Huzzah – a novel approach to coding with AI
Hello everyone. I've been working on this experimental editor called Huzzah. I've been working almost exclusively with coding agents since January of this year, and over the past few months I began to feel utterly exhausted by them. They're great, but I'm finding it more and more tedious to write full sentences for every change I want. Not only that, but it seems there's a complexity limit for codebases - beyond a certain point the agent begins confusing itself. I'd like to go back to writing code, but I don't want to go all the way back to fully manual coding. So I've come up with this…
In plain words
Huzzah is an experimental code editor that bridges manual coding and AI agents. Developers write pseudocode describing changes they want, and the editor synchronizes it to real source code on save, storing the pseudocode as a record of intent. It targets software engineers fatigued by writing lengthy prompts for coding agents but who want to avoid returning to fully manual coding. The tool addresses the complexity limits of current AI coding agents by combining human-written pseudocode with automated code generation.
written from the facts on this page · September 2026
From the sources
A new experimental way to code with AI
If you’re a software engineer like me, the first few months of 2026 were incredible. Coding agents suddenly became good enough that we no longer needed to manually write code. But if you’re like me, then sometime later you hit a wall. The honeymoon period ended, and the novelty wore off. No more dopamine hits. It’s August, and I feel utterly fatigued . To be honest, I’m sick to death of writing longform English to describe every change I want to my codebase. However, I also don’t want to go back to writing all my code manually. There was real tedium in that practice that I’d prefer to avoid for…well, the rest of my life. And yet, I sense that I need to have better insight and control over…from danielvaughn.dev
In the maker’s words, at launch
Hello everyone. I've been working on this experimental editor called Huzzah. I've been working almost exclusively with coding agents since January of this year, and over the past few months I began to feel utterly exhausted by them. They're great, but I'm finding it more and more tedious to write full sentences for every change I want. Not only that, but it seems there's a complexity limit for codebases - beyond a certain point the agent begins confusing itself. I'd like to go back to writing code, but I don't want to go all the way back to fully manual coding. So I've come up with this interaction paradigm where you: 1. write pseudocode in whatever way makes the most sense to you 2. on save, the editor synchronizes your work to real source code 3. the pseudocode is persisted alongside the generated code, making your prompt effectively a stored record of intent. It may not work for every use case, but in my initial playthroughs I've found it very enjoyable. Right now it's just a proof of concept - installation instructions are here in the readme: https://github.com/danielvaughn/hz You can also watch a video of it in action here: https://x.com/danielvaughn/status/2090456808431165715 Cheers!
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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