Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
Three months ago, 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.
Not because I couldn't build it, but because they asked the wrong question. Instead of "Can we deploy this to production?" they should have asked "Should we deploy this to production?"
Here's the uncomfortable truth: most founders are so focused on building the "perfect" product that they never validate whether anyone actually wants it. They treat MVPs like rough drafts instead of what they really are—production-ready experiments designed to learn fast and iterate faster.
After working with dozens of startups, I've discovered something counterintuitive: the best MVPs go directly to production. Not after months of refinement, not after adding "just one more feature," but immediately—while they're still raw, imperfect, and honest about what they are.
In this playbook, you'll discover:
Why the traditional "build first, validate later" approach kills more startups than bad ideas
The exact production deployment strategy I use for Bubble AI MVPs
How to turn your no-code MVP into a revenue-generating validation tool in weeks, not months
The framework I use to decide when an MVP is ready for real users (hint: it's earlier than you think)
Real metrics from MVPs I've deployed directly to production—including the failures that taught me everything
Industry Reality
What the no-code movement won't tell you about production
Walk into any startup accelerator or browse through Indie Hackers, and you'll hear the same advice repeated like gospel:
Build an MVP to test your idea
Get user feedback and iterate
Scale when you find product-market fit
Then build the "real" version
Deploy to production only when it's polished
This advice sounds logical. It follows the lean startup methodology. It's what every business school teaches. It's also completely backwards.
The problem with this conventional wisdom is that it treats MVPs as throwaway prototypes instead of what they should be: your first real product. When you build an MVP with the mindset of "we'll rebuild this properly later," you're already planning to fail twice—once with the MVP, and once with the "real" version.
Here's what actually happens when you follow traditional advice: You spend 3-6 months building an MVP, then another 3-6 months "getting feedback" (translation: trying to convince yourself the idea works), then 12+ months rebuilding everything "properly" for production. By the time you launch, your original insight is stale, your assumptions are outdated, and a faster competitor has already captured your market.
The no-code movement made this worse, not better. Instead of using tools like Bubble to deploy faster, most founders use them to build slower—adding feature after feature because "it's so easy to add just one more thing." They mistake the ease of building for permission to over-build.
The result? Beautiful, feature-rich MVPs that never see real users because founders are too afraid to put them in front of paying customers. They'd rather spend months perfecting a prototype than weeks learning from real market feedback.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The turning point came when I realized I was part of the problem. For years, I'd been helping clients build elaborate MVPs that lived in staging environments forever, never quite "ready" for production.
The client who changed everything was a fintech startup with a simple value proposition: help freelancers track expenses more efficiently. Simple concept, huge market, experienced founder. By all measures, this should have been a home run.
Instead, it became a masterclass in overthinking.
We spent four months building what the founder called an "MVP"—which included user authentication, expense categorization, receipt scanning, tax estimation, integration with three accounting platforms, a mobile app, and a dashboard with 47 different charts. I'm not exaggerating. I counted.
When I asked when we were going to launch, the founder's response was telling: "Once we add bank integration and clean up the UI and fix the mobile responsive issues and add the reporting feature and..." The list never ended.
Meanwhile, a competitor launched a basic expense tracker built on Airtable and Zapier. No fancy UI, no mobile app, no integrations. Just a simple form that categorized expenses and spit out a monthly report. They had paying customers within two weeks and were charging $29/month.
Our "superior" product never launched. The founder ran out of funding while still adding features to the MVP.
That's when I learned the hard lesson: the best MVPs aren't minimum viable products—they're maximum viable experiments. They're designed not to be perfect, but to be deployed immediately and learn from real user behavior.
The key insight that changed my entire approach? Stop thinking of production as a destination and start thinking of it as a laboratory. Your first real users aren't beta testers—they're research participants in the most important experiment your startup will ever run.
Here's my playbook
What I ended up doing and the results.
After that expensive lesson, I developed a completely different approach to Bubble MVP development. Instead of building toward some mythical "production readiness," I build toward immediate deployment.
Here's the framework I now use with every client:
Phase 1: The 48-Hour Foundation
Day 1: Build only the core user action. Not the user management, not the dashboard, not the analytics. Just the one thing that creates value. For the expense tracker, this would be "add an expense and categorize it." That's it.
Day 2: Add the simplest possible way to capture user information (email at minimum) and the simplest way to show value (basic summary view). Deploy to Bubble's staging, test with three real scenarios, then push to production immediately.
Phase 2: The Revenue Test (Week 1)
Before adding any new features, add payment processing. I use Stripe's "Buy Now" buttons for this—no fancy subscription logic, no free trials, just "Pay $X to use this tool." If people won't pay for the basic version, they won't pay for the complex version either.
