recommend 3 product nudges or in-app messages to drive upgrades.  
Summarize findings in a short table with “Signal”, “User Type”, and “Recommended Nudge”.

Operate and Communicate

23. Prepare investor updates (and Q&A prep)
Use AI to summarize your latest metrics into a confident narrative — and rehearse for the questions investors will ask next.
Try this prompt:

Here are my latest investor update notes: [paste metrics, highlights, and challenges].  
Summarize them into a 150-word investor email.  
Then generate 5 tough follow-up questions a VC might ask about these results, with short sample answers.

Deep dive: How to Use AI to Prep for Investor Q&A

24. Automate customer support docs
Upload your existing documentation file (Markdown, Notion export, or PDF) and let AI turn it into a simple, user-friendly help article.
Try this prompt:

Rewrite this technical document: [attach your doc or paste content].  
Audience: [describe your typical user — e.g., “non-technical small-business owner”].  
Convert it into a structured help article with plain language and short steps.  
Add a short FAQ section at the end and include relevant examples for clarity.

25. Create job descriptions and interview questions
Generate clear hiring briefs and interview questions that fit early-stage SaaS realities.
Try this prompt:

Write a job description and 5 interview questions for a [role, e.g., “Growth PM” or “Founding Engineer”] at a SaaS company called [company name].  
Stage: [pre-seed / seed / Series A].  
Company size: [number of people].  
Key goal for this role: [main objective — e.g., “increase activation,” “build first analytics pipeline”].  
Emphasize [specific traits — e.g., adaptability, cross-functional collaboration, ownership mindset].  
Keep the tone authentic and avoid corporate HR language.

Takeaway

You don’t need complex AI workflows to get real results.
These prompts are meant to get you moving, not overthinking.
Pick one and try it today.

👋 Let’s me know in the comments what’s the most useful for you so I can do a deep dive on it with multi-prompt workflow and all the details.

Raising your Series A isn’t just about the deck.

It’s about surviving the Q&A that follows.

Raising a Series A has never felt harder. Recent data from Crunchbase shows that for the 2021 seed cohort, only about 36 % of startups ever made it past seed into a Series A or exit.

In more recent article, Carta’s data suggest that just 13 % of companies that raised seed in early 2022 progressed to a Series A.

In short: even among startups that hit seed, most don’t survive the jump, and the Q&A at that stage is often where things fall apart.

So what can you do?

Imagine walking into the room having already defended your numbers, your market story, and your AI angle, against the toughest version of the questions you’ll face. That’s the edge you can create for yourself using AI.

Why Practicing With AI Beats Practicing Alone

Mentors and co-founders are helpful, but they know your story too well. They’ll pull punches. Investors won’t.

What you need is a skeptic who doesn’t care about your feelings. AI, when prompted correctly, can act as that skeptical VC, asking you the hardest questions one by one. Rating your answers, and pointing out where you need to tighten up.

Think of it as a fundraising fire-drill.

Here is the Prompt

Copy-paste this into ChatGPT or Claude and run it.

Pro tip: don’t just type your answers. Use dictation. Speaking out loud forces you to be clear, concise, just like in the real thing.

You are a venture capital investor preparing to evaluate my Series A fundraising pitch.Your role is to simulate a skeptical investor Q&A session to test how well I can defend my business.

Step 1: Collect Context
Before you begin questioning, ask me 3–5 clarifying questions to understand my startup. These should cover:

• What I’m building and for whom
• Current traction stage (users, revenue, etc.)
• Target market and competitive context
• Team and fundraising goal

Step 2: Simulated Q&A 
Once you have context, begin acting like a Series A VC.
Ask me questions one by one, waiting for my answer before moving to the next.

Cover the following investor categories (in random order so I don’t just “prepare” for a sequence):

• Market, Problem & Timing
• Product & Differentiation
• Business Model & Unit Economics
• Traction & Growth Metrics
• Go-to-Market Strategy
• Competition & Defensibility
• AI Strategy & Technology
• Team & Execution Capability
• Risks & Challenges
• Vision, Scale & Path to $100M+
• Fundraising Ask & Use of Capital

Step 3: Evaluation of Each Answer
After each of my responses:
Rate the answer on a 3-level scale: Meh / OK / Great
Provide a one-sentence note on how to improve that specific answer.

Step 4: Wrap-Up Debrief
After 8–10 questions, stop and provide a final summary:
My strongest answers (where investors would be impressed)
My weakest answers (where investors would likely push back)
2–3 concrete suggestions for how to tighten my pitch before a real investor meeting.

What This Looks Like in Practice

I have run this on one of my startup ideas and here is the final debrief.

Took me like 10 - 15 minutes.
Cough 2 weak spots and really got me thinking about the go-to-market plan.
And for the $100M well I happy to lower this number and adjust it to my modest vision.
And for the rest it gave my some confidence that I know my shit when it comes to growth, strategy and AI angle.

Why This Matters

Instead of over-preparing your slides and under-preparing your Q&A, you’ll be doing the opposite:

• Stress-testing your story against the hardest questions

• Practicing how you sound, not just what you say

• Spotting weak points before investors expose them

Run this prompt today. Dictate your answers. Treat it like a rehearsal, because the real thing could cost your fundraising.

Growth doesn’t stall because you lack ideas.

It stalls because you’re too close to the product to see what’s really broken.
Or because you’re fixing things out of order.

That’s where a growth audit helps.

And with the right prompt templates, you don’t need to hire a team or wait for a quarterly review.
You can uncover your biggest growth blockers in 30 minutes or less using AI.

Why Growth Feels Like a Black Box

You’re getting users, but retention’s flat.
You’ve built features, but expansion is weak.
You’ve invested in onboarding, but activation still lags.

These aren’t funnel issues. They’re insight gaps.

If you keep guessing, you’ll keep spinning.

Let’s break the loop with three targeted growth audit prompts.

The 3 Growth Prompts You’ll Want to Run

Each prompt gives you a different lens to examine your product.

• Prompt 1: Full-funnel audit across PLG stages

• Prompt 2: Growth loop mechanics and bottlenecks

• Prompt 3: PLG readiness check to test if self-serve even fits

Run them in sequence, or pick the one that fits your current challenge.

Prompt 1: Core Product-Led Growth Audit

Use this when:

• You want to pinpoint where your growth funnel breaks

• You need a structured look at acquisition, activation, retention, and monetization

• You're building or improving your self-serve experience

This prompt helps you:

• Map your full PLG journey

• Uncover gaps in activation and engagement

• Check whether you're ready for expansion before scaling acquisition

Paste it into ChatGPT or Claude and let it interview you like a growth consultant.

You are a growth strategist auditing a B2B software product. Your job is to uncover bottlenecks and opportunities across acquisition, activation, engagement, monetization and expansion using product-led growth principles. Work only with the information the founder or product manager supplies. Do not guess or invent facts. If the user omits something that affects the audit, ask for it clearly and concisely.

1. Start by understanding the product and customer:
   • Ask for a plain-language description of the product, the core job it does, and the main buyer personas.
   • Clarify the business model (free trial, freemium, usage-based) and the current pricing tiers.
   • Request current North Star metrics and any retention or engagement metrics they track (e.g., weekly active users, net revenue retention).

2. Explore acquisition:
   • Ask how new users currently discover and sign up for the product.
   • Get sign-up numbers and growth channels (organic search, referrals, paid ads, sales outbound).
   • Check whether the product qualifies users itself (product-qualified leads/accounts) or if marketing qualifies them.

3. Evaluate activation:
   • Ask the user to outline the onboarding flow from sign-up to first value.
   • Identify friction points (long set-up, missing self-serve features) and time-to-value.
   • Check if activation requires human help or if it’s self-serve.

4. Examine engagement and retention:
   • Request data on how often ideal customers should use the product.
   • Ask for retention curves and common reasons users churn.
   • Probe whether the product encourages habitual workflows around its core value.

5. Assess monetization and expansion:
   • Ask how users convert from free to paid tiers and what percentage upgrade.
   • Find out whether there’s a path for individuals to expand usage inside their organization (team plans, enterprise plans).
   • Check if enterprise monetization is self-serve or sales-assisted.

6. Identify growth loops:
   • Ask how the product generates word-of-mouth or network effects.
   • Request any existing loops (e.g., user shares content → new user signs up → creates content → more sharing) and the metrics that support them.
   • If loops are missing, ask for current experiments or ideas to create them.

