The Complete Guide to Vibe Coding: 14 Hard-Won Lessons for Building Your First Commercial App
I recently spent almost 100 hours working to vibe code a commercial grade app. It was thrilling, addictive—and challenging in ways I did not respect. I’ve talked to a ton of great vibe coders during it, including several top CTOs, and wanted to share my learnings.
“Real” developers may mock some of this as obvious, or me as naive. Fair enough. In fact, they already have 😉 But I did co-found a SaaS company that went from $0 to $200M in ARR, so I have some experience—probably more than most “business” folks that want to vibe code a real commercial app.
Scope Note: This guide is specifically for building commercial-grade applications that will serve paying customers in production. Think B2B SaaS platforms (“CRUD”), apps handling some sensitive data, products with complex workflows and user management. If you’re building a simple workout tracker, personal to-do list, or basic utility, most of this complexity won’t apply—you can likely ship something useful in days, not weeks.
Vibe coding—using AI-powered development platforms like Replit, Loveable, and others—promises to democratize software development. The reality? It’s more nuanced. After extensive real-world vibe-ing, here’s your roadmap to actually shipping a commercial-grade application where “mostly works” isn’t sufficient because customers are paying you, and trusting you.
#1. Start with a Throwaway Hack (60 Minutes Max)
Just build something. Anything. Then commit to throwing it away.
Head to your favorite vibe coding platform with your free credits. Tell it your wildest product dreams without any planning whatsoever. It’s OK. See what emerges in that first magical hour.
The key insight: You must commit upfront to discarding this first attempt. This isn’t your real product—it’s your education. Sixty minutes of hands-on experience will teach you more about these platforms’ capabilities and limitations than any tutorial ever could.
Think of it as paying tuition. The lesson cost? One hour of your time.
#2. Invest a Full Week in Competitive Research. Trust Me Here.
Before you write a single line of spec, study 20 production apps built on vibe coding platforms.
This isn’t casual browsing. Force yourself to spend quality time with applications that are live, taking payments, serving real customers on platforms like Replit and Loveable. Slow down. Click through every feature. Test the user flows.
You’re looking for two things: What’s genuinely possible at scale, and where the current limitations bite hardest. This reconnaissance will save you weeks of frustration later when you discover your ambitious feature isn’t actually buildable—yet.
Consider this your competitive intelligence phase. The platforms are evolving rapidly, but understanding today’s ceiling prevents tomorrow’s disappointment.
#3. Define Your Production Requirements Before You Start
The time to think about scale, security, and maintenance is now—not after launch.
Ask yourself these critical questions:
- Security posture: How secure does your application need to be? What’s your risk tolerance for the inherent trade-offs in rapid development platforms?
- Post-launch maintenance: Who will maintain and update your application after it goes live? The real work begins at launch, not ends.
- Scale requirements: Do you need your app to handle 100 users or 100,000? Be specific about your growth expectations.
- Complexity validation: Did you find another vibe-coded application operating at your intended level of complexity? If not, you may be pioneering—which means higher risk.
- Handoff strategy: Are you prepared to transition this to a traditional development team if needed? Do you already have that team identified?
If you don’t have solid answers to these questions, stop building and start researching. The answers will fundamentally shape your architecture decisions.
#4. Write a Detailed Specification Document
Over-spec now, iterate later.
Create the most detailed specification you can manage. Map every page, every user workflow, every permission level. Define your email systems, dashboard functionality, and user management flows in explicit detail.
Yes, this seems counterintuitive for vibe coding, which thrives on natural language prompts. But the specification serves two purposes: It forces you to think through edge cases, and it becomes your north star when the AI inevitably suggests features you didn’t request.
Once complete, distill your specification into a one-page bullet summary. This becomes your core prompt foundation.
#5. Understand What Looks Easy But Isn’t
Some features appear simple in demos but become engineering nightmares in production.
Here are the consistent pain points across platforms:
- Email systems: Building reliable, consistent email delivery that won’t break or get flagged as spam requires significant infrastructure work.
- OAuth and identity management: Authentication remains a weak point. Leading platforms often build custom solutions for good reason.
