One Assumption
Tepia anchors each MVP to the single belief that would end the business if false, and writes it down before design begins.
Read: MVP App Development for StartupsTepia plans MVPs around one risky assumption, one core job and a success threshold agreed before design starts, then builds the smallest release that tests it. Most MVPs use React Native or Flutter for a single cross platform codebase, with manual back office steps standing in for automation until the idea is proven.
A good MVP plan names one user, one job and one number, then builds only what it takes to measure that number.
Tepia anchors each MVP to the single belief that would end the business if false, and writes it down before design begins.
Read: MVP App Development for StartupsTepia often builds a simple admin panel so staff can run matching or approvals by hand until the idea earns automation.
Read: App Development for StartupsSuccess is a number agreed upfront, such as completed bookings per week, so results cannot be reinterpreted after launch.
Read: How to Choose an MVP Development PartnerSignup, first core action and repeat action events are wired before the first user arrives, so the review has real data.
Figures Tepia uses when helping teams plan an MVP.
In its review of 431 VC backed startups that shut down since 2023, CB Insights found 43 percent cited poor product market fit.
Apple says App Review typically handles 90 percent of submissions in under 48 hours, so an MVP launch date rarely slips on review.
Tepia clients report apps averaging 4.5 stars on the App Store and Google Play, and early reviews shape later downloads.
A minimum viable product is not the full app with features removed. It is the smallest release that tells you whether a specific belief about your market is true. Founders who skip that framing tend to ship a thin version of every roadmap item, then cannot tell which part worked. Tepia asks one question before anything else: what has to be true for this business to work, and how will we know within a few months?
Good answers are specific. Clinic managers will send patients a link, and at least half will finish it before arrival. Contractors will post a job and accept a bid within a day. Office teams will reorder supplies from a phone instead of by email. Each names a user, an action and a threshold, which makes the MVP testable.
The plan then works backward from that test to the fewest screens, integrations and back office tools needed to run it. Tepia keeps that test visible on every planning document, so when a new feature request arrives the team can ask one question: does this help us learn the answer sooner?
Tepia uses a comparison like this in Discovery to pressure test a plan before design starts.
| Planning question | Weak answer | Strong answer |
|---|---|---|
| Who is the first user? | Small businesses | Owners of dental groups with two to five locations in Texas |
| What job does the MVP do? | Manage operations | Confirm tomorrow’s appointments by text and fill cancellations |
| What proves it worked? | Users like it | 30 percent of cancellations refilled within 4 hours over 8 weeks |
| What is done by hand? | Nothing, everything automated | Staff approve each refill match from an admin panel |
| What is out of scope? | To be decided | Billing, reporting and rollups across locations |
| When do we decide? | When it feels ready | A fixed review date with the threshold agreed upfront |
The strong column reads narrow on purpose. A narrow MVP that clearly passes or fails teaches more than a broad one that produces ambiguous data.
Tepia runs MVPs through the same six phases as larger builds, compressed and focused on the test. Arriving with research, designs or a requirements document shortens Discovery.
A focused MVP often lands near the short end of Tepia’s usual ranges: Discovery 1 to 3 months, development and QA 2 to 6 months, launch about a month. See our process.
The first weeks after launch are for reading data, not adding features. Tepia reviews the funnel with you: how many users reached the core action, how many repeated it, and where the rest dropped off. Session recordings and a handful of follow up interviews usually explain the numbers.
Then make the call you agreed to make. If the threshold was met, the next release replaces manual steps with automation and adds the features that kept coming up in interviews. If it missed, decide whether the job, the user or the channel was wrong before writing more code. Tepia’s app evolution consulting exists for exactly this stage.
More reading: MVP app development, how to write an app requirements document, marketplace MVPs and digital health MVPs. Talk to Tepia about your idea.
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