7. Summarize findings and recommend specific next steps. Prioritize fixes that unblock activation or retention before chasing new acquisition. If the product lacks a strong self-serve path or quick time-to-value, clearly state that PLG may not make sense yet. Highlight opportunities to build or strengthen loops, optimize onboarding, or introduce product-qualified lead scoring.

Prompt 2: Growth Loop Audit

Use this when:

• Your product depends on collaboration, sharing, or data compounding

• You suspect your growth loops aren’t firing

• You want to build a repeatable, compounding growth engine

This prompt helps you:

• Map each step of your loop and measure drop-offs

• Spot weak or missing incentives that break the cycle

• Align teams around outcomes, not functions

It’s especially useful for B2B products trying to turn usage into growth.

You are an AI growth advisor performing a loop-centric audit of a B2B SaaS product. Do not rely on generic funnels. Use only the founder’s input and challenge assumptions where needed.

1. Ask the user to describe existing growth loops: a loop is a closed system where user actions create outputs (new users, content, data) that feed back into future growth. Examples include content loops, collaboration loops, or data network effects. If none exist, request ideas or experiments in progress.

2. Gather core product details: mission, target users, main use cases, and pricing. Verify whether the product solves a frequent, straightforward problem and delivers value quickly; otherwise, product-led growth may not fit.

3. For each loop the user mentions, map the steps (e.g., user signs up → creates value → invites teammates → team expands) and ask for metrics at each step (conversion rates, referral rates, time-to-value). Identify where the loop breaks down.

4. Check cross-functional alignment: ask how product, engineering, marketing, and sales teams currently work together. Are they organized around the loop or siloed by funnel stage? Loops require cross-functional teams working toward the same output.

5. Probe investment decisions: see if the company prioritizes initiatives that create compounding effects (steady week-over-week growth) rather than short-term spikes. If not, call it out and ask why.

6. Evaluate monetization within loops: determine whether the product has self-serve upgrade paths embedded in the loop or requires a separate sales process. Identify friction points that might prevent expansion.

7. Deliver a concise audit that highlights which loops are working, which need tuning, and where new loops could be built. Suggest tangible experiments, such as adding in-product referral prompts or collaborative features that naturally spread the product inside customer organizations.

Prompt 3: PLG Readiness Check

Use this when:

• You’re not sure if PLG even fits your product

• You’ve tried going self-serve, but it didn’t stick

• You’re exploring a hybrid sales-led + product-led motion

This prompt challenges the PLG hype. It helps you:

• Identify friction that makes self-serve adoption unrealistic

• Compare user behavior with PLG benchmarks

• Avoid investing in a go-to-market model that doesn’t fit your product

You are tasked with auditing a B2B software product’s readiness for product-led growth. Challenge the assumption that PLG is always the right move. Ask only for facts from the founder or PM.

1. Clarify the product’s use case, pricing, and buyer (individual vs. enterprise). Determine whether a single user can derive value without extensive setup or integration. If time-to-value is long or the product is priced high, state early that PLG may introduce too much friction.

2. Ask for evidence that the product can attract and convert users without human help: sign-up flow, onboarding, and upgrade numbers. If upgrades depend heavily on sales calls or success managers, note that as a barrier to PLG.

3. Check whether users routinely invite colleagues or create content that brings in others. If the growth engine depends on paid marketing or outbound sales, highlight the cost trade-offs and question the scalability.

4. Investigate retention: request retention curves and reasons for churn. If the product serves infrequent or complex workflows, warn that building a self-serve engine may not be worth the investment.

5. Summarize whether PLG is viable. If not, suggest blending product-led elements with sales-led growth, such as using product usage to qualify leads for a sales team or offering a trial to accelerate sales cycles.

Pick One and Run It

If you're stuck on growth, don't guess.
Run the right prompt. See what’s broken. Act on what matters.

• Run Prompt 1 if you want a full funnel audit

• Run Prompt 2 if you rely on usage-based loops

• Run Prompt 3 if you’re not sure PLG fits your model

Each one is a mini growth strategist, ready to challenge your assumptions and focus your efforts.

Everyone's watching their competitors.
But almost no one’s doing it well.

Founders tend to fall into two camps: they either ignore the competition entirely, or they obsess over surface-level stuff—like a new pricing page or a flashy redesign—without extracting any real strategic advantage.

But what if you could turn AI into a full-time competitive analyst?

One that doesn’t sleep, doesn’t get tired, and connects the dots across data sources you’d never have time to read yourself?

Here’s how.

Why Competitive Intelligence Still Sucks (And Why It Matters Now)

The problem isn’t a lack of data.

There’s more than ever—pricing pages, feature changelogs, customer reviews, hiring trends, Reddit threads, marketing campaigns, funding announcements. It’s all out there.

The problem is synthesis.

Most startups don’t have the resources (or time) to turn scattered competitive signals into useful insights. So they either overreact to noise or miss the early signs of disruption entirely.

Meanwhile, founders who know how to systematize this process are able to:

• Spot product gaps before they become threats

• Reverse-engineer what’s working in marketing

• Predict upcoming moves by reading between the lines

• Steal smart ideas and make them better

And that’s where AI can give you an unfair advantage.

The Ideal Setup: One-Person CIA for Your Market

Imagine having a competitive intelligence workflow that:

• Scrapes your top 3 competitors’ pricing pages weekly using Browse AI

• Clusters customer reviews with Claude to find recurring complaints

• Summarizes competitor blogs and SEO trends via Perplexity

• Highlights market gaps using a SWOT prompt in ChatGPT

Too much to do manually.

But with the right tools and prompts, it’s a 15-minute founder ritual.

Here’s how to set it up.

The Framework

Let’s break it down into 4 key components:

1. Track Pricing Moves

Tools like Browse AI or Visualping can monitor pricing pages and send alerts when anything changes. For example, you might detect that a competitor silently introduced a new “Startup Plan” aimed at undercutting your cheapest tier.

Example prompt:
“Compare the pricing structure of [Competitor A] and [Competitor B]. What tiers do they offer, and what segments are they targeting? Suggest any gaps we could exploit.”

2. Monitor Product Updates

Set up a changelog RSS feed in Feedly, or use Kompyte to get automatic digests of what changed on a competitor’s site. Claude can summarize recent blog posts, UI changes, or new integrations for quick review.

Example prompt:
“What’s changed in [Competitor’s] product over the last 3 months? Summarize any new features or roadmap shifts and what they signal.”

3. Analyze Their Marketing Strategy

Use Semrush to get SEO keyword gaps. Use Perplexity AI to quickly check what channels a competitor is using to grow. Ask ChatGPT to compare their content themes or ad positioning.

Example prompt:
“Analyze the top-performing content and ads from [Competitor]. What themes are they emphasizing and who are they targeting?”

4. Mine Reviews for Weak Spots

Use a Browse AI prebuilt scraper for G2 or Capterra. Then ask Claude or ChatGPT to cluster the reviews by pain points, praise, and missing features.

Example prompt:
“What are the most common complaints and praises in [Competitor’s] reviews? What recurring customer needs are going unmet?”

The Prompt Template

Competitor Deep Dive + Strategic Gaps Generator

Here is the prompt:

I want to analyze a competitor to identify strategic insights and opportunities for my startup.

Here’s the context:

ABOUT MY STARTUP
- My product is [brief description]
- We serve [target customer] in [market or niche]
- Our main value proposition is [describe in 1 sentence]

THE COMPETITOR
- Competitor name: [company name]
- Website: [URL]
- Optional: Link to public reviews (G2, Reddit, etc.)

Please help me analyze the competitor in the following areas:

1. Positioning & Messaging
- What do they claim is their main value?
- What customer pain points are they emphasizing?
- Who are they targeting?

2. Product Strategy
- What key features do they highlight?
- What differentiators do they focus on?
- Any recent product updates?

3. Pricing & Business Model
- How is their pricing structured?
- Are there any hidden tactics?
- How does it compare to our pricing?

4. Growth & Marketing Tactics
- What channels are they using?
- What SEO/ads/content strategies stand out?
- Any recent campaigns or partnerships?

5. Customer Sentiment
- What are users loving or hating in reviews?
- Any recurring feature requests or complaints?

6. Strategic Gaps
- What are they NOT doing?
- Where do they seem vulnerable?

7. Opportunities for Us
- What positioning angles would clearly differentiate us?
- What unmet needs could we address?

Please format the output using clear section headers and bullet points.