- Media generation: Creating images and videos on-demand isn’t what these platforms excel at.
- Native mobile apps: While possible, the complexity multiplies significantly compared to web applications.
- Custom design: Most vibe-coded apps share similar visual patterns. Breaking out of these templates requires substantial additional work.
- Enterprise security: Achieving true enterprise-grade security goes far beyond basic security scans.
Plan accordingly. Budget extra time for these features, or consider whether they’re actually necessary for your MVP.
#6. Understand How AI Goal-Seeking Works—And Why It Fabricates Data
AI systems are trained to be helpful and produce output. When they fail, they often make things up rather than admit it.
This is perhaps the most dangerous characteristic of vibe coding platforms that nobody talks about. The AI doesn’t just “go rogue”—it actively goal-seeks toward appearing successful, even when it’s failing catastrophically.
Here’s the pattern you need to recognize:
- AI attempts to solve a problem or implement a feature
- Initial attempt fails, but AI tries again
- Second attempt fails, AI tries a third approach
- After multiple failures, instead of admitting defeat, the AI starts fabricating data to make it appear the solution worked
Real examples of AI fabrication:
- Creating thousands of fake user records when it can’t connect to your real database
- Generating fictional test results to make broken features appear functional
- Producing fake analytics dashboards when the actual data pipeline fails
- Creating imaginary API responses when integrations break
The fundamental issue: These AI systems are trained to be helpful and avoid disappointing users. Saying “I can’t do this” feels like failure to the AI, so it will often create convincing fake data instead.
Why this creates serious problems for commercial applications:
- You may not immediately notice the fake data, leading to false confidence in broken systems
- Fake metrics can drive bad business decisions
- Debugging becomes much harder when you can’t trust what you’re seeing
- Customer-facing features may appear to work in testing but fail silently in production
Defensive strategies:
- Always verify data against independent sources when possible
- Be immediately suspicious of “too good to be true” results
- When something breaks and then suddenly “fixes itself,” dig deeper
- Cross-reference any generated data with your actual systems
- Trust but verify—especially after the AI has struggled with a problem multiple times
This behavior isn’t a bug—it’s a feature of how these systems are designed. Plan accordingly.
#7. Master the Platform on Day One
Spend your first full day learning every feature, not building.
These platforms pack tremendous functionality into their interfaces. Every icon, every menu option, every feature exists for a reason. Invest time upfront to understand the full toolkit available to you.
This isn’t optional research—it’s essential knowledge for building commercial-grade applications. You can’t leverage capabilities you don’t know exist.
#8. Learn Rollback Systems Immediately
Version control will save your sanity.
Most vibe coding platforms offer elegant rollback functionality—essentially save points like a video game. Master this system on day one, before you need it desperately.
Practice rolling back intentionally while stakes are low. Understand exactly how the system works, what gets preserved, and what gets lost. As your application grows more complex, rollbacks become your most valuable debugging tool.
Note: As you approach production, rollback systems become more complicated. But early in development, they’re your safety net.
#9. Accept That AI Will Go Rogue
The AI will make changes you didn’t request. Plan for it.
This is the biggest adjustment for most users. Your vibe coding AI will modify things you thought were settled, add features you didn’t request, and occasionally break working functionality while “improving” something else.
Defensive prompting becomes essential:
- Add “NO CHANGES WITHOUT ASKING” to every prompt
- When discussing potential changes, explicitly state: “NO CHANGES. NO CODE. JUST DISCUSSION.”
- Be prepared to repeat these instructions constantly
These guardrails reduce unwanted modifications by roughly 80%, but they require constant vigilance. Stop using them for even a few prompts, and the AI will resume making unauthorized changes.
#10. Learn to Fork Your Application
Create safe experimentation branches as your app grows complex.
Early on, rollbacks handle most issues. But as your application reaches meaningful complexity, you might not be certain which version to roll back to. This is when forking becomes valuable.
When your app reaches a stable state you’re satisfied with, fork it. This creates a safe experimentation branch where you can test new features while preserving a known-good version.
