A useful MVP focuses on the assumptions you need to test. Budget and timeline depend on the scope, integrations and reliability requirements. Agreeing those early helps avoid building features that do not contribute to the first validation milestone.
Agentic AI workflows have collapsed that trade-off. A senior engineer driving Claude, Cursor and a disciplined agent setup now delivers real, production-standard code at velocities that used to be impossible. The judgment is still senior — the execution is accelerated by AI, with the pace depending on scope, integrations and review requirements.
The result: US and Canadian startups can now afford to validate ideas in code rather than in slides — with a real chance of hitting product-market fit before the first round runs out.