When to Use It

• Entering a crowded space

• Planning a product launch or pivot

• Developing pricing or go-to-market strategy

• Prepping a pitch deck or investor Q&A

Limitations

You won’t get internal metrics or future plans.

But this system gives you a clearer picture than 99% of founders flying blind.

It’s not about perfect intel. It’s about consistently better intel.

Take Action

Pick your top 1–2 competitors. Paste the prompt into ChatGPT Deep Research or Perplexity.

If you want to go deeper, set up tools like Browse AI, Feedly, or Semrush to collect intel on autopilot.

Run this monthly and you’ll be 3 steps ahead of everyone still “guessing.”

Let me know what you uncover.

PS: If you learn something new leave me a ♡.

A few months ago, a founder friend of mine—let’s call him Jake—was fired up about his new SaaS idea.

He wasn’t technical, but AI coding tools like Cursor AI had him convinced he could build a simple MVP himself.

So, he fired up Cursor AI and typed something like:

"Build me a SaaS app for X."

A minute later, he had a bunch of code.

He copied, pasted, ran it... and nothing worked.

Debugging was a nightmare.

The AI kept making weird mistakes.

Hours turned into days, and Jake started thinking, Maybe AI coding tools just aren’t that good?

Here’s the thing: AI coding isn’t the problem. The problem was his prompt.

A vague, high-level prompt like that won’t get you a working MVP. But a well-crafted first prompt? That’s where the magic happens.

Let’s break down how to prompt these tools like a pro so you can actually build your MVP instead of wrestling with broken code.

The Framework for Effective AI Coding Prompts

Think of AI coding tools like an incredibly fast but slightly clueless junior developer. They’ll do exactly what you ask—sometimes too literally. That’s why your prompt needs structure.

Here’s what your first prompt should include:

1. Project Context – What are you building, and who’s it for?

2. Key Features – The core functionalities you need.

3. Tech Stack (if known) – Preferred frameworks, languages, tools.

4. Constraints – MVP priorities, platform choices, what to avoid.

5. Desired Output – What should the AI actually generate first?

This helps the AI make fewer assumptions, so you get useful output instead of vague, half-baked code.

The Expert-Level AI Coding Prompt

Copy, tweak, and paste this into your AI coding tool:

I am building an MVP for a [describe your product, e.g., "task management app for remote teams"].

### Project Context:
- The purpose of this MVP is to [explain what the product does in one sentence].
- The target audience is [describe who will use this product].

### Key Features:
- [Feature 1, e.g., "User authentication with email/password and Google login"]
- [Feature 2, e.g., "Task creation with drag-and-drop organization"]
- [Feature 3, e.g., "Real-time collaboration on tasks"]

### Tech Stack:
- Preferred technologies: [list frameworks, libraries, or tools you want to use, e.g., Next.js, Supabase, TailwindCSS]
- Backend requirements: [any necessary backend services, e.g., "Supabase for authentication and database"]

### Constraints:
- This is an MVP, so keep the architecture simple and scalable.
- Avoid unnecessary dependencies; use built-in solutions where possible.
- The UI should follow modern design patterns (TailwindCSS preferred).

### First Task:
[Example: Generate a project setup with Next.js, Supabase authentication, and a simple dashboard with a protected route. 
- Include environment variable handling.
- Follow best practices for structuring the project.
- Output the full project structure and initial code files.]

Why This Works

• Context-Rich → The AI understands your product, not just isolated features.

• Scoped & Specific → It knows what to build first instead of dumping everything at once.

• Technical Preferences → Ensures alignment with your preferred tools & constraints.

• Actionable Output → You get a structured, working setup instead of random snippets.

When to Use This Prompt

• Starting a brand-new AI-assisted project

• Pivoting an MVP and need a quick rebuild

• Automating boilerplate code setup

• Exploring different frameworks before committing

Ready to Build?

Fire up Cursor AI, Lovable, or your favorite AI coding tool and drop in this prompt.

If you’ve been stuck, this might be the shortcut you need. Let me know what you’re building—I’d love to hear how it goes!

PS: If you learn something new leave me a ♡.

In 2008, Drew Houston was pitching Dropbox to early users. He’d show a demo, and people would nod enthusiastically.

"Yeah, I’d totally use this."

But when he followed up, almost none of them signed up.

Why? Because people don’t like to be mean. They tell you what you want to hear, not what they actually think.

This is the startup founder’s curse. You ask customers if your idea is useful, and they lie to you—out of politeness, optimism, or just not wanting to think too hard.

So how do you get to the truth?

The Framework: How to Get Honest Customer Feedback

Most founders make two mistakes:

1. They ask about the future. “Would you use this?” People are bad at predicting their own behavior.

2. They ask for opinions. “What do you think?” Everyone has an opinion, but only actions matter.

Instead, you need to structure discovery interviews to uncover:
✔️ Past behavior (what they’ve already done, not what they might do)
✔️ Real problems (what they already struggle with, not hypotheticals)
✔️ Problem ranking (because not all problems are urgent enough to solve)

The Interview Structure

Use this four-part script to guide your conversations:

1. Build Rapport (5 min)

Start casually. Get them comfortable. The goal is to get them talking about their work or life, not your idea.

• “Tell me about your role and day-to-day work.”

• “What tools/processes do you use regularly?”

2. Identify Pain (10 min)

Dig into the actual problems they face. The trick is to get specific.

• “What’s the most frustrating part of doing X?”

• “Tell me about the last time this happened.” (If they can’t recall a time, it’s not a real problem.)

• “How do you solve this today?”

3. Rank the Problems (5-10 min)

This is where most founders unlock real insights.

• “Here are the problems I heard from you: [summarize]. Did I miss anything?”

• “If you had to rank these from most painful to least, what would that look like?”

• “If you could magically fix just one today, which would it be?”

(If your problem isn’t at the top, it’s not their biggest priority.)

4. Gauge Urgency (10-20 min)

Not all problems are worth solving. The best ones cause real pain and force people to hack together their own solutions.

• “What’s the impact when this problem happens?”

• “Have you tried to solve this before? What did you do?”

• “If you could magically fix it today, how much would it be worth to you?”

5. Wrap Up (5 min)

• “Who else should I talk to about this?”

• “Can I reach out again when we have something to test?”

Subscribe now

The Prompt: Get a Custom Interview Script

Use this AI prompt to generate a structured discovery interview tailored to your product and audience.

I am conducting customer discovery interviews for [your startup idea].

My target customers are [describe them].

They currently solve this problem by [describe their current method].

I want to uncover their real pain points and willingness to pay.

Generate an interview script with:
✔️ Open-ended rapport-building questions
✔️ Specific prompts to uncover past behavior
✔️ A ranking step where customers score their biggest problems
✔️ Probing questions to assess problem severity
✔️ A closing section to identify next steps

For the problem ranking step, ask:

- “Here are the problems I heard from you: [summarize]. Did I miss anything?”
- “Can you rank these from most painful to least?”
- “If you could fix just one today, which would it be?”

For urgency, include:

- “What’s the impact when this happens?”
- “How have you tried to solve it?”
- “How much is this costing you in time/money/stress?”

This prompt ensures that your interviews surface real pain, not polite feedback.

Takeaway: Run This Interview Before You Build

Drew Houston eventually realized that Dropbox’s real market wasn’t casual users who said “cool idea” and never followed through. It was developers and tech teams who were already hacking terrible solutions to sync their files—emailing themselves ZIPs, carrying USB drives, writing their own scripts.

When Dropbox launched with a waiting list, it exploded. From 5,000 signups to 75,000 overnight.

Why? Because it solved a problem people actually felt—and ranked as their biggest pain.

Talk to your customers the right way, and you’ll know if your startup is worth building.

Now go run your first interview.

PS: Was that useful? Leave me a ♡ so I know I’m on the right track.
What founder challenge should I tackle next?

Many startup ideas fail because they are built on bad feedback.
Founders talk to the wrong people, hear what they want to hear, or collect surface-level responses that don’t reflect real behavior.

Getting feedback isn’t the hard part—getting useful feedback from the right people is. If you talk to people who don’t experience the problem, their opinions will send you in the wrong direction. If you ask broad, vague questions, you’ll get polite but meaningless answers.

