We had a call last month with a founder who had spent $180,000 and seven months building an MVP. Seven months. For an MVP. When we asked what was live, the answer was "we are almost done with the infrastructure." No users. No revenue. No product. Just infrastructure.
This is not a rare story. It is the most common story. And it is killing startups that otherwise have great ideas.
What an MVP Actually Is
The term "Minimum Viable Product" has been so thoroughly diluted that it has lost all meaning. So let us be clear about what it is. An MVP is the smallest thing you can ship that tests your core hypothesis with real users. That is it. It is not version 1.0 of your product. It is not the foundation for your platform. It is a test.
The purpose of an MVP is to answer one question: does anyone actually want this? Everything that does not directly contribute to answering that question is waste. Beautiful waste, perhaps. Technically impressive waste, certainly. But waste.
We wrote a full guide on how to build an MVP that lays out the process, but the core principle is simple: ship the minimum, learn the maximum.
The Overengineering Hall of Shame
Here are real examples from projects we have audited or taken over. Names are changed, but the patterns are painfully real.
The Kubernetes startup. Pre revenue SaaS company. Three engineers spent four months configuring a Kubernetes cluster with auto scaling, blue green deployments, and a service mesh. Their app had 12 beta users. A single $20/month server would have handled 10,000 times their load. When we rebuilt their deployment on a simple serverless stack, their infrastructure cost dropped from $2,400/month to $47/month. Their deploy time went from 25 minutes to 90 seconds.
The microservices marketplace. Two person team building a marketplace app. They architected 11 microservices before they had a single listing on the platform. Each service had its own database, its own CI/CD pipeline, its own monitoring. They were spending 80% of their engineering time on inter service communication and deployment orchestration. We consolidated the entire thing into a monolith. It shipped in six weeks.
The custom design system. A B2B tool where the founder insisted on building a custom component library from scratch before building the actual product. Buttons, form fields, modals, toasts, all custom. Three months of work that could have been replaced by any off the shelf UI library in an afternoon. The product itself never launched.
Why Smart People Overengineer
Overengineering is not a stupidity problem. It is an incentive problem.
Engineers optimize for what they know. If you have spent your career at companies with millions of users, you build for millions of users. It feels irresponsible not to. But building for scale you do not have is not responsible engineering. It is premature architecture, and it is one of the most expensive mistakes a startup can make.
Founders confuse building with progress. Shipping infrastructure feels productive. Setting up monitoring dashboards feels productive. Configuring a CI/CD pipeline with 14 stages feels productive. But none of it is progress if there is no product for users to use. Progress is measured by what users can do today that they could not do yesterday. Everything else is preparation.
Fear of rework drives over investment. "If we do not build it right the first time, we will have to rebuild it later." This is technically true and strategically irrelevant. If your hypothesis is wrong, you are going to throw away everything anyway. If your hypothesis is right, you will have revenue to fund the rebuild. Either way, the first version does not need to be the last version. The decision of when to rebuild vs. refactor is a bridge you cross when you have users, not before.
What Your MVP Actually Needs
Here is the short list. If something is not on this list, it probably does not belong in your MVP.
One core workflow that delivers value. Not five features. Not a platform. One thing that makes one user's life better. If you cannot articulate this in a single sentence, you are not ready to build yet.
Authentication, but simple. Email and password. Maybe Google OAuth. You do not need SSO, SAML, RBAC, or multi tenant isolation. You need users to be able to log in.
A database that stores the data. PostgreSQL handles nearly everything. One database, one schema, straightforward queries. You can shard later. You can add caching later. Right now you need to store and retrieve data without it falling over.
Basic deployment. Your code needs to get from your repository to a server. A simple CI/CD pipeline that runs tests and deploys on merge to main. That is it. No canary releases. No feature flags. No A/B testing infrastructure.
Error tracking. You need to know when things break. A single error tracking service is sufficient. You do not need a full observability platform.
This is the stack we use for most MVPs we build as part of our full stack development work: Next.js, Supabase, Vercel, and Sentry. It handles everything above, deploys in under 60 seconds, costs less than $50/month, and can scale to tens of thousands of users without changes. When you look at the modern startup tech stack, the convergence toward this kind of simplicity is not accidental.
The Speed Advantage Is the Only Advantage
For a startup, speed is not a nice to have. It is the only structural advantage you have over incumbents. A large company has more money, more engineers, more brand recognition, and more distribution. The one thing they cannot do is move fast. Every week you spend overengineering your MVP is a week you are surrendering your only advantage.
Consider the math. If you ship your MVP in 6 weeks instead of 6 months, you get 4.5 extra months of user feedback. That is 4.5 months of learning what works, what does not, what users actually want versus what you assumed they wanted. Compounded over the life of a startup, that learning gap is enormous. It is often the difference between finding product market fit and running out of money.
We have seen this play out with Traderly, where getting a working product in front of traders quickly was far more valuable than perfecting the architecture. The architecture evolved to match real usage patterns, not hypothetical ones.
The Rule of Thumb
Here is the test we apply to every technical decision during an MVP build: if removing this does not prevent users from experiencing the core value proposition, remove it.
Does removing Kubernetes prevent users from using the product? No. Remove it. Does removing the custom design system prevent users from using the product? No. Remove it. Does removing the microservices architecture prevent users from using the product? No. Remove it.
Does removing the ability to create an account, submit data, and see results prevent users from using the product? Yes. Keep it.
It really is that simple. But simple is not easy, especially when every engineering instinct tells you to build it "the right way." The right way for an MVP is the way that ships. Full stop.
When to Start Engineering for Real
Once you have users, once you have revenue, once you have validated that the thing you built is the thing people want, then you engineer. Then you add the monitoring. Then you think about scale. Then you consider whether your monolith needs to become services. Then you invest in a design system.
The sequencing matters. Validate first, engineer second. The vast majority of startups that fail never had a technology problem. They had a market problem that they discovered too late because they were too busy building technology nobody asked for.
If you are building an MVP and the timeline is measured in months instead of weeks, something has gone wrong. Talk to us. We will cut through the complexity and get your product in front of users before the runway disappears.