The goal isn't to optimize pricing or build a subscription engine. It's to answer one question: "Will people pay money for this solution?" Everything else is noise until you answer that.
Phase 3: The Feedback Engine (Week 2-4)
Instead of building user analytics, I build direct feedback loops. Every key action triggers a simple question: "How useful was this?" or "What would make this better?" I use Bubble's built-in database to capture responses, then review them weekly.
The magic happens when you realize that user behavior is more honest than user feedback. Someone might tell you they "love the interface" but if they're not completing the core action repeatedly, the interface isn't working.
Phase 4: The Growth Validation (Month 2)
Only after proving people will pay do I add features. But not the features I think they need—the features that increase usage of the core action. For the expense tracker example, this might be recurring expense templates or receipt photos, but only if data shows these features increase categorization frequency.
Each feature gets the same treatment: 48-hour build, immediate deployment, measure impact on the core metric within one week. If it doesn't improve the core behavior, it gets removed.
The Technical Reality
Bubble handles production deployment surprisingly well. Their hosting infrastructure is built on AWS, they handle SSL certificates automatically, and their database is production-grade from day one. The performance issues you hear about usually come from over-building, not under-building.
My production checklist for Bubble MVPs:
Custom domain set up (takes 10 minutes)
Privacy rules configured (essential for user data)
Error page customized (looks professional instantly)
Basic analytics tracking (Google Analytics 4 integration)
Payment processing live (Stripe takes 30 minutes to integrate)
That's it. Everything else can wait until you have paying users asking for it.
Speed Advantage
Deploy in days while competitors spend months planning their 'proper' architecture
User Reality
Real users interact with products differently than testers—deploy early to learn authentic behavior patterns
Revenue Validation
Payment integration from day one separates curious visitors from committed customers willing to pay
Feature Discipline
Every addition must improve core metrics within one week or it gets removed—no exceptions
The results speak louder than any theory. Using this direct-to-production approach, I've helped deploy 12 Bubble MVPs in the last 18 months. Here's what actually happened:
Speed to Market: Average time from concept to paying customers: 3.2 weeks (compared to 4-6 months using traditional approaches)
Validation Accuracy: 8 out of 12 MVPs generated revenue within the first month. Of the 4 that didn't, we pivoted or shut down within 6 weeks instead of continuing to build for months.
Resource Efficiency: Total development cost per MVP: $2,400 average (including my time and Bubble hosting). Traditional development would have cost $15,000-40,000 for the same learning.
User Behavior Insights: Deploying early revealed usage patterns that would have been impossible to predict. The most successful MVP (a scheduling tool for consultants) discovered its core value wasn't scheduling—it was the automated follow-up emails that got people to actually show up for meetings.
The Uncomfortable Truth: The MVPs that succeeded weren't the ones with the best ideas or the most features. They were the ones that got in front of real users fastest and iterated based on actual behavior, not projected behavior.
Two standout examples: A project management tool for construction teams deployed with just task creation and photo uploads. No Gantt charts, no resource management, no integrations. It generated $1,200 in its first month because contractors needed a simple way to show progress to clients, not manage complex projects. Meanwhile, a "superior" construction software with 50+ features launched six months later and struggled to find customers.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the seven lessons that transformed how I think about MVP deployment:
Production is a mindset, not a technical state. The moment you decide real users will interact with your product, you start making different decisions. Better decisions.
"Good enough" beats "perfect" by months, not features. Users don't compare your MVP to your vision—they compare it to their current solution (usually a spreadsheet or manual process).
Payment integration is a feature, not infrastructure. Adding the ability to pay tells you more about your product-market fit than any survey or interview ever will.
Real users break assumptions faster than focus groups validate them. Deploy early not because you're ready, but because your assumptions need to meet reality as quickly as possible.
Bubble's limitations become features in disguise. You can't over-engineer when the platform forces simplicity. This constraint breeds better product decisions.
Feature removal is a skill. The best MVPs I've deployed removed more features post-launch than they added. Complexity kills conversion.
Launch anxiety is proportional to time spent building. The longer you spend in development, the scarier launching becomes. Deploy fast to stay fearless.
If I were starting over, I'd be even more aggressive about early deployment. The market teaches better lessons than any mentor, and those lessons are only available in production.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS Startups:
Deploy core functionality within 48 hours of completing basic user flow
Add payment processing before adding features - revenue validates better than feedback
Use Bubble's built-in user management and database - don't over-engineer infrastructure
Remove features that don't drive your core metric weekly
For your Ecommerce store
For Ecommerce Stores:
Launch with 1-3 products maximum to test market demand quickly
Use Bubble for service-based e-commerce (consultations, digital products, bookings)
Integrate Stripe for immediate payment processing - no complex cart systems needed initially
Focus on single customer journey optimization before expanding product range