So how do you find people who will give you honest, insightful feedback before you invest time and money into building something?

Why Most Founders Struggle to Find the Right People

Most attempts at gathering feedback fail because of:

• Talking to the wrong audience – Friends, startup communities, or general LinkedIn polls don’t reflect real customers.

• Receiving vague, overly positive feedback – People don’t want to be rude, so they say it’s "interesting" instead of telling you it won’t work.

• Asking bad questions – If you ask, "Would you use this?" people will say yes just to be nice. But saying "yes" isn’t the same as paying for it.

• Relying on surveys instead of conversations – Mass surveys attract random opinions, while direct conversations reveal actual pain points.

Instead of asking anyone, you need a system to find people who actually experience the problem and care about solving it.

Where to Find the Right People Online

Your target users are already discussing their challenges somewhere.
You just need to find where.

1. Social Media & Professional Networks

• LinkedIn – Look for people posting about the problem or engaging with relevant content.

• Twitter/X – Search for complaints, recommendations, and discussions around your topic.

• Reddit – Find niche subreddits where your audience talks about their struggles.

2. Online Communities & Industry Forums

• Slack & Discord groups – Many industries have private communities where people discuss pain points.

• Facebook groups – Particularly useful for B2C and niche professional communities.

• Industry forums – Search for "[your industry] community" or "[problem] forum."

3. Q&A & Review Sites

• Quora – Identify people asking and answering relevant questions.

• Capterra & G2 – Read reviews of existing solutions to find common frustrations.

4. Competitor Research

• Identify people commenting on competitor content.

• Read negative reviews of competitors to find pain points that haven’t been solved.

How to Identify the Best People to Talk To

Once you find discussions, prioritize people who fit these categories:

• Actively searching for solutions – Look for posts that include:

  • "Alternative to [competitor]"

  • "Best way to [solve problem]"

  • "How do I [task]?"

• Making recommendations – People who suggest solutions often have deep knowledge.

• In relevant job roles – If B2B, prioritize professionals who deal with the problem daily (e.g., Sales tools → Heads of Sales).

• Proxies and analogues – If you can’t find direct users, look for people in similar industries with the same problem.

How to Reach Out and Get Responses

Once you find the right people, the next challenge is getting them to engage. Most outreach messages fail because they are too vague, too long, or too focused on your idea rather than their experience.

What to Avoid

• "Hey, can I pick your brain?" → Too vague, sounds like a favor.

• "Would you use this?" → Easy to say yes, but doesn’t reveal real behavior.

• Long emails explaining your idea → No one has time to read that.

What Works Instead

• Be specific about why you’re reaching out.

• Make it clear you’re not selling anything.

• Keep it short and easy to answer.

Example message:
"Hey [Name], I saw your post about [problem]. I’m working on something in this space and trying to understand [specific challenge]. Would love to hear how you currently solve this—just 10 min, no pitch. Open to a quick chat?"

AI-Powered Template to Find and Engage the Right People

Use this structured AI prompt to generate a list of potential respondents and an outreach message.

Copy and paste this prompt into one of the Deep Research AI tools (Perplexity Deep Research is free at the moment). Refine to fit your case and fill in the [blanks].

Act as a research assistant for a startup founder validating an idea.

Here are the idea details:

Industry / Problem area: [Describe your industry or the specific problem you are solving.]

Target audience: [Who experiences this problem? Be specific about job roles, industries, or company size.]

Discussion keywords: [Examples: "Alternative to [competitor]", "How to fix [problem]", "Best way to [do X]".]


Instructions for Output

Step 1: Find relevant discussions

Search LinkedIn, Twitter, Reddit, and Quora for posts from the last 30 days that include:

"Alternative to [competitor]"

"How to solve [problem]"

"Recommendation for [product/task]"

Complaints about existing solutions (e.g., "[Competitor] is too expensive" or "Why is [problem] so frustrating?").


Step 2: Identify relevant people

If B2B, look for professionals in [target industry/role].

If no direct users, find proxies in adjacent industries.

Prioritize those asking or answering questions, not just liking posts.

Step 3: Generate a personalized outreach message

Keep it short and reference their post.

Clearly state you are not selling anything.

Offer a simple, low-commitment ask (e.g., a 10-minute chat).

Example Outreach Message:
"Hey [Name], I saw your post about [problem]. I’m working on something in this space and trying to understand [specific challenge]. Would love to hear how you currently solve this—just 10 min, no pitch. Open to a quick chat?"

Signs You’re on the Right (or Wrong) Track

Finding the right people for startup feedback isn’t a straightforward process. It takes iteration, and setbacks are normal. Here’s how to know whether you’re making progress or if you need to adjust your approach.

Indicators You’re on the Right Track

• People are sharing detailed responses – They describe their frustrations, existing solutions, and workarounds instead of giving one-word answers.

• You hear consistent patterns – Different people mention the same pain points or describe the problem in similar ways, signaling a real demand.

• Some people already pay for a workaround – If users are hacking together their own solutions, it’s a strong sign they have an urgent problem.

• You get follow-up questions – When people ask, "How are you solving this?" or "When can I try it?" they’re showing genuine interest.

• They introduce you to others – When someone says, "You should talk to [person]—they have this problem too," you’re reaching the right audience.

Indicators You Need to Adjust

• People say the problem isn’t a priority – If most responses are “Yeah, that’s annoying, but I wouldn’t pay for a solution,” the problem isn’t painful enough.

• You’re only getting generic, polite feedback – If people say "Sounds interesting" or "Cool idea" but don’t engage further, they’re not the right audience.

• Nobody is already trying to solve this problem – If there are no workarounds, no complaints, and no discussions about alternatives, the problem might not be real.

• People ignore your outreach completely – If you’ve refined your message and targeted the right people but still get no responses, reconsider your approach. Are you reaching out to the right audience? Is your message too vague or too focused on your idea instead of their pain points?

• You keep getting different answers – If every conversation contradicts the last, your target audience might be too broad, and you need to niche down.

How to Adjust on the Fly

• If you’re getting low response rates, tweak your outreach message to be more specific and direct.

• If you’re getting surface-level answers, ask better follow-up questions like “How do you currently solve this?” or “What’s the hardest part about [problem]?”

• If you’re not seeing patterns, narrow your audience and focus on a more specific user group.

Talking to the right people takes time. If your first few conversations don’t go as planned, that’s part of the process. Keep adjusting and refining until you start seeing real signals.

Take Action: Find Your First 5 Conversations Today

The difference between a successful startup and a failed one? Talking to the right people early.

Use the AI prompt, find five relevant people today, and send your first outreach messages.

Start small, iterate based on responses, and refine your approach. The sooner you talk to the right people, the faster you’ll know whether your idea is worth building.

Would love to hear what responses you get—let me know how it goes!

PS: Was that useful? Leave me a ♡ so I know I’m on the right track.
What founder challenge should I tackle next? Maybe how to ask the right questions so you get useful feedback?

Most SaaS pricing feels like a shot in the dark.

Some founders price based on gut feeling.
A few ask customers, only to hear, "It depends."
Others copy competitors.

The result?

• Underpriced plans that leave money on the table.

• Overpriced tiers that scare away customers.

• Feature bundles that don't align with value.

Imagine if pricing was a science, not a guess.

Instead of playing a guessing game, what if you could structure your pricing based on customer value, willingness to pay, and business sustainability?

The Reforge Pricing Framework provides a structured approach, breaking SaaS pricing into tiers based on clear customer segments and usage behaviors. But it’s complex.

So I distilled it into an AI-friendly pricing prompt that guides you through the process—step by step.

The Framework (Simplified)

The Reforge framework structures pricing around three key principles:

1. Customer Segmentation:

   • Different user groups value different things.

   • Your tiers should match distinct use cases (e.g., startups vs. enterprises).

2. Value Metrics:

   • Identify the metric customers associate with value (e.g., seats, usage, storage).

   • Price scales based on the metric that best reflects success.

3. Psychological Price Anchoring:

   • Guide customer choices using a Good, Better, Best structure.

   • Your mid-tier should be the most compelling (high-margin, high-conversion).

Example: Slack’s Pricing Tiers

• Free (For individuals and small teams)

• Pro (Unlocks integrations and history)

• Business+ (Adds security and compliance)

• Enterprise Grid (Custom pricing for large orgs)

Each tier serves a specific customer need and scales on a clear value metric (users and features).

