Why one LLM isn't enough: routing prompts across models without losing control
Model quality changes every month. Here's how we design routing, fallbacks and cost caps so your product never depends on a single AI vendor.
Most first products try to do too much. Founders worry that a small product will look unfinished, so they add accounts, settings, dashboards and integrations before anyone has proven they want the core thing. The result is months of build time and a launch that teaches very little.
Before we start any MVP, we run every proposed feature through five questions.
1. What's the one thing a user must be able to do?
Write it as a single sentence. Everything in version one should serve that sentence. If a feature doesn't, it waits.
2. What would prove this is working?
Pick a measurable signal: people completing the core action, coming back within a week, or paying. If you can't measure it, you can't learn from the launch.
3. Can this be manual for now?
Many features can start as a human doing the work behind the scenes. Automated onboarding can be a call. Automated reports can be a spreadsheet you email. Automate once you know it's needed.
4. Can we use something that already exists?
Authentication, payments, email, forms and analytics all have reliable off-the-shelf options. Building them from scratch rarely proves anything about your business.
5. What happens if we cut it?
If the honest answer is "nothing much" or "a few users would be slightly annoyed", cut it. You can add it back in a week if you're wrong.
Small doesn't mean throwaway
Cutting scope is different from cutting corners. The features you keep should be built properly, on an architecture that can grow. That's how you launch in weeks without facing a rewrite when customers arrive.
Planning a first product? See how our MVP development works.
