# Daniel Vaughn publishes Huzzah, an AI editor built around persistent pseudocode > Source: > Published: 2026-08-20 19:53:50+00:00 # Daniel Vaughn publishes Huzzah, an AI editor built around persistent pseudocode **The experimental editor treats persistent `.hz` pseudocode as a human-authored specification and regenerates source code from changes to it.** By [RuntimeWire Staff](/author/runtimewire-staff) ยท Published Primary source: [Daniel Vaughn](https://www.danielvaughn.dev/posts/huzzah/) ## Why it matters Huzzah tests whether human-authored intent can remain a durable software artifact instead of disappearing inside coding-agent chats. Its current public prototype is much narrower than that premise: it sends a full pseudocode input to OpenAI and displays read-only generated code, without reconciliation, review states or accept-or-reject controls. Daniel Vaughn has published [Huzzah](https://www.danielvaughn.dev/posts/huzzah/?ref=runtimewire), an experimental AI coding editor built around persistent, developer-written pseudocode. Vaughn presents it as an alternative interface for working with large language models rather than a replacement for coding agents. The project's [source code is public on GitHub](https://github.com/danielvaughn/hz?ref=runtimewire). [Vaughn's website identifies him](https://www.danielvaughn.dev/?ref=runtimewire) as a design engineer and Head of UX at Dreadnode, while the AI security company's [team page lists him as Head of UX/UI](https://dreadnode.io/company/about/?ref=runtimewire). He says he has roughly 12 to 15 years of web experience. Huzzah grew from his frustration with spending increasing amounts of time describing code changes in longform English, even as coding agents became capable enough to handle much of the implementation. His complaint goes beyond prompt fatigue. Chat records a sequence of requested changes, while source code becomes the lasting artifact. The developer's original intent can end up scattered across discarded sessions, repeated instructions and implementation details authored by a model. Huzzah gives that intent its own persistent document. ### The prompt becomes the program A developer in Vaughn's Huzzah demonstration writes a pseudocode specification in a file ending in `.hz` . Vaughn does not prescribe a grammar: the specification can be terse, verbose or shaped around whatever concepts make sense to its author. In the demonstration, a fizz buzz program begins with a small specification: ``` fizz_buzz() loop 100 modulo 3 ? "fizz" 5 ? "buzz" both ? "fizz buzz" ``` Huzzah generates an implementation from that document. To make the function accept a variable number of iterations, the developer changes `fizz_buzz()` to `fizz_buzz(n)` and replaces `loop 100` with `loop n` . [Vaughn's article says Huzzah captures the pseudocode diff, uses it as the model prompt and regenerates the affected source](https://www.danielvaughn.dev/posts/huzzah/?ref=runtimewire). [Watch Vaughn's Huzzah demonstration](https://www.danielvaughn.dev/videos/huzzah-social.mp4?ref=runtimewire). The article also gives shopping-cart and todo-list examples. Their pseudocode describes data structures and operations such as adding an item, calculating a checkout total and toggling a task's completion state. Vaughn argues that a language-agnostic specification could eventually support implementations for several languages or execution environments. [Vaughn's article calls coding-agent prompts "longform, imperative, and transient" and contrasts them with Huzzah's "pseudocode, declarative, and persistent" workflow](https://www.danielvaughn.dev/posts/huzzah/?ref=runtimewire). The pseudocode remains available as human-authored documentation while the generated source provides the implementation. ### The repository describes a local experimental application The [Huzzah repository](https://github.com/danielvaughn/hz?ref=runtimewire) describes the project as an experimental interface for building software by editing persistent pseudocode and synchronizing it with an AI-generated implementation. Its setup documentation describes a local web application that requires Node.js 22.19 or newer and access to a model provider supported by the Pi coding-agent framework. The documented providers include Anthropic, OpenAI, Google, Azure OpenAI, Amazon Bedrock, Ollama, LM Studio and vLLM. That setup is broader than the narrow demonstration of turning a pseudocode example into generated source, but the supplied materials do not establish production deployments, usage metrics or a hosted service. The repository documentation should be read alongside