Now, let’s build your pricing model with AI.

The AI Pricing Prompt

Copy and paste this prompt into ChatGPT or Claude to get structured pricing recommendations:

I am pricing a B2B SaaS product called [your product name]. 

I need a structured pricing model based on customer segmentation and value metrics. Here's my business context:

1. Product & Market:
- My SaaS product helps [describe problem it solves].
- Our ideal customers are [small businesses, mid-market, enterprises, etc.].


2. Key Value Metric:
- Customers measure success by [monthly active users, storage used, transactions, API calls, etc.].


3. Competitive Landscape:
- My competitors charge [list competitors and their price points].


4. Tiers & Feature Breakdown:
- I want to create [number of tiers] pricing plans.
- My entry-level plan should focus on [self-serve, onboarding, usage limits].
- My premium plan should emphasize [enterprise needs, security, compliance].


Generate:

- A three-tier pricing model with recommended price points.
- Feature distribution per tier based on customer needs.
- Psychological price anchoring strategy (to maximize conversions).
- Optional add-ons or expansion pricing recommendations.

When to Use This Prompt?

Use this AI-assisted pricing approach when:

1. You’re launching a new SaaS product.

2. Your pricing feels misaligned with value.

3. You need to optimize conversion and expansion revenue.

Limitations & Next Steps

AI-generated pricing is a starting point, not a final decision. You still need to:

• Validate it with customer interviews.

• Test willingness to pay with real-world pricing experiments.

• Continuously iterate based on customer behavior and churn data.

Takeaway: Test it today.

Pricing isn’t a one-time decision—it’s a process.
Take 5 minutes, run your SaaS through this prompt, and compare the AI’s recommendation with your current pricing.

You might be surprised by what you uncover.

PS: Was that useful? Leave me a ♡ so I know I’m on the right track.
What founder challenge should I tackle next?

You underestimate how fast money disappears.

You raise funds (or bootstrap).
You set a rough budget and start building.
Three months in, cash flow gets tight.
Unexpected costs pile up.
Suddenly, you're scrambling to stretch every dollar.

The problem?

Traditional budgeting methods don’t fit early-stage startups.

They assume predictable revenue, stable expenses, and clear financial patterns—none of which exist when you’re just getting started.

You need a budget that adapts as you learn.
One that prioritizes survival, growth, and speed.
Not just financial discipline.

A Smarter Way to Budget

Instead of making a static budget, use an adaptive AI-driven approach that:

• Prioritizes key expenses that drive growth

• Flags unnecessary costs before they spiral

• Adjusts in real time based on your cash runway

Think of it as a financial co-pilot that helps you plan smartly without getting lost in spreadsheets.

The AI-Driven Startup Budget Framework

1. Define Your Baseline

   • What’s your total capital? (Savings, investment, revenue)

   • What’s your planned runway? (6, 12, 18 months?)

2. Identify Your Essential Costs

   • Core expenses (team, tools, hosting, marketing)

   • One-time vs. recurring costs

3. Allocate Based on Growth Drivers

   • Prioritize expenses that directly impact user acquisition, retention, or revenue

   • Use AI to model scenarios (e.g., “What if we cut tool X?” or “What if we increase ad spend?”)

4. Set Dynamic Cash Flow Monitoring

   • Use AI tools (like ChatGPT or Claude) to track actual spending vs. projections

   • Get automated alerts when burn rate exceeds safe limits

5. Run 'Survival Scenarios'

   • What happens if revenue stalls for 3-6 months?

   • How can you reduce costs without killing growth?

The Startup Budgeting AI Prompt

Copy-paste this into ChatGPT or Claude to get a startup-specific budget plan:

I’m building [your startup] and need a realistic budget for the next [X] months.  

My available capital is [$X], and my expected revenue is [$X/month].  

Here’s what I know:  
- Core expenses: [list your fixed costs like team, software, hosting]  
- Growth expenses: [list variable costs like marketing, partnerships]  
- One-time costs: [list any big upfront investments]  
- Runway goal: [e.g., “I need to last 12 months before raising again”]  

Help me:  
1. Identify critical vs. non-essential expenses  
2. Suggest a burn rate strategy to keep my runway safe  
3. Recommend adjustments based on realistic scenarios  
4. Spot any financial risks I might be missing  

Run this prompt, tweak the numbers, and refine based on the AI’s suggestions.
It’s like having a CFO without a full-time salary.

Why This Works

• Focuses on what matters (growth + survival, not just numbers)

• Quick to update (adjust as reality changes)

• Helps catch blind spots (AI sees patterns humans miss)

Try it out and see if your budget is truly startup-proof.

What’s the biggest budgeting mistake you’ve made in your startup?
Hit share in the comments—I might include it in the next issue.

PS: Was that useful? Leave me a ♡ so I know I’m on the right track.
What founder challenge should I tackle next?

Most founders struggle to explain their startup in a crisp, compelling way.

They either ramble on with too much detail or stay vague, confusing investors, customers, or partners.

And when the moment comes—at a pitch event, meeting, or even an unexpected conversation—they fumble instead of making an impact.

The Problem with Elevator Pitches

An elevator pitch is supposed to be short and punchy, but that’s where most founders go wrong:

• Too vague: “We help businesses scale with AI-powered solutions.”

• Too complex: “We optimize cross-functional workflows using predictive heuristics and machine learning automation.”

• Too generic: “It’s like Uber for X.”

The result? The listener tunes out.

The Ideal Pitch

Imagine if your pitch immediately grabbed attention, sparked curiosity, and left people wanting to hear more.

A great elevator pitch does three things:

1. Clearly states what you do.

2. Explains who it’s for and why they should care.

3. Ends with a hook that invites the listener to ask more.

And now, thanks to AI, you can refine and perfect your pitch in minutes.

The Framework

One of the best ways to structure an elevator pitch is using the Problem-Solution-Impact format:

• Problem: What pain point does your startup solve?

• Solution: How does your product/service solve it?

• Impact: What’s the key benefit or result for your target audience?

Here’s a real-world example:

Problem: Sales teams waste hours tracking deals manually.
Solution: Our CRM automates deal tracking and sends real-time alerts.
Impact: Teams close 20% more deals without extra effort.

Now let’s turn this into an AI-powered prompt.

The AI Prompt

Copy and paste this into ChatGPT or Claude, fill in the blanks, and refine:

Act as a startup pitch coach.  
I need a compelling elevator pitch for my startup.  

Here’s what I have so far:  
• My startup is called: [Company Name] 
• It helps: [Target Audience] 
• The main problem they face is: [Problem in 1-2 sentences] 
• We solve it by: [Solution in 1-2 sentences] 
• The biggest impact we create is: [Key benefit/result]  

Please format the pitch in a Problem-Solution-Impact structure.  

Then, give me three variations:  
1. A short version (one sentence) 
2. A conversational version (casual tone) 
3. A high-stakes version (for investors/pitch competitions)  

Also, include a hook at the end that encourages further conversation.

Why This Works

This template forces clarity. Instead of vague jargon, you get a structured, compelling pitch.

It also gives you variations—so you can adapt your pitch depending on who you’re talking to.

When to Use It

• Fundraising? Use the high-stakes version for investor meetings.

• Networking? Try the conversational version for casual chats.

• Cold outreach? The short version works great in emails and DMs.

Try It Now

Paste the prompt into ChatGPT or Claude.
Test different variations.
Refine the wording.

Then, next time someone asks, “What does your startup do?”—you’ll have the perfect answer.

PS: Was that useful? Leave me a ♡ so I know I’m on the right track.
What founder challenge should I tackle next?

That dreaded moment: deciding what goes into your MVP.

Building everything feels safe but leads to delayed launches and wasted resources. Most founders end up choosing features based on gut feel or investor pressure, resulting in bloated MVPs that miss market windows. The real cost isn't just time and money – it's the missed opportunity to learn from real users.

The difference between a successful MVP and a failed one often comes down to what you choose to leave out.

The Ideal Solution

Every startup needs a systematic way to evaluate feature priorities.

The perfect solution would combine quantitative scoring with startup-specific constraints, accounting for both market impact and development realities. It would help founders make confident decisions about what to build first, backed by data but practical enough for early-stage startups. Most importantly, it would be quick to implement and adapt as you learn.

What we need is a framework that turns subjective feature debates into objective decisions.

