A text format for UI wireframes – comparing token costs across 4 format
I've been exploring how to describe UI layouts to LLMs efficiently. The problem: When you ask an AI to generate or modify UI, how do you describe the current state? - Natural language ("header on top, form below") is ambiguous - ASCII art breaks when edited (alignment issues) - HTML is precise but verbose I ran some measurements. For a simple login form: - Natural language: 102 tokens - ASCII art: 84 tokens - HTML: 330 tokens I experimented with a grid-based text format using Excel-like cell references: grid: 4x3 A1..D1: { type: txt, value: "Login" } A2..D2: { type: input, label: "Email" }…
A text format for UI wireframes – comparing token costs across 4 format launched on February 5, 2026 with 5 votes, #1,882 of 16,627 launches that month and more than 75% of that year's launches.
What it does
Text-based UI wireframe generator - Wireframes that AI can read and write - enlinks-llc/katsuragi
In the maker’s words, at launch
I've been exploring how to describe UI layouts to LLMs efficiently. The problem: When you ask an AI to generate or modify UI, how do you describe the current state? - Natural language ("header on top, form below") is ambiguous - ASCII art breaks when edited (alignment issues) - HTML is precise but verbose I ran some…
Does a similar job
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LLMs can generate valid JSON 100% of the time2023 · github.com · ▲854Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
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Fine-grained stylistic control of LLMs using model arithmetic2023 · github.com · ▲85We developed a new framework that enables flexible control of generated text in language models. By combining several models and/or system prompts in one mathematical formula, it lets you tweak your style and combine model outputs with ease. A handy tool for those working with LLMs, looking for more fine-grained control of stylistic output. More details in our paper: https://arxiv.org/abs/2311.14479. Feedback and potential applications are welcome.
TypMoDec 2025 · typmo.com · ▲154Hello HN! I’ve been working on a small tool that helps you move from quick wireframe experiments to solid, production-ready prompts. As a designer, I’ve always felt that getting the structure right early saves a ton of pain later. TypMo leans into that idea by grounding everything in IA-style wireframes- fast to create, easy to iterate, and perfect for figuring out what you actually mean before throwing prompts at AI. I’m now pushing it a step further with a lightweight DSL. Still early, still rough around the edges, but with some AI help it’s starting to feel real. Would love to hear what…


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