Huzzah swaps throwaway AI prompts for persistent, declarative pseudocode

Developer Daniel Vaughn is burned out on chatting with coding agents. His complaint isn’t that AI writes bad code — it’s that the interaction model wastes intent. Prompts get discarded, so there’s no durable record of what a human actually wanted. The instructions are imperative and repetitive, re-describing the same application changes turn after turn and burning tokens. And English itself is a lossy medium: most of a sentence carries social rather than technical signal, which makes it a clumsy way to specify software.

His answer is Huzzah, an experimental editor that inverts the paradigm. Instead of longform, imperative, transient chat messages, you write terse, declarative pseudocode into a persistent .hz file. Saving the file triggers code generation; editing it lets Huzzah diff your changes and feed only that delta to the LLM, regenerating the affected source. A FizzBuzz becomes four lines of shorthand rather than a paragraph of prose, and the pseudocode doubles as living documentation of intent. Because it’s language-agnostic, one spec could in principle target multiple languages — useful for portable algorithms like a CRDT.

Vaughn is candid about the limits. The approach suits greenfield projects far better than existing codebases, may not hold up at scale, and struggles with cross-file dependencies. Developers lacking domain expertise are probably better served by plain natural language, and you lose LSP features unless they’re regenerated too. Huzzah is open source and firmly in the experimental stage — a design provocation about controlling AI-generated code, not a finished tool.