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.
But here's the thing - it wasn't because I couldn't deliver. It was because I've learned something that most founders miss: your first MVP should take one day to build, not three months. Yes, even with AI and no-code tools like Bubble.
This experience taught me a fundamental truth about MVPs in 2025: the constraint isn't building anymore - it's knowing what to build and for whom. While everyone's obsessed with the latest no-code features, they're missing the real opportunity.
Here's what you'll learn from my contrarian approach:
Why I recommend starting with manual validation before touching Bubble
The 3-layer validation system I use before building any AI MVP
How to test market demand in days, not months
When to actually start building (spoiler: it's later than you think)
My simple framework for AI MVP templates that actually convert
If you're planning to build an AI MVP on Bubble, this might save you months of wasted effort. Let me show you why distribution and validation come before development - always.
Industry Reality
What every founder believes about MVPs
The no-code revolution has created a dangerous myth: if you can build it fast, you should build it first. Every startup guru preaches the same gospel - "ship fast, iterate faster." Bubble's marketing amplifies this with promises of "build anything in hours."
Here's what the industry typically recommends for AI MVPs:
Start with the tech - Pick your AI APIs, set up your Bubble workflows, integrate everything
Build core features first - Create the main functionality, add AI integrations, make it work
Launch and iterate - Release to users, gather feedback, improve based on usage
Scale with data - Use analytics to optimize, add features based on user behavior
This approach sounds logical because it's borrowed from traditional software development. The problem? It treats your MVP like a product when it should be treated like a hypothesis.
The reality is that most "MVP failures" aren't technical failures - they're market validation failures. Founders spend months perfecting their Bubble workflows while never validating if anyone actually wants what they're building.
Even worse, the ease of no-code tools creates a false sense of progress. You feel productive because you're building, but you're often building the wrong thing for the wrong people. By the time you realize this, you've invested weeks or months in code that nobody wants.
This conventional wisdom exists because it feels productive and measurable. But it skips the most important step: proving that your idea solves a real problem people will pay for.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
When that marketplace client came to me, they had all the classic symptoms. No existing audience. No validated customer base. No proof of demand. Just an idea, enthusiasm, and a budget for a complex two-sided platform.
Their core statement revealed everything: "We want to see if our idea is worth pursuing."
Here's what they wanted me to build: a platform connecting service providers with customers, complete with user profiles, booking systems, payment processing, reviews, and automated matching algorithms. In Bubble, this would mean dozens of data types, complex workflows, and multiple user interfaces.
The project scope included:
User authentication and profile systems
Service provider onboarding flows
Customer search and booking interfaces
Payment integration and escrow systems
Review and rating mechanisms
AI-powered matching algorithms
They'd heard about Bubble's capabilities and new AI integrations. They weren't wrong - technically, you can build all of this. The platform is powerful enough to handle complex applications.
But I've seen this movie before. Beautiful, functional platforms with zero users. Perfect workflows that nobody uses. Sophisticated AI features solving problems that don't exist.
So instead of taking their money and building what they asked for, I asked them a simple question: "How do you know people want this?"
Their answer was telling: "Well, we think there's a gap in the market." Classic founder assumption. No customer interviews. No validation experiments. No proof of demand.
That's when I knew I had to say no - and show them a better way.
Here's my playbook
What I ended up doing and the results.
Instead of building their platform, I walked them through my validation framework. This system has saved me and my clients countless hours and thousands of dollars by proving (or disproving) ideas before writing a single line of code.
Layer 1: The One-Day Validation Test
I told them to spend exactly one day testing their hypothesis. Create a simple landing page - not in Bubble, just a basic page explaining the value proposition. Then:
Write compelling copy explaining the problem they solve
Add an email signup for "early access"
Drive traffic through their personal networks
Measure signup rate and engagement
If they couldn't get 50 people excited about a landing page, why would those same people use a complex platform?
Layer 2: Manual Market Validation (Week 1-4)
Before touching Bubble, I recommended they manually create their marketplace:
Reach out to potential service providers via LinkedIn and email
Find potential customers through social media and forums
Manually match them via WhatsApp and email
Handle payments through simple tools like PayPal
This approach forces you to understand every part of your business model. You learn what customers actually want, how providers really work, and where the friction points exist.
Layer 3: Process Automation (Month 2)
Only after proving demand manually should you consider building automation. And even then, start small:
Use Airtable or Google Sheets for your database
Create simple forms for intake
Use Zapier for basic workflow automation
Handle payments through existing solutions
When you finally move to Bubble, you'll know exactly what to build because you've manually operated every process. Your data types will reflect real user needs. Your workflows will solve actual pain points. Your AI features will automate proven processes, not theoretical ones.
The key insight: Your MVP should be your marketing and sales process, not your product. Distribution and validation come before development.
Process Design
Validate demand manually before building anything technical
Market Research
Use direct customer contact to understand real pain points
Automation Strategy
Build only proven processes - start with spreadsheets and forms
Technical Planning
Let manual operations inform your Bubble architecture and workflows
The client who originally wanted the complex marketplace? They followed my framework and discovered something interesting. After manually connecting 20 service providers with customers, they realized their original idea was solving the wrong problem.
Instead of building a broad marketplace, they pivoted to a specialized booking system for a specific niche. By the time they came back to me for technical development, they had:
50 validated service providers ready to use the platform
200+ customers who had already used their manual service
Clear understanding of essential features vs nice-to-haves
Proven unit economics and pricing model
When we finally built their Bubble application, it took 3 weeks instead of 3 months because we knew exactly what to build. More importantly, it launched with existing demand rather than hoping to create it.
This approach doesn't just save development time - it fundamentally changes your success probability. You're building for known demand rather than assumed demand.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons I've learned from applying this validation-first approach across multiple client projects:
Manual operations reveal hidden complexities - Every marketplace has edge cases you won't discover until you manually handle transactions
Customer language is different from founder language - Direct interaction shows you how customers actually describe their problems
Distribution is harder than development - Getting your first 100 users is 10x harder than building the platform
Feature creep kills MVPs - When you validate manually first, you focus only on essential workflows
AI should automate proven processes - Don't use AI to create new workflows - use it to scale existing ones
No-code doesn't mean no-strategy - Bubble makes building easy, but it doesn't make building right any easier
Speed to market beats speed to code - You can test most business models in days without writing code
The biggest mistake I see founders make is treating their MVP like a product launch when it should be treated like a learning experiment. Bubble is incredibly powerful, but power without direction is just expensive distraction.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups building AI MVPs:
Start with customer interviews before touching Bubble
Use manual processes to validate your AI automation ideas
Focus on one specific use case rather than building a platform
Test pricing and willingness to pay before development
For your Ecommerce store
For e-commerce businesses exploring AI MVPs:
Validate personalization ideas with manual curation first
Test recommendation logic with spreadsheets before AI
Use existing tools (Shopify apps) before custom Bubble development
Prove demand for AI features through manual delivery