Montage
The runtime framework for agentic user interfaces!
What it does
AI agents render UI slowly, expensively, and inconsistently — and a huge chunk of inference bills gets eaten by UI generation. Montage fixes it. Your agent emits a tiny intent schema; we compile it server-side into production components. 10x faster hydration, 50-100x fewer output tokens, model-agnostic, framework-agnostic, themed to your brand. Don't let your agents reinvent UI every turn - ship them on Montage!
Does the same job
all alternatives →- RARemy, an AI agent that compiles annotated Markdown into full-stack appsApr 2026 · remy.msagent.ai · ▲5
Hi HN! Sean from MindStudio here. I wanted to share something we've been working on that I think introduces some new ideas into the "AI coding agent" space. Remy is an AI agent that builds full-stack TypeScript apps from a spec written in a new flavor of annotated markdown. The spec has two layers: prose describing what the app does, and annotations that carry the technical precision (data types, edge cases, validation rules, code snippets). The agent then "compiles" this into code: backend methods, typed schemas, frontends, test scenarios, and everything else are derived artifacts of the…
- AAAgentServe – A open-source framework for hosting scalable AI agents2024 · github.com · ▲9
Hey HN! I am super excited (and slightly nervous) to introduce AgentServe! AgentServe is a framework to make hosting scalable AI agents as easy as possible. With 4 lines of code AS wraps your agent (any framework) in a FastAPI and connects it to a Task Queue (celery or redis). Why Should You Care? Standardized Communication Pattern: AgentServe proposes that all agents should communicate with each other and the outside world with “Tasks” that can be submitted in a sync or async way. This simple API wil enable Framework Agnostic: No favorites. OpenAI, LangChain, LlamaIndex, CrewAI are all…
- IBI built a tool to roast landing pages using AI agents2024 · roastmylandingpage.io · ▲9
I built a tool to roast landing pages with AI agents. I was gathering feedback from watching landing page roast videos, and figured out I could prompt LLMs to analyse a screenshot and roast based on the same criteria. It's not 100% accurate yet, but it has been really insightful when I've tested it on my own websites. Let me know what you think!
- PTPrototyper - the fastest AI software design platform2025 · getaprototype.com · ▲6
Hi HN, I’ve been working the past year on something called Prototyper , and today we’re opening up the new version. The motivation is simple: whenever I built products in the past, I noticed the best ideas came after the “first version.” You try something, it feels wrong, you change it, repeat. Most tools make that painful. Prototyper is my attempt to make that loop natural—so you can explore ideas quickly instead of forcing them through a rigid workflow. This release includes: instant updates (no compile/refresh lag) simplified UI (months spent just removing steps) responsive by…
- CACoding Agents swarming your codebaseSep 2025 · infrastructureas.ai · ▲9
I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!
More ai this month
the category →
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.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 26d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com