AI Can Generate a SaaS Prototype. Building the Product Still Takes Months.

Short summary

Building a SaaS product with AI coding tools like Claude accelerated prototyping but the product still took over three months to ship. The hardest parts weren't code generation but architectural decisions around privacy, cost economics, and edge-case handling. The author shifted from an LLM-first approach to deterministic matching with AI as an optional fallback, resulting in a faster, cheaper, and more privacy-preserving product.

• •AI tools sped up coding but product decisions around privacy, cost, and edge cases took months
• •LLM-first approach for form-filling was too expensive and exposed sensitive user data to external providers
• •Final architecture uses deterministic local matching first with AI only as optional fallback

Generated with AI, which can make mistakes.