An MVP should answer a business question through a working product. Can a customer complete a useful task? Will a team adopt a better way of working? Can the service deliver what people are willing to pay for? A long feature list makes those questions harder to answer.
Start with one complete journey
Choose one user and one outcome. For a booking product, that might be finding an available appointment, reserving it and receiving confirmation. A dashboard, referral scheme and loyalty programme can wait if they do not help complete that journey.
Write the journey as a sequence of actions. Include the awkward steps: no availability, an expired session, a failed payment or a cancellation. These are part of a usable first release, even when the visual design is deliberately simple.
Separate essential behaviour from convenient automation
A first release can use manual operations behind the scenes. You might review applications yourself before building an approval engine. Make that choice explicit: who performs the work, how long it takes and what volume would make automation worthwhile.
Avoid postponing foundations that are expensive to retrofit. Access permissions, data ownership and a way to recover from failed operations need attention from the beginning. Fewer features should mean a smaller promise, not an unreliable one.
Test the riskiest dependency early
List every external service the product depends on. Check whether it provides the access, data and behaviour your workflow requires before designing the whole experience around it. A prototype using representative data can uncover limits that a polished mockup cannot.
For AI features, define acceptable output and the human review step. Test with difficult examples as well as ideal inputs. Keep the underlying task usable when a provider is slow or unavailable.
Agree what done means
Replace “users can book” with observable acceptance criteria: an available slot can be reserved once, the customer receives confirmation and an administrator can find the booking. This gives the team a shared basis for estimating and reviewing the work.
Keep a separate list for later ideas. Before adding one to the first release, ask which current assumption it tests or which essential task it enables. If the answer is neither, it probably belongs in a later iteration.
Plan the first learning cycle
Decide what you will observe after release: completed tasks, abandoned steps, support requests and reasons people stop using the product. Combine those observations with direct conversations. A launch produces evidence; the next development decision should respond to it.