MVP development for startups, built to survive Series A
Good MVP development for startups means shipping the smallest product that tests your riskiest assumption, on foundations you won’t have to rip out once it works. Many MVPs fail the second test: they get users, then the team spends months rebuilding instead of growing.
I help founders cut scope hard, pick a stack nobody will regret, and know exactly which corners are safe to cut. I lead the build hands-on, starting with a two-week sprint.
Cut scope until it hurts, then cut once more
The best scoping question I know is: what would we have to learn in the next three months for this company to still exist? Build only what answers it. Everything else goes on a list called “after we have users”.
In practice that usually means:
- One user type, not three. A two-sided product can often start with you manually playing one side.
- One core workflow, done properly. Not a dashboard, settings page and reporting suite around a workflow that doesn’t work yet.
- Manual operations behind the scenes. Approve signups by hand, send the weekly report from a script, issue refunds from the Stripe dashboard.
- No mobile app if a responsive web app will do. App store review adds a day or more to every release, and sometimes much longer.
- No admin panel beyond what your framework gives you for free.
Pick a boring stack
An MVP is the wrong place to try a new framework or database. Rails, Django or Laravel on PostgreSQL, deployed to a managed platform, gets a small team from zero to paying customers faster than anything novel – and you’ll be able to hire for it. Server-rendered pages with a little JavaScript beat a separate single-page app and API for most early B2B products.
Start with a monolith. Microservices in an MVP give you distributed-systems problems before you have a single customer. If you’re undecided between the big two Python and Ruby options, I compare them in Rails vs Django.
Corners you can safely cut
- Visual polish beyond clean and usable. A component library and sensible defaults are enough.
- Scale. One app server and one database will carry you a very long way. Don’t build for a million users you don’t have.
- Test coverage of UI details. Test the core workflow and anything touching money; skip the rest for now.
- Infrastructure as code, Kubernetes, multi-region. Use a managed platform and move later if you need to.
- Internal tooling. SQL queries and a shared notebook are fine for the first hundred customers.
Corners you must never cut
These are the decisions that turn an MVP into a rewrite. They cost little to get right on day one and a lot to retrofit:
- The data model. Think hard about the core entities and their relationships. In a B2B product, put an account or organization on every row from the start – adding tenancy later touches every query.
- Authentication. Use your framework’s built-in auth or a proven provider. Never roll your own password storage.
- Money. Store amounts as integers in minor units, never floats. Handle payment webhooks idempotently. Treat your payment provider as the source of truth for what was charged.
- Backups that restore. Test one before launch.
- Ownership. The code, the cloud account and the domain belong to the company, not the developer or agency.
SaaS MVP development and AI MVPs
For a SaaS MVP, the extra must-have is a clean line between your product and your billing provider: an entitlements record in your own database, updated from webhooks, so you can change pricing without rewriting features. Usage limits can wait; that line can’t.
For an AI MVP, the temptation is to make the model the product. Usually the product is the workflow around the model: getting the right data in, checking the output, and letting a person fix what’s wrong. Call a hosted model API rather than training anything, keep prompts in version control, log every input and output from day one, and set a hard monthly spend cap. Once real users arrive, LLM evaluation becomes the thing that tells you whether a change helped.
When you shouldn’t hire anyone to build it
If you can test your assumption with a landing page, a spreadsheet, a no-code tool or by doing the service manually for ten customers, do that first. It’s faster and cheaper than any developer. Bring in engineering once you know what people will pay for. If you’re a non-technical founder working out whether you need a cofounder, an agency or someone like me, start with technical cofounder alternatives.
Questions
How long does MVP development take?
With hard scoping, a focused MVP for a single workflow is usually a matter of weeks to a couple of months, not quarters. If an estimate runs past three months, the scope is almost always too big. The first two-week sprint should already put something usable in front of a real user.
Will we have to rebuild the MVP after we raise?
Not if the data model, authentication, money handling and ownership were done properly. You’ll refactor and extend constantly, which is normal. A full rewrite usually comes from a bad data model or an exotic stack nobody can hire for.
Should we build our MVP with no-code tools?
If it lets you test demand faster, yes. No-code is great for validation. Move to code when you hit a hard limit – complex logic, data ownership, cost at scale – and plan to rebuild rather than migrate, because no-code data models rarely translate cleanly.
Do you build MVPs alone or with a team?
It depends on scope. For a tight MVP I can make the architecture calls and write much of the core myself, often alongside a founder or one or two developers. For anything larger I lead the team doing the build and stay hands-on in the code.
Planning an MVP and want it to last?
Send me the one-paragraph version of the idea. We’ll cut scope together and use a two-week sprint to put the first real piece in front of users.
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