Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
Last year, a potential client approached me with an exciting opportunity: build a two-sided marketplace platform. The budget was substantial, the technical challenge was interesting, and it would have been one of my biggest projects to date.
I said no.
Here's the thing - this client came to me excited about the no-code revolution and new AI tools. They'd heard these tools could build anything quickly and cheaply. They weren't wrong about the technical capabilities, but their core statement revealed a fundamental problem: "We want to see if our idea is worth pursuing."
They had no existing audience, no validated customer base, no proof of demand. Just an idea and enthusiasm. Sound familiar?
In this playbook, I'll walk you through why most software proof of concepts fail before they even start, and the contrarian approach I recommend instead. You'll discover:
Why building a product to "test market demand" is backwards thinking
The real purpose of a proof of concept in 2025 (hint: it's not what you think)
My 4-step validation framework that takes days, not months
When to actually build vs when to fake it
How to turn manual processes into your competitive advantage
This approach has saved my clients hundreds of thousands in development costs while actually increasing their chances of success. Ready to challenge everything you've been told about software validation?
Industry Reality
What the startup world preaches about MVPs
If you've spent any time in startup circles, you've heard the gospel of the Minimum Viable Product. The advice is everywhere: "Build fast, ship early, iterate quickly." Every accelerator, every blog post, every LinkedIn thought leader repeats the same mantra.
Here's what the industry typically recommends for software proof of concepts:
Start with an MVP: Build the simplest version of your product with core features
Launch to get feedback: Put it in front of users as quickly as possible
Measure everything: Track user behavior, conversion rates, engagement metrics
Iterate based on data: Use feedback to improve the product
Scale what works: Double down on successful features and user segments
This conventional wisdom exists because it sounds logical. It feels scientific. It gives founders a structured approach to reduce risk. And honestly, it works great... for products that already have proven demand.
But here's where this approach falls apart in practice: You're still building before you know if anyone wants what you're building. Even a "minimum" viable product can take weeks or months to develop. You're optimizing for speed of development when you should be optimizing for speed of learning.
The real problem isn't the time to build - it's that most founders confuse validation with development. They think proving the concept means proving they can build it. But the hardest part was never the building - it's finding people who actually want to buy it.
That's why I take a completely different approach. Instead of building to test, I test before building. Let me show you what happened when I applied this thinking to that marketplace project.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
When that client came to me wanting to build a two-sided marketplace, everything about the project looked perfect on paper. They had a solid budget, clear technical requirements, and genuine enthusiasm. But one statement stopped me cold: "We want to see if our idea is worth pursuing."
This wasn't a client who had validated demand and needed execution. This was someone hoping to use development as market research. They were essentially asking me to build an expensive experiment.
The client's situation was classic startup thinking gone wrong. They'd identified a real problem in their industry - connecting suppliers with buyers more efficiently. They'd even done some initial research and found that existing solutions were clunky and overpriced. So far, so good.
But then they made the leap that kills most startups: they assumed a technical solution was the answer. Their reasoning was straightforward - "If we build a better platform, people will use it." They wanted to test this hypothesis by building the platform and seeing what happened.
Here's what they actually had:
A problem they believed existed
A solution they thought would work
Zero proof that anyone would pay for that solution
No existing relationships with potential customers
No distribution strategy beyond "build it and they will come"
I'd seen this pattern before. In fact, I'd been part of it. Early in my freelance career, I built beautiful, functional products for clients who were essentially hoping the market would validate their assumptions post-launch. Most of those products are digital graveyards now.
That's when I realized something that changed how I approach every project: Your MVP should be your marketing and sales process, not your product. If you can't manually deliver value to customers first, you definitely can't automate it.
Here's my playbook
What I ended up doing and the results.
Instead of taking their money to build a platform, I gave them something more valuable: a framework to validate their idea without writing a single line of code. Here's the exact process I walked them through:
Step 1: Manual Value Delivery Test
"Can you solve this problem manually for 10 customers?" I asked them to create a simple landing page explaining their value proposition and start reaching out to potential suppliers and buyers directly. No platform, no automation - just good old-fashioned hustle.
The goal wasn't to scale; it was to prove that:
Suppliers actually wanted more customers
Buyers were frustrated with current solutions
Both sides would pay for better connections
The unit economics could work
Step 2: The WhatsApp MVP
Week 1: Create a simple landing page with Notion or a basic website builder. Week 2-4: Start manual outreach to potential users on both sides. Use WhatsApp, email, or even phone calls to manually match supply and demand. Document every interaction, rejection, and success.
This "technology" isn't scalable, but it's perfect for learning. You'll discover pricing sensitivity, actual user needs, and operational challenges without investing months in development.
Step 3: Prove the Economics
Before building anything, they needed to answer:
What would customers pay for this service?
How much does it cost to acquire each customer?
What's the lifetime value of a customer?
How much manual work can you eliminate before automation becomes profitable?
Step 4: Build Only What You Can't Fake
After proving demand manually, then you can start automating. But here's the key: only automate processes you've already proven work. Don't build features you think customers want - build features that eliminate work you're already doing manually.
This approach flips traditional thinking on its head. Instead of building to test, you test to build. Instead of hoping customers will come, you find customers first.
Validation Framework
Manual process testing before any development starts
Market Research
Real customer conversations trump surveys and assumptions
Economics Proof
Unit economics validation through actual transactions
Build Strategy
Only automate processes already proven manually
Three months later, my client sent me an update. They'd followed the manual validation approach and discovered something crucial: their original idea was wrong, but they'd found something better.
Turns out, suppliers didn't need more customers - they needed better customers. The real pain point wasn't connection volume; it was connection quality. Through manual outreach, they learned that suppliers would pay premium prices for pre-qualified leads rather than more leads.
This insight completely changed their business model. Instead of building a marketplace platform, they pivoted to a lead qualification service. They're now manually vetting buyers and selling qualified leads to suppliers at 3x the price they originally planned to charge for platform access.
Best part? They're profitable without building any software. They validated demand, proved the economics, and built a sustainable business using nothing more than Google Sheets and email. When they eventually do build software, it'll be to scale something that already works, not to test if it might work.
The "proof of concept" wasn't a piece of software - it was proof that customers would pay for the value they provided. That's the only validation that matters.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the top lessons I've learned from applying this approach across multiple client projects:
Manual > Automated for validation: If you can't deliver value manually, you definitely can't automate it profitably
Customers > Features: Finding people who want to pay is harder than building features they might want
Distribution > Product: Your go-to-market strategy matters more than your product quality in the early stages
Revenue > Metrics: Actual money changing hands tells you more than any engagement metric
Constraints breed creativity: Forcing yourself to solve problems manually often reveals better solutions
Speed of learning > Speed of building: Learning what customers want is more urgent than building what you think they want
Pivot early, not late: It's easier to change direction when you haven't invested months in development
The biggest mindset shift? Stop treating software development as market research. Use actual market research for market research, then use development to scale what you've already proven works.
When this approach works best: When you're testing a new market, new customer segment, or fundamentally new value proposition. When it doesn't work: When you're optimizing an existing, proven business model.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups looking to implement this playbook:
Start with Calendly + Notion instead of building a platform
Manual onboarding reveals product-market fit faster than automated flows
Use email sequences and personal outreach before building in-app messaging
Validate pricing through actual sales conversations, not landing page tests
For your Ecommerce store
For e-commerce stores testing new concepts:
Sell products manually through social media before building a full store
Use WhatsApp Business for customer service before implementing chatbots
Test demand through pre-orders and waitlists, not inventory investment
Validate shipping and fulfillment manually before automating logistics