The RICE Framework Adapted

Rice Scoring comes from Intercom's product team, but we'll adapt it for startups.

The framework evaluates features using four metrics: Reach, Impact, Confidence, and Effort. For startups, this provides a beautiful balance between data-driven decisions and practical constraints. The key is modifying it to account for MVP-specific considerations like technical dependencies and core feature requirements.

Example RICE calculation:

1. Feature reaches 30% of users (0.3)

2. High impact score (1.0)

3. 80% confidence (0.8)

4. 5 days of effort

5. RICE score = (0.3 * 1.0 * 0.8) / 5 = 0.048

RICE gives you a numerical score for each feature, making priorities crystal clear.

The AI-Ready Template

Our template structures the prioritization process in a founder-friendly way.

The prompt combines RICE scoring with MVP-specific considerations, helping you think through both quantitative and qualitative aspects of each feature. It's designed to work with AI assistants like Claude or GPT-4, turning your rough thoughts into actionable priorities.

I am building [product name] to solve [core problem] for [target users].

My initial feature list includes:
- [List 3-5 key features you're considering, one per line]

My constraints:

Time to initial launch: [target timeline]

Development resources: 
- [team size/availability]

Technical limitations: 
- [any major constraints]

--------

Using RICE framework, evaluate each feature with:

RICE Score Components:

- Reach: How many users will this impact in a quarter [0-100%]
- Impact: Effect on user experience [0.25=minimal, 0.5=moderate, 1.0=high, 2.0=massive]
- Confidence: How sure am I about estimates [0-100%]
- Effort: Dev time needed [days, rough estimate]

Additional MVP Considerations:

- Must-have vs. nice-to-have [essential/optional]
- Technical complexity [low/medium/high]
- Dependencies on other features [yes/no, which ones]

Expected output:

- Ranked feature list with RICE scores
- Core MVP feature recommendations
- Risk assessment
- Suggested development sequence
- Estimated MVP timeline

Use this template when:

• You have a list of potential MVP features

• You're struggling to decide what to build first

• You need to justify feature priorities to stakeholders

Limitations:

1. Requires some market understanding to estimate reach and impact

2. Works best with 3-7 features at a time

3. May need adjustment for highly innovative products

The template isn't perfect, but it's far better than gut-based decisions.

The Real Value

Feature prioritization isn't about perfect scores – it's about confident decisions.

This framework forces you to think systematically about each feature's value, while the AI helps spot gaps in your reasoning and suggests alternatives you might have missed. It turns vague feature ideas into concrete build decisions, helping you launch faster with the right MVP.

Your MVP's success depends more on what you leave out.

Take Action Now

Open your favourite AI assistant (I’m team Claude) and paste in the template.

Run your current feature list through it.
Pay special attention to features that score surprisingly high or low – they often reveal hidden assumptions about your product.

Let's build better MVPs, one feature at a time.

PS: Was that useful? Leave me a ♡ so I know I’m on the right track.
What founder challenge should I tackle next?

Stop staring at that blank landing page.

You know your product solves real problems, but somehow the words aren't flowing. The messaging frameworks you've found feel too corporate.

And AI prompts are giving you generic marketing fluff.

The Messaging Trap

Most founders face this exact problem.
They swing between being too technical ("our proprietary algorithm optimizes cross-functional workflows") and too vague ("transform your business").

The result?
Landing pages that confuse prospects instead of converting them.

A Better Way

Imagine having a systematic way to transform your product knowledge into compelling landing page copy. No marketing jargon, no empty promises – just clear messaging that shows prospects exactly how you'll solve their problems.

Even better, imagine having a ChatGPT or Claude that understands B2B SaaS and can help you iterate on your copy rapidly.

The Expert Framework

Enter Anthony Pierri's B2B SaaS positioning framework.
As a messaging expert who's helped numerous B2B startups nail their homepage copy, Pierri developed a structured approach that focuses on what matters: specific user problems, concrete capabilities, and immediate benefits.

The framework breaks down landing page messaging into clear building blocks:

- Market Segment Definition: Who exactly are you targeting?
- Context: How do they work today?
- Problems: What specific moments cause pain?
- Product Category: Where do you fit in their toolkit?
- Capabilities: What new things can they do?
- Features: What specific elements enable those capabilities?
- Benefits: What immediate, guaranteed outcomes can you promise?

Here's how it works.
Instead of writing "Transform your sales operations with AI-powered insights," you'd write:

"When sales managers spend their Monday mornings manually compiling pipeline reports [context], they miss critical deal risks [problem]. Now you can automatically identify at-risk opportunities [capability] using our real-time deal health scoring [feature], so you never start the week with surprise deal losses [benefit]."

Here is the prompt

I've turned this framework into an AI prompt template that helps you generate and iterate on your landing page copy quickly. The prompt structures your inputs to focus on specific details that matter, helping you avoid vague marketing speak and unrealistic promises.

Copy/paste and fill out the [placeholders].

Act as a SaaS positioning expert and help me out.

I am building landing page copy for my B2B SaaS product. Here's what I know:

Market Understanding

- My target persona is [individual role or team, e.g., "Head of Sales" or "IT department"]
- They typically work in [company size/type, e.g., "mid-market B2B companies with 100-500 employees"]
- Their current process involves [2-3 sentences about how they currently handle the problem]
- Their specific struggling moment is [describe a concrete situation where they feel pain, e.g., "spending 3 hours every Monday morning manually compiling sales reports"]

Product Positioning

- My product category is [single, specific category, e.g., "sales analytics platform" or "IT workflow automation tool"]
- The main capability we unlock is [what users can do now that they couldn't before, in one sentence]
- Our key technical features include [2-3 core technical capabilities]
- Our key UI/UX features include [2-3 main interface or usability features]
- The immediate, guaranteed benefit is [specific, measurable outcome users get]

Social Proof Elements

- We have [X] customers in [target market]
- Our key testimonial is [single most impressive customer quote]
- Our most relevant certification/compliance is [security/technical certification]

Goals

- Primary conversion goal: [specific action, e.g., "book a demo" or "start free trial"]
- Secondary goal: [backup conversion action, e.g., "join waitlist" or "download whitepaper"]

----

Please help me create:

1. A hero section headline and subheadline

2. A problem section that describes:
- The status quo and its limitations
- The costs of not solving this problem
- Why existing solutions fall short

3. Three main benefit statements with supporting feature details
A primary call-to-action statement

Use simple, direct language focused on capabilities rather than abstract benefits. Avoid jargon, buzzwords, and marketing speak.

Best Use Cases

The template works best when:

• You have a clear understanding of your target user

• You can describe specific moments where users struggle

• You know your core product capabilities

• You have some initial customer proof points

Use it early in your landing page process to generate a first draft, then iterate based on feedback. The prompt is particularly effective for:

• Testing different angles with the same core information

• Ensuring consistency across page sections

• Moving quickly from technical features to user benefits

Keep in mind: This is a starting point, not a magic solution.
The output will need editing to match your voice and may miss nuances specific to your market. It works best when combined with customer conversations and real-world feedback.

Remember

Effective SaaS landing pages aren't built on clever marketing – they're built on specific user problems, concrete capabilities, and immediate benefits. This framework helps you identify those elements, and the AI prompt helps you turn them into compelling copy.

Your turn

Take 2 minutes now to test it.
Pick your most important user persona, think of one specific moment they struggle, and run it through the prompt.

You might be surprised at how quickly you can generate effective copy.

PS: Was that useful? Leave me a ♡ so I know I’m on the right track.
What founder challenge should I tackle next?

Marketing feels like shouting into a hurricane these days.
Every channel is saturated, every tactic has been copied, and the traditional playbooks just don't work like they used to for early-stage startups.

A Different Approach

Drawing from Alistair Croll's "Just Evil Enough" framework and tools like ChatGPT and Claude, we can create marketing that stands out without requiring massive budgets or established brand recognition.

The framework breaks down into four key elements:

1. System Awareness: Understand your market's unwritten rules and norms

2. Novelty and Creativity: Find unexpected angles that people won't copy

3. Acceptable Disagreeability: Push boundaries just enough to gain attention

4. Recon Canvas: Analyze opportunities across Product, Market, and Medium

Take Dropbox's early growth strategy as an example.
Instead of spending heavily on ads, they turned their limitation (need for viral growth) into an advantage. They created a referral program offering extra storage for both parties - a classic "Bug into Feature" play that got users marketing for them. It was just unconventional enough to work, without crossing any ethical lines.

