When I started building Codapult, I wasn't just trying to put authentication, billing, and a dashboard into a Next.js starter kit. I wanted a foundation that developers could extend with AI coding agents without gradually losing control of the architecture.
After building a production-oriented Next.js 16 SaaS boilerplate around that idea, a few lessons became clear.
1. Giving an agent access to the codebase isn't the same as giving it the right context.
An agent can read files and generate code, but it still needs to understand how the project is supposed to fit together. Where should business logic live? Which adapter handles payments? How does a module connect to the database? Which conventions must remain intact?
Hey Product Hunt! 👋
I built Codapult because I kept rebuilding the same SaaS foundation - authentication, billing, teams, and admin - before getting to the product itself. I also wanted a codebase that stays understandable as it grows, especially when AI coding agents help implement it.
Codapult is a full-source Next.js 16 SaaS foundation built around clear module boundaries and adapter-based integrations for auth, payments, storage, background jobs, and AI services. The CLI helps tailor the codebase to a project's needs, while MCP gives compatible coding agents structured project context. You can self-host it and replace providers without rewriting application logic.
The goal isn't to ship the most features. It's to give developers a foundation they can adapt without accumulating unnecessary complexity.
For those building SaaS with AI coding agents, what's been hardest to keep under control as the codebase grows?