Build Your MVP, or Rescue the One You Shipped

What is MVP development?

MVP development is building the smallest version of a product that real users can use, so you can validate demand before committing to a full build. A good MVP ships fast on production foundations, with a clean data model, real authentication, and secure APIs, so the version that proves the idea can also grow into the product.

An MVP earns its place by putting a real product in front of real users quickly, then proving what to build next. We do two things. We build that first version with production foundations, and we rescue the version you already shipped when it starts to strain. Across 250+ products shipped for clients in 13+ countries, most of them in the USA, that first version is where the real learning happens.

When does an MVP need a rescue?

An MVP needs a rescue when the prototype holds in a demo but real users, real data, and real security expose the gaps. Plenty of teams ship a working MVP on a no code tool like Supabase, Lovable, Xano, or WeWeb, or vibe code one with Cursor, Claude Code, Bolt, or Replit, then hit the same wall.

That is the point where we come in. We harden what works, replace what does not, and take it to production. Every engagement starts with an architecture and security audit, so the plan is grounded in your real stack and data rather than a template. From there we work in priority order, fixing what puts the product at risk first, then scaling what holds. You end up with a maintainable codebase you own, whether we build it from scratch or take over what someone else started.

How much does an MVP cost?

At our published estimate ranges, an MVP costs 15,000 to 50,000 dollars, and a growth build that takes a validated product to scale runs 50,000 to 150,000 dollars, at a blended rate of 25 to 50 dollars per hour. Every number is an estimate range scoped against your product, never a fixed bid before discovery.

That rate sits well below the 150 to 300 dollars per hour US specialists typically bill for comparable scope, which is why many US founders build the first version with us and keep the same team for the scale up. Enterprise programs that grow out of a successful MVP run 150,000 to 300,000 dollars and up, on the same estimate first model as our custom software development work.

How long does an MVP take?

Most MVPs reach a usable first release in a few weeks, and a typical MVP ships in 8 to 12 weeks end to end. We build with AI assisted development and proven foundations rather than starting from scratch, so sprints run about 30 percent faster and the exact timeline is agreed against scope up front.

Roughly 80 percent of our production code is AI generated and engineer reviewed, verified by our internal team, which is what makes those timelines possible without giving up review discipline. Our AI native development page explains how that delivery model works. Speed never comes from skipping foundations. It comes from senior engineers spending their time on architecture and review rather than boilerplate.

How does a vibe coded prototype reach production?

We take the prototype you already have and make it real. We audit security and data access first, then rebuild the parts that will not scale, add tests and error handling, wire up CI and monitoring, and hand you documented code you own. The path is the same whether you vibe coded it or built it on no code.

Vibe coding means describing what you want to an AI tool and shipping what it generates. Cursor, Claude Code, GitHub Copilot, Bolt, and Replit make it fast to get a working prototype, and founders lean on them heavily. In the Y Combinator Winter 2025 batch, a quarter of startups shipped codebases that were about 95% AI generated, according to YC CEO Garry Tan.

A demo and a product are different problems. A 2025 Veracode study of AI generated code found that 45% of samples failed security tests and introduced OWASP Top 10 flaws, with no improvement from newer or larger models. A separate scan of more than 5,600 vibe coded apps by Escape.tech found over 2,000 vulnerabilities and more than 400 exposed secrets, most of them from keys left in the frontend, missing access control, and Supabase row level security that was never turned on. The Stack Overflow 2025 survey adds that 66% of developers name AI output that is almost right but not quite as their top frustration.

Our guide to vibe coding risk in startups covers the patterns that keep AI assisted code maintainable, and if you built on Supabase, our Supabase RLS security checklist and guide to whether Supabase is production ready are the exact checks we start from.

What your AI built app is usually missing. The checklist we run on every rescue audit, and the gap between a demo and a product.

• Concurrent writes. Two users acting at once corrupt state unless transactions and locking are designed in.
• Real authentication and role based access. Working login is not access control. Who can read and change which records must be enforced server side.
• Input validation and rate limiting. Untrusted input and unthrottled endpoints are the two doors attackers try first.
• Secrets management. API keys belong in server side configuration, not in frontend code where scanners find them.
• Backups and data persistence. A restore that has actually been tested, not just a database that exists.
• Error handling, logging, and monitoring. Production fails quietly without them, and you find out from customers.
• CI, tests, and a staging environment. The difference between shipping changes and gambling them.