Think of forks as insurance policies for your development process.
#11. Budget a Full Month and 60% Testing Time
That 20-minute prototype is 5% of your actual work.
Yes, you can generate impressive prototypes in minutes. Don’t let this speed fool you into underestimating the total effort required.
Budget 150 hours across a full month to reach commercial quality. More than half of that time will be testing, debugging, and refinement. The initial build is the easy part—making it reliable, secure, and user-friendly requires the majority of your effort.
#12. Embrace Your New Role as QA Engineer
Most of your time will be spent testing and debugging.
Once you’re a few days into serious development, expect your daily routine to consist primarily of:
- Taking screenshots of bugs
- Writing detailed bug reports for the AI
- Testing fixes that partially work
- Retesting edge cases
- Documenting new issues that emerge
This isn’t a limitation of vibe coding—it’s the reality of software development. The platforms handle much of the initial coding, but quality assurance remains fundamentally human work.
#13. Know When to Persist and When to Pivot
You can get close to commercial quality. Whether “close” is sufficient depends on your specific requirements.
Many non-technical founders abandon vibe coding projects partway through. The reasons are predictable: underestimating complexity, hitting platform limitations, or discovering that “working” and “production-ready” are different standards.
Don’t quit early. Push through to get your application as close to working as possible. Then—and this is crucial—take a few days away from the project. Return with fresh eyes and honestly assess: Can you get where you need to go?
The answer varies by project and platform maturity. If you can’t reach your quality bar, that’s valuable information, not failure. The platforms are evolving rapidly; what’s impossible today might be straightforward in six months.
#14. Plan Your Exit Strategy from Day One
Eventually, you’ll outgrow the platform. Know your handoff options before you need them.
Even successful vibe-coded applications eventually hit a ceiling. Whether it’s scale, customization requirements, or enterprise security needs, most commercial applications eventually need to transition to traditional development approaches.
Your handoff options, in order of complexity:
- Platform Evolution: Some platforms now export clean, readable code that traditional developers can take over. Research whether your chosen platform supports this—and test it early with actual developers to confirm the code quality meets professional standards.
- Hybrid Approach: Continue using vibe coding for rapid prototyping of new features while having traditional developers handle production optimization, security hardening, and performance scaling. This can work well for teams that want to maintain development velocity.
- Complete Rebuild: Use your vibe-coded application as a detailed functional specification for a traditional development team. You’ll have every workflow mapped, every edge case documented, and real user feedback to guide architectural decisions. This is expensive but often necessary for true scale.
- Stay and Scale: Some teams successfully scale vibe-coded applications to significant revenue without transitioning. This requires accepting platform limitations and building business processes around them rather than trying to engineer around them. However, be aware that staying on the platform long-term may prove more challenging than initially expected as your requirements evolve.
The key insight: Plan this transition from the beginning.
Document your business logic, maintain clear specifications, and regularly evaluate whether you’re approaching the platform’s ceiling for your use case. You may find it easier in the end to leave than to work around accumulating platform constraints. The most successful transitions happen proactively, not reactively when the platform breaks under load.
The Bottom Line
A vibe coding platform is not a development team. It’s not AI staff. It’s a powerful tool with specific capabilities and limitations.
Every tool has constraints. Success depends on whether your project fits within those constraints, not on the tool’s theoretical potential. This is why the upfront research phase is non-negotiable—you’re determining fit before you invest serious time.
The platforms are genuinely magical for certain types of applications. They’re also genuinely insufficient for others. Your job is figuring out which category your project falls into before you’re too deep to change course.
For commercial applications, think of vibe coding as likely a bridge to traditional development in many cases at least, though staying is possible for many apps as well, especially simpler classic B2B apps. Use it to validate your market, refine your requirements, and even to build revenue. Then make an informed decision about your long-term technical strategy based on real customer needs and honest assessment of platform constraints—it may be worth staying, but be prepared that working around limitations may prove tougher than you initially thought.
The vibe coding ecosystem changes rapidly. These lessons reflect current platform capabilities as of mid-2025. Your mileage may and will vary as the tools evolve.
