An MVP is the smallest working product that lets real users complete one core job so you can learn whether it is worth building further. Pick one user role and one core workflow, defer everything else, set up analytics from day one, and choose a team that gives you a written scope, milestone-based delivery and full ownership of the code.
Start with one user and one job
The most common MVP mistake is trying to impress investors, match competitors and express the whole vision in the first release. Instead, write down who the first user is and the single job they must be able to finish, such as booking, ordering, submitting a document or getting an answer.
A useful filter for every feature is: can we launch without this? If yes, it goes on a later list. Two or three user roles are usually enough at this stage.
A founder's guide to scoping a minimum viable product, avoiding overbuilding and choosing a development partner.
What to include and what to defer
Usually worth including: sign-in, the core workflow, a simple admin view, basic analytics and a way to collect user feedback. Billing deserves real care if you charge from day one, because a bug there costs revenue and trust.
Usually worth deferring: complex settings, many integrations, advanced reporting, multi-language support and infrastructure built for scale you have not reached yet. You can refactor after you have learned what users actually do.
If your MVP includes an AI feature
Keep it to one AI-powered workflow. For most first versions a hosted language model accessed through an API is enough; custom training is rarely the right first step. Add retrieval (RAG) only if the answers must come from your own documents.
Decide how you will judge whether the AI output is good enough before you build, log failures and usage so costs stay visible, and keep a human fallback for sensitive actions. Model pricing changes, so check current provider pricing rather than relying on old blog figures.
What to ask an MVP development team
Ask for a written scope with what is in and out, a named person who reviews your feedback, milestone-based delivery you can inspect, and code and cloud accounts that belong to you from the start. Ask for relevant examples and speak to references where possible.
Be cautious of the cheapest quote. Compare what each quote covers: design, testing, deployment, post-launch support and GST are often treated differently, which is why published price ranges vary so widely.
After launch
Treat the launch as the start of learning. Watch where users drop off, talk to the first users, and let evidence decide the next sprint rather than whoever is loudest. Plan some budget and time for fixes and iteration.
Common questions
It depends on scope. A single focused workflow can take weeks, while multi-role platforms, mobile apps and integrations take longer. A written scope is the only reliable way to estimate.
Many teams validate with a web app first because it is quicker to ship and update. Choose mobile first if the idea depends on device features such as the camera or push notifications.
You should. Agree in writing that the source code, design files and cloud accounts are yours, and that you have access to the repository throughout.
Yes, but keep it to one clear AI workflow, start with a hosted model, and plan evaluation and a human fallback.