Let's be clear – this isn't about being unethical or deceptive.
It's about being just different enough to get noticed while staying true to your values and customer needs. Think of it as "pattern interruption with purpose."

The Subversive Marketing Template

Here's the prompt template I've developed that combines subversive marketing principles with AI guidance. It's specifically designed for startup founders who need to make an impact with limited resources.

I am building [product/service] and want to break through the noise in my market using creative, unconventional approaches. Here's my situation:

Context 
My target market is [describe your ideal customer].
The conventional way companies market in my space is [describe typical marketing approaches].
My biggest marketing challenge right now is [describe your main obstacle].

System Analysis
What are the "unwritten rules" or standard practices in my industry that everyone follows? Example: All companies in my space use technical jargon in their marketing.

I think these are:
- [Rule/practice 1]
- [Rule/practice 2]
- [Rule/practice 3]


Resources & Constraints
My unique advantages are:
Example: Direct access to specific community/network/resource.

- [Unique advantages 1]
- [Unique advantages 2]

My key limitations are:
Example: Marketing budget under $5000/month.

- [limitations 1]
- [limitations 2]

Risk Tolerance
On a scale of 1-10, where:
1 = Very conservative.
5 = Willing to be noticeably different
10 = Ready to be radically different

My risk tolerance is [number] because [brief explanation].

---

Based on your inputs, you'll receive:

Analysis of which subversive tactics best fit your situation, chosen from:

- Bug into Feature: Turn limitations into selling points
- Buyer Upgrade: Shift target audience without changing product
- Access: Leverage unique network/resource access
- Bait and Switch: Offer initial value, then upsell strategically
- Combination: Bundle products/services in unexpected ways
- Arbitrage: Exploit information or timing advantages
- Aggregation: Collect and structure niche data/resources
- Reframing: Create new positioning or perspective
- Regulation Exploits: Use regulatory frameworks advantageously
- Sliding the Overton Window: Gradually shift what's acceptable
- Misappropriation: Repurpose existing systems creatively


For each recommended tactic:

- Specific application to your situation
- Implementation roadmap
- Risk assessment
- Success metrics


Recon Canvas analysis showing how to apply tactics across:

- Product: How to modify or position your offering
- Market: How to approach your target audience
- Medium: Which channels to leverage


Experimentation plan:

- Small-scale test design
- Key metrics to track
- Specific boundaries not to cross
- When to scale up or pivot

How to Use This Framework

The power of this approach lies in how it forces you to think systematically about breaking patterns. Instead of randomly trying to be different, you're strategically identifying opportunities where unconventional approaches can work in your favor.

Use this two-step process with AI:

1. Generate initial ideas using ChatGPT for each tactical approach

2. Refine and analyze these ideas with Claude's more nuanced capabilities

Remember, these AI tools are your thought partners, not your solution. Feed them specific information about your market, constraints, and risk tolerance. Then use their suggestions as a starting point for your own strategic thinking.

Getting Started

Start small. Test one unconventional tactic in a controlled way. Measure the response. Scale what works.

What's your biggest marketing challenge right now?

Try running it through this template with both ChatGPT and Claude to see what unconventional approaches emerge.

PS: Was that useful? Leave me a ♡ so I know I’m on the right track.
What founder challenge should I tackle next?

Most founders jump straight from idea to building.

They're confident they've spotted a problem worth solving.

But confidence isn't enough when you're investing time and resources into a solution.

You need a systematic way to validate your idea before committing fully.

After watching dozens of founders struggle with validation (myself included), I knew there had to be a better approach. Then I discovered how Jobs To Be Done framework could be adapted for early-stage validation, and everything clicked.

The Problem with Validation

Founders often validate their ideas through scattered conversations and gut feelings. They collect random feedback until something "feels right" or worse—build based on their assumptions alone.

The result? Solutions that:

• Miss the mark on real customer needs

• Solve problems no one wants to pay for

• Create features customers don't use

• Waste precious development time

The Framework

Jobs To Be Done shines in understanding what customers are really trying to accomplish. While the full framework covers emotional and social aspects, its functional core is perfect for B2B solution validation.

But using the raw framework isn't enough. You need a practical system that focuses on what matters most: ensuring your solution fits a real problem worth solving.

That's why I built a prompt template that combines JTBD's functional analysis with validation filters that ensure you're on the right track.

The prompt helps you:

• Break down the exact job customers need done

• Validate your understanding with clear metrics

• Reality-check your solution's feasibility

Think of it as your personal advisory board that never gets tired, never loses objectivity, and always checks the important details.

The Template

Here's how it works:

1. Copy/paste the prompt in Chat GPT or Claude

2. Fill out the sections honestly. Don't sugarcoat your assumptions

3. Get scored on your problem/solution fit

PROBLEM/SOLUTION FIT ANALYSIS

I have an idea for a product/feature that I want to make sure will solve my customers' problems. Let me explain...

MY IDEA
- I am building [what are you building? be specific]
- Right now, I have [current stage: just an idea, prototype, beta users, etc.]

WHO IT'S FOR
- I want to help [be specific about your target customer]
- They work in [industry/sector]
- They are typically [key characteristics that matter]

THE PROBLEM AND SOLUTION
- I believe they struggle with [what problem did you spot?]
- I'm confident about this because [what evidence or insights do you have?]
- My solution will help them by [how exactly will you solve their problem?]
- Their current process is [how do they solve this today? list 3-4 steps]
- The biggest pains in this process are [what frustrates them the most?]

MEASURING SUCCESS
- Today, this takes them [current time/money/resources spent]
- With my solution, they could [what specific improvements will they see?]
- This means [translate to business value - money saved, time gained, etc.]

REALITY CHECK
- For this to work, they'll need to [what do customers need to do/have?]
- I'm worried about [what might go wrong or prevent adoption?]
- Next, I should [what do you need to validate first?]

-------------------
Based on your answers, you'll receive:

1. A Problem/Solution Fit Score (0-100%)
   - Problem Understanding (0-25%)
   - Solution Match (0-25%)
   - Value Proposition (0-25%)
   - Implementation Clarity (0-25%)

2. Gaps Analysis
   - Critical Gaps: What crucial information or validation is missing
   - Assumption Risks: Which assumptions need the most urgent verification
   - Edge Cases: Important scenarios you might not have considered

3. Action Plan
   - Quick Wins: Immediate actions to improve fit (next 1-2 weeks)
   - Critical Tasks: Essential validation needed (next 1-2 months)
   - Risk Mitigation: Specific steps to address biggest concerns

Each action item will include:
- What to do
- How to do it
- Expected outcome
- How this improves your fit score

When to Use It

Use this template when:

• You have a clear idea but haven't started building

• You're pivoting your existing solution

• You're adding major new features

• You're entering a new market segment

The magic happens in the gaps analysis. Pay special attention to assumptions that need validation and edge cases you might have missed.

Why This Works

The template succeeds because it:

• Forces concrete thinking about customer needs

• Demands specific metrics instead of vague benefits

• Highlights risky assumptions before they become costly mistakes

• Provides actionable next steps based on your gaps

Is it perfect? No. You still need to talk to real customers and validate your assumptions. But it gives you a structured starting point and helps you ask better questions when you do those customer interviews.

Ready to Test It?

Think about that idea you've been sitting on. The one you're pretty sure could work, but haven't validated yet. Run it through this template.

You might be surprised by what you discover. Either you'll gain confidence in your direction, or you'll spot critical gaps before investing too much time.

Either way, you'll be making decisions based on analysis rather than assumptions.

PS: Was that useful? Leave me a ♡ so I know I’m on the right track.
What founder challenge should I tackle next?

Naming a startup is like getting a tattoo.

Choose wrong, and you're stuck with a painful reminder of poor judgment.

Choose right, and you've got a conversation starter that opens doors.

After watching a dozen founders struggle with random name generators and thesaurus diving, I knew there had to be a better way.

Then I saw Greg Isenberg break down his framework for naming startups, and everything clicked.

The Problem with Startup Names

Most founders approach naming like throwing darts blindfolded. They brainstorm until something "feels right" or worse—pick the first available .com domain they find.

