Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
Last year, I had one of those moments that completely changed how I think about MVP development. A potential client approached me with an exciting opportunity: build a two-sided marketplace platform using AI and no-code tools like Bubble. The budget was substantial, the technical challenge was interesting, and it would have been one of my biggest projects to date.
I said no.
Not because I couldn't deliver—I absolutely could have built exactly what they wanted. But because they were asking the wrong question entirely. They wanted to know if their idea would work by building the full solution first. That's backwards, and expensive, and honestly? It's the reason most AI-powered MVPs fail.
Here's what you'll learn from this experience:
Why most MVP strategies fail before you write a single line of code
The real purpose of an MVP in the AI era (hint: it's not what you think)
A simple framework that saved my client $50,000+ and 3 months of development
When to build with Bubble AI tools vs. when to validate manually
The one-day MVP test that beats months of development
If you're considering building an AI-powered product or wondering whether to invest in complex no-code platforms, this case study will save you from making a very expensive mistake.
Industry Reality
What most founders get wrong about AI MVPs
Walk into any startup accelerator or browse Product Hunt, and you'll see the same pattern everywhere: founders rushing to build AI-powered platforms using tools like Bubble, believing that "MVP" means "minimum viable product that looks and works like the full vision."
The standard advice goes like this:
Start with no-code tools because they're faster and cheaper than custom development
Build core features quickly to test market demand
Add AI capabilities to differentiate from competitors
Launch to get user feedback and iterate based on usage
Scale the platform once you prove product-market fit
This approach exists because it feels logical and mirrors how successful products evolve. The problem? It confuses building with validating. Even with AI and no-code tools making development faster, you're still optimizing for the wrong thing.
The real issue isn't technical—it's strategic. Most founders are so excited about the possibilities of AI and platforms like Bubble that they skip the most important step: proving people actually want what you're planning to build.
In 2025, the constraint isn't building—it's knowing what to build and for whom. AI tools and no-code platforms have made the "how" easier, but they've made the "what" and "who" even more critical to get right first.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The 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, and they weren't wrong—technically, you can build a complex two-sided marketplace with these platforms.
But their core statement revealed the fundamental problem: "We want to see if our idea is worth pursuing."
They had enthusiasm and a budget, but that was it. No existing audience, no validated customer base, no proof of demand. Just an idea and the belief that building it would somehow prove its worth.
This is where most AI MVP projects go wrong. The founders think: "If we can build it fast and cheap, why not just build it and see what happens?" It sounds reasonable, but it's backwards thinking.
What I realized from this conversation—and what my experience with AI automation projects had taught me—is that even "quick" builds take significant time. Building a functional two-sided platform, even with no-code tools, would have taken 2-3 months minimum. That's 2-3 months of opportunity cost, 2-3 months of burning budget, and 2-3 months of building something that might have zero demand.
The client was treating their MVP like a product development project when it should have been a marketing and validation exercise. They wanted to test if people would use their platform by building the platform first. That's like opening a restaurant to see if people like your food instead of cooking samples first.
Here's my playbook
What I ended up doing and the results.
Instead of saying "yes" to the lucrative project, I shared a completely different approach that challenged everything they thought they knew about MVP development:
"If you're truly testing market demand, your MVP should take one day to build—not three months."
Here's the step-by-step framework I recommended:
Day 1: Create Your Validation MVP
Instead of building a platform, create a simple landing page or Notion document explaining your value proposition. Make it feel real, but don't build functionality yet. Focus on clearly communicating what problem you solve and for whom.
Week 1: Manual Outreach Campaign
Start direct outreach to potential users on both sides of your marketplace. Don't pitch the platform—pitch the solution. Find people who have the problem you're solving and ask if they'd be interested in a solution.
Week 2-4: Manual Matchmaking Process
Here's the crucial part: manually facilitate the core interaction your platform would automate. If you're building a marketplace, manually match supply and demand via email, WhatsApp, or simple spreadsheets. If you're building an AI tool, manually provide the intelligence.
Month 2: Scale Manual Process
Only after proving demand through manual processes should you consider building automation. Start with simple tools—Airtable, Zapier workflows, basic forms—before jumping to complex platforms like Bubble.
This approach tests the fundamental assumption: do people actually want what you're building? And it does it without spending months in development.
The key insight from my AI automation experience is that the technology to build has never been easier—the challenge is knowing what to build. Your MVP should be your marketing and sales process, not your product.
Validation First
Test demand before building anything complex
Manual Scaling
Start with manual processes to prove the concept works
One-Day Setup
Create validation tools in hours, not months
Market Reality
Learn what customers actually want vs what you think they want
The client initially pushed back on this approach. They wanted something that "looked real" and worried that manual processes wouldn't properly test their idea. But after walking through the economics—$50,000+ in development costs versus a few weeks of manual testing—they agreed to try the validation-first approach.
Within two weeks of manual outreach, they discovered something crucial: their target market had the problem they wanted to solve, but the solution they'd planned wasn't what users actually wanted. The feedback revealed a much simpler, more focused approach that required different technology entirely.
Instead of building a complex two-sided marketplace, they ended up creating a simple matching service that could be operated through existing tools. No custom platform needed, no AI complexity required—just a streamlined process that solved the real problem.
This validation process saved them months of development time and tens of thousands in development costs. More importantly, it gave them real market feedback that shaped a much stronger product strategy.
The manual approach also revealed something unexpected: the most valuable part of their service wasn't the technology—it was the curation and quality control that came from human oversight. This insight became their competitive advantage when they eventually did build technology to scale.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Technology constraints aren't the real constraint anymore. With AI and no-code tools, anyone can build complex systems quickly. The real constraint is knowing what to build and for whom.
Manual validation beats automated assumptions. Manually facilitating your core value proposition teaches you things no amount of user testing on a built product can reveal.
Speed to market means speed to validation, not speed to building. Getting market feedback in days or weeks is more valuable than launching a full product in months.
Your first MVP should test demand, not functionality. You can build amazing functionality, but if nobody wants it, the functionality doesn't matter.
Manual processes reveal the real value proposition. When you do things manually first, you understand what parts actually matter to users versus what seems important to you.
No-code tools are for scaling validation, not replacing it. Use platforms like Bubble after you know what to build, not to figure out what to build.
The best MVPs often aren't products at all. They're processes, services, or manual implementations that prove the underlying business model works.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups:
Test core workflows manually before building automation
Use simple tools (forms, spreadsheets) for initial validation
Focus on proving users will pay, not just use
Build audience before building product
For your Ecommerce store
For ecommerce businesses:
Test demand with pre-orders or waiting lists
Manually fulfill initial orders to understand operations
Validate pricing and positioning before building inventory
Use existing platforms before building custom solutions