Vaughn's article. The article describes a future-facing workflow in which edits to a saved `.hz` file produce a diff that guides regeneration of affected source. Huzzah remains an experimental project, so the public implementation and that proposed workflow should not be treated as evidence of a mature coding environment. ### Vaughn has worked on the design-code boundary before Huzzah follows a recurring theme in Vaughn's projects: finding interfaces that let people express software without working entirely in conventional source code. Before Huzzah, Vaughn created Matry, a design-tooling project intended to connect designers and software developers. A [1909 profile described Matry](https://www.weare1909.org/blog/accelerator-get-to-know-the-founders?ref=runtimewire) as an attempt to create a programming language specifically for designers, while its public work remains collected under the [Matry GitHub organization](https://github.com/matry?ref=runtimewire). Vaughn's personal site also lists Stride, a browser-based, keyboard-driven design tool, alongside projects called Tardis and Legume. Huzzah applies that design instinct to the divide between developers and coding agents. In Vaughn's concept, the `.hz` document is readable by a person, dense enough to guide a model and durable enough to serve as documentation. The developer specifies behavior and inspects the resulting implementation; the model translates the specification into source. ### Persistent intent already has well-funded competitors Other AI coding products have also moved toward reusable instructions and durable specifications. [Cursor's project rules](https://cursor.com/docs/rules?ref=runtimewire) place reusable, version-controlled agent instructions inside a repository. [Augment Code's Intent](https://www.augmentcode.com/blog/intent-a-workspace-for-agent-orchestration?ref=runtimewire) organizes agents around a living specification, approval checkpoints and resumable workspaces. [Zed, a code editor with AI tooling](https://zed.dev/ai?ref=runtimewire), supports agentic editing, reviewable diffs and persistent project instructions. Huzzah assigns the specification a different role. Cursor rules provide standing context for an agent, and Augment's living spec coordinates work across agents and workspaces. Vaughn's concept treats pseudocode as the developer's editable representation of the program, with generated source derived from that representation. Money has already poured into the broader AI coding category. Cline [announced $32 million across seed and Series A funding in July 2025](https://cline.bot/blog/cline-raises-32m-series-a-and-seed-funding-building-the-open-source-ai-coding-agent-that-enterprises-trust?ref=runtimewire). Replit [raised $250 million in September 2025](https://replit.com/news/funding-announcement-series-c?ref=runtimewire), and Qodo [announced a $70 million Series B in March 2026](https://www.qodo.ai/blog/qodo-70m-series-b-shift-to-artificial-wisdom?ref=runtimewire). Those financings do not involve Huzzah, but they show the amount of capital chasing tools that mediate how developers direct and review AI-generated code. [Vaughn describes Huzzah as actively developed and experimental](https://www.danielvaughn.dev/posts/huzzah/?ref=runtimewire). No funding, investors, customers, pricing, production deployments or usage metrics have been disclosed in the supplied materials. ### Ambiguity remains the expensive part Pseudocode leaves room for interpretation, especially when requirements involve state, error handling, performance, security or relationships across multiple files. A chat interface lets the model ask questions and gives the developer room to clarify edge cases conversationally. Huzzah will need a way to surface ambiguity without reproducing the long chat sessions Vaughn wants to escape. [Vaughn identifies several constraints himself](https://www.danielvaughn.dev/posts/huzzah/?ref=runtimewire). The approach may encounter problems at scale, appears better suited to new codebases and may struggle to express cross-file dependencies. Language-server-style features are also unavailable, though he suggests they could eventually be generated. Those constraints keep Huzzah focused on a practical test: whether editing persistent pseudocode gives developers a clearer record of intent than repeatedly explaining software changes to an assistant. The project does not yet establish that the method can support large production systems. Its prospects depend on whether the specification stays precise once the program becomes larger than the explanation it replaced.