The result? Names that:

• Feel disconnected from their target audience

• Create confusion about what the company does

• Limit growth potential

• Sound like every other startup in their space

The Greg Principle

Greg's genius lies in his three-category approach to naming:

• Descriptive names that explain your purpose

• Cultural phrases that ride momentum

• Humor-based options that stick in memory

But knowing the categories isn't enough. You need a system to generate and validate names that hit these marks consistently.

That's why I built an AI prompt that combines Greg's framework with validation filters that ensure your name can scale.

The prompt forces AI to:

• Generate names across all three categories

• Check them against critical validation tests

• Assess future-proofing potential

• Evaluate branding possibilities

Think of it as your personal naming committee that never gets tired, never gets stuck in one creative lane, and always checks the important details.

The Prompt

Here is how it works:
Copy/paste the prompt in Chat GPT or Claude (like Claude results better).
Fill out the [placeholders] with your info. And hit enter.

I'm brainstorming names for a [describe your startup/product] that [describe core function/purpose]. The target audience is [describe ideal customers/users].

Name Type Preferences
Please generate names in these categories:

1. Descriptive Names
    * Clear, direct names that immediately convey what the product/service does
    * Should pass the "telephone test" (easy to spell when heard)
2. Cultural Phrases
    * Emerging terms or expressions that resonate with the target audience
    * Words/phrases that are gaining cultural momentum
3. Humor-Based Names
    * Names that could make people smile or create memorable associations
    * Potentially incorporate wordplay or clever references

Requirements Checklist
Please ensure all suggested names:
* Are memorable and scroll-stopping
* Pass the telephone test (easy to spell when heard)
* Avoid negative words or connotations
* Can be transformed into a strong visual brand
* Are available as a .com domain (preferred) or have obvious alternatives
* Work well as social media handles
* Don't feel "tofu" (bland/generic that could apply to any industry)

Additional Considerations
Please assess each name against these criteria:
* Does it suggest positive action/outcomes?
* Could it scale beyond the initial product/service?
* Does it have international implications or potential issues?
* Could it become a verb or common phrase?
* Does it have strong branding potential?

Format Requests
For each suggested name, please provide:
1. The name itself
2. Category (Descriptive/Phrase/Humor)
3. Generate 5 options for each category

Variation Requests
Please provide options that are:
* Single words
* Two words
* Three words (if appropriate)
* With and without AI/tech suffixes (if relevant)

When you get the first batch of ideas tell the AI: more or this, less from that and keep prompting. I usually get 2 to 3 good ones on the first try.
Next, look if the domain is available.

What surprised me most when testing this prompt was how it consistently produced names that founders wouldn't have considered—yet immediately resonated with their target audience.

What's the most memorable startup name you've encountered recently, and why did it stick with you? Drop your examples below.

I've spent 100+ hours experimenting with AI tools.
And 16+ years of helping founders design SaaS start-ups.
AI has become integral to my startup design process in recent months.

Here's what I've learned about finding validated startup ideas.

Common Mistakes in Startup Ideation

Many first-time founders fall into predictable traps when searching for startup ideas:

1. Starting with Solutions, Not Problems

• Building something cool without validating if anyone needs it

• Getting excited about technology rather than user pain points

• Assuming others have the same problems you have

2. Targeting Overcrowded Markets

• Building "another X for Y" without clear differentiation

• Entering markets dominated by well-funded competitors

• Choosing ideas based on current trends rather than lasting problems

3. Insufficient Market Research

• Relying on friends and family for validation

• Not talking to potential customers before building

• Making assumptions about user behavior without data
  

4. Poor Problem Selection

• Solving "nice to have" instead of "must have" problems

• Targeting problems without clear monetization potential

• Choosing problems where users have no budget or buying power
  

Characteristics of High-Potential Startup Ideas

Strong startup opportunities typically share these traits:

1. Problem Characteristics

• Frequent and painful enough to demand immediate attention

• Affects users with purchasing power

• Currently solved through expensive or inefficient workarounds

• Growing in importance due to market trends
  

2. Market Characteristics

• Large enough to support significant growth

• Expanding or evolving due to industry changes

• Clear path to monetization

• Limited but not zero competition (validates market exists)
  

3. Solution Potential

• Technical feasibility with current technology

• Clear competitive advantage possible

• Reasonable customer acquisition costs

• Strong unit economics potential
  

Step 1: Finding Problems Using Reddit and Perplexity

Use this prompt with Perplexity to mine Reddit for valuable problems:

Search Reddit for people expressing significant frustration, pain points, and "I wish" statements in [INSERT YOUR INDUSTRY/DOMAIN]. 

Focus on subreddits where your target users hang out, especially professional/industry-specific ones like r/developers, r/consulting, r/sales, etc.

Look for:
- Posts starting with "How do you deal with..."
- Comments containing "I hate that I have to..."
- Phrases like "The worst part of my job is..."
- Recurring complaints about existing tools/processes
- People describing manual/repetitive tasks
- Comments about "wasting time on..."
- Posts asking "Is there a tool that can..."

For each significant problem found:

PROBLEM 1:

- Pain Point: [Describe the core frustration/challenge]
- Audience Profile: [Job roles/industries expressing this pain]
- Current Solutions: [How people are currently handling this]
- Impact Level: [Time wasted/costs/emotional frustration described]
- Mention Frequency: [Number of unique users expressing this pain]
- Representative Quotes:

  * [Include 2-3 detailed problem descriptions]
  * [Focus on quotes that quantify the impact]

PROBLEM 2:

[Repeat format]

Prioritize problems where:

- Multiple users express strong emotional frustration
- People are currently using hacky/manual workarounds
- The problem costs significant time/money
- Users mention they'd "pay anything" for a solution
- The pain point affects a specific professional audience
- The problem appears unsolved despite existing tools

Sort by problem impact and frequency. Only include problems from the last 6 months.

Analyzing Perplexity Results

When reviewing the results, focus on:

1. Problems mentioned frequently across different communities

2. Clear patterns in user frustrations

3. Quantifiable impact (time/money wasted)

4. Evidence of current workarounds

5. Signs of willingness to pay

Step 2: Ideating Solutions

Once you've identified a promising problem, use this prompt with Claude to explore potential SaaS solutions:

CONTEXT:
[Insert problem description, target audience, and current workarounds found through Perplexity]

Please generate 3 potential SaaS solutions with:

1. SOLUTION OVERVIEW
- Core value proposition
- Key features for MVP
- Main differentiator
- Target price point

2. VALIDATION PATH
- Quickest path to first customer
- Manual MVP approach
- Key metrics to track
- Initial distribution channel

3. RISKS & CHALLENGES
- Main technical hurdles
- Competition risks  
- Critical resource needs

Prioritize solutions that can be:
- Built with minimal initial resources
- Validated quickly with real users
- Monetized early

Step 3: Validation Without Building

Before writing any code, validate your chosen solution through:

1. Landing Page Test

• Create a simple landing page describing your solution

• Run minimal ads to drive traffic

• Measure email signups and engagement

• Analyze which value propositions resonate
  

2. Customer Interviews

• Find 20+ potential customers

• Focus on understanding their workflow

• Present solution concepts (not features)

• Ask for pre-commitments or letters of intent

3. Fake Door Testing

• Add "Buy Now" or "Sign Up" buttons

• Measure click-through rates

• Capture email addresses of interested users

• Test different pricing tiers
  

4. Manual MVP

• Deliver the service manually to early customers

• Use existing tools to cobble together solutions

• Focus on learning what users truly value

• Validate willingness to pay
  

Success Indicators

Your idea is worth pursuing when:

1. Problem Validation

• Multiple users express strong interest

• Clear pattern in pain points emerges

• Users are actively seeking solutions

• Current solutions are inadequate

2. Market Validation

• Significant market size confirmed

• Clear path to monetization

• Reasonable customer acquisition costs

• Strong unit economics potential

3. Solution Validation

• Users excited about proposed solution

• Pre-commitments or letters of intent secured

• Strong landing page conversion rates

• Successful manual MVP tests

4. Business Validation

• Clear competitive advantage identified

• Sustainable business model possible

• Reasonable development costs

• Path to scale visible

Key Takeaways

1. Start with real problems, not solution ideas

2. Use data-driven research to validate problems

3. Generate multiple solution approaches

4. Validate before building

5. Focus on problems where users have both pain and budget

6. Look for opportunities to start small but scale big
   

The goal isn't to find a perfect idea, but rather to identify a promising problem space where you can create significant value for users while building a sustainable business.