PrismOS

The problem

AI coding assistants are single-voiced. One model takes a feature request and decides everything itself — scope, architecture, implementation, testing — and it never disagrees with itself. The output compiles and demos well, and it quietly skips every tradeoff a real team would argue about.

The second failure is context. Most agent tools generate in a vacuum. They do not know what the codebase already looks like, what stack it runs on, or what was decided three features ago. The result is technically valid and architecturally foreign.

Feature delivery is a coordination problem before it is a code-generation problem. The value in a team comes from friction — the architect pushing back, QA refusing to sign off, the PM cutting scope. Strip that out and call the result autonomous development, and you have a demo rather than a delivery system.

What I built

Point PrismOS at a codebase and describe a feature. It reads the existing product, loads project memory from prior runs, activates seven specialized agents, streams their reasoning live, forces them into structured debate, resolves conflicts through a Release Manager, and returns a package: production-ready code, tests, a conflict log, a benchmark, and a binding SHIPPABLE or NEEDS_REVISION verdict.

The full surface shipped — landing page, dashboard, two-step run creation, a live seven-agent streaming view, project and session history, a conflicts explorer, a benchmark comparison, an architecture page, and a self-contained demo mode.