About plain

I've spent enough time building production systems to recognize a pattern. Most AI tools today are very good at generating something that looks like it works. They produce convincing demos, local proofs, and quick wins. But none of them ship scalable products. Building scalable systems requires deliberate architecture and modular backend components such as services, datastores, queues, and workflows that can evolve independently. Without clear separation of responsibilities, state leaks across boundaries and the generated application collapses into an implicit monolith. The result is rarely something that I would ship to production. plain exists because building real systems is still hard. I built it out of personal necessity after repeatedly fighting the same failures when trying to ship generated systems in real environments.

The Gap Between Demos and Durable Systems

Turning an idea into a demo is no longer difficult. Turning it into a durable, scalable backend still is. Production systems demand explicit contracts, clear boundaries, repeatable structure, deployment-aware design, and components that can evolve without breaking everything around them. In 2025, it was striking to see pitch decks replaced by live demos, and as an investor that progress was genuinely exciting. But the pattern repeated: companies raised millions on those demos and then immediately hired teams to rebuild the same ideas into real systems that could actually ship. Many tools optimize for generating AI output quickly. plain optimizes for systems that are designed to run in production.

Introducing plain

plain is a platform for building production-grade components, with AI treated as a first-class citizen where it genuinely makes sense. The emphasis is production first. AI is not bolted on, and it is not everywhere by default. It is integrated deliberately alongside databases, services, queues, and infrastructure. plain helps teams define, generate, and operate components that live below applications and above raw primitives and models, resulting in systems that can grow without becoming fragile.

plain is not a prompt playground, a chatbot builder, a demo generator, or a layer that hides complexity behind magic. It is built on the belief that if a system cannot be reasoned about, it cannot be operated. Production systems fail in predictable ways, and plain is designed around those failures by favoring explicit structure over clever abstraction, making tradeoffs visible, ownership clear, and defaults intentional. Systems should be boring to run, and if something would not belong in a real production environment, plain does not generate it.

plain is built for engineers responsible for systems after launch, platform and infrastructure teams, and founders who care about moving fast without sacrificing durability. It is not optimized for throwaway prototypes, one-off experiments, or systems that never need to scale, evolve, or be maintained by real teams.

Build Systems You Actually Ship

plain is for teams that want to move quickly without deferring production concerns. It helps you design, generate, and operate systems with clear boundaries, explicit contracts, and ownership that holds up over time. Whether you are a founder building toward scale or an enterprise team modernizing critical systems, plain is built for what you actually ship.