What an MVP budget is actually spent on
Founders tend to picture MVP cost as the price of writing code. In practice a focused build divides roughly into deciding what to build, implementing the core journey, and creating the launch surface: pricing, onboarding, analytics and the payment path. That final part is frequently treated as optional even though it determines whether launch teaches you anything.
Why scope moves the number more than anything else
Every additional user journey adds roughly one and a half weeks before the interaction and testing overhead is counted. Two journeys instead of one rarely costs exactly twice as much, because the states between them also need to work together.
This is why the single most valuable hour in any MVP project is the one spent cutting scope. It is also why the DIY route is not automatically the cheapest: AI tools remove much of the cost of typing code, not the cost of building the wrong thing quickly. See product validation for how to reduce that risk before committing the build budget.
Where AI features change the maths
Simple LLM calls add relatively little when the data and workflow are straightforward. Retrieval over your own data takes longer because the work is in data quality, permissions and evaluation. Agentic workflows add more again because each tool action, failure path and permission needs to be designed and tested. The budget should include the evaluation set and cost model, not just the feature itself.
Hidden costs the quote usually omits
- —Hosting, database and model usage — modest at MVP scale, but not zero.
- —Design assets, domain, email infrastructure and legal pages.
- —Analytics tooling and the time to define an activation funnel properly.
- —Post-launch iteration after real users arrive.
- —Your own time — usually the largest real cost on the DIY route, and always excluded from the number.
If you want a real quote rather than a planning range, the MVP development page sets out exactly what a focused build includes.
If you are a non-technical founder and want the build done for you, start with AI app development for non-technical founders. If you would rather scope it yourself first, read how to build an MVP. If the product already exists and the question is what to fix next, that is an AI product consultant conversation, or use the Lovable app review if you already have an AI-built prototype and need to know whether it is ready for customers.