Alternatives
Products that do what Montage does
The runtime framework for agentic user interfaces!
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- 2RA
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…
Apr 2026 · remy.msagent.ai
- 3AA
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…
2024 · github.com
- 4IB
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!
2024 · roastmylandingpage.io
- 5PT
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…
2025 · getaprototype.com
- 6CA
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!
Sep 2025 · infrastructureas.ai
- 7SA
Hey everyone! Excited to share Scene with you! We spent hours investigating the intricacies of how people create websites. We focussed primarily on collaboration: what it looks like when teammates with different areas of expertise work together to build a site. We did a deep dive into how designers and marketers work today, and how they envision working in the future. AI will be a big part of that future. But AI is not here to replace the web design process. We know designers don't fully trust creations made entirely by AI—and why should they? Instead, AI is here to lend a helping hand. It…
2024 · scene.io
- 8IM
Hi HN! Solo developer here. 10 days ago, I started building this after spending countless hours copying/pasting marketing sections and fighting to keep them consistent with our design system. I wondered: "What if AI could understand our design system and generate React components that actually match it?" Current progress (10 days in): - Can generate hero sections that follow your design tokens - Uses your actual component variants and styles - Works with Next.js, Tailwind, shadcn/ui It's very early days, but I'm excited to share it with other devs who: - Are tired of rebuilding…
2024 · robustlaunch.com
- 9WB
Hey HN, After GPT-3 created waves in the tech industry, a lot of AI tools were emerging and with that, some AI website builders But the results seemed way too generic to us. It felt like the developers were rushing to catch the wave instead of building a proper tool We took our time, did months of RnD and finally came up with something better than what others in the market are doing. It’s got better design output. While it’s still in beta, I wanted to show HN what we did. Will appreciate the feedback when you guys try it out. Here is the link to signup for the beta:…
2024 · dorik.com
- 10PR
Hi HN, While building RAG agents, I noticed a lot of token budget was wasted on formatting overhead (HTML tags, JSON structure, whitespace). Existing solutions felt too heavy (often requiring torch/transformers), so I wrote this lightweight, zero-dependency library to solve it. It includes strategies for context packing, PII redaction, and tool output compression. Benchmarks show it can save ~15% of tokens with negligible latency overhead (<0.5ms). Happy to answer any questions!
Dec 2025 · github.com
- 11AO
Hi HN, We built one of the largest RAG set-ups that exist toady with Usul.ai (6B tokens). We started by using langchain and llamaindex, they were able to get us to a prototype in a couple of days, but took 3 months of taking pieces apart and optimizing them to make it perform well at such large scale. We put all of these learning into an MIT licensed open-source project — Agentset. Our goal to let people get production quality RAG w/o having to understand or optimize the underlying pieces. It supports 22 file formats, agentic search, deep research, citations, and a UI out of the box.…
Oct 2025 · github.com
- 12AA
We’ve published a set of open-source reference implementations on how to build production-grade Agentic AI applications on AWS. What’s in the repo: • Agentic RAG, memory, and planning workflows with LangGraph & CrewAI • Strands-based flows with observability using OTEL & Arize • Evaluation with LLM-as-judge and cost/performance regressions • Built with Bedrock, S3, Step Functions, and more GitHub: https://github.com/aws-samples/sample-agentic-frameworks-on-... Would love your thoughts — feedback, issues, and stars welcome!
2025 · github.com
- 13AB
I built a small UI design agent that explores multiple UI designs at once, and iterates with or without user input. No need for complicated magic prompts to converge on good design. To get the agent to reliably produce good-looking, functional designs, I generated over 1000 designs while tweaking the system prompt. Let me know what you think!
2025 · trylayout.com
- 14RA
Hey HN, we recently launched Remy, an AI agent designed to take the pain out of video search, and wanted to give the HN community a technical deep dive on how it works under the hood. The Problem: There’s a ton of valuable content on the internet, but finding the “best parts” of long videos is frustratingly inefficient. Current video search methods haven’t evolved much since the early days of YouTube and aren’t designed for today’s massive volume and variety of information. Instead, we’re left scrubbing through long videos or, worse, missing valuable content entirely due to decision…
2024 · useremy.com
- 15IB
Hi HN I built a fun little tool: It uses Groq’s LLaMA 3.3 + Puppeteer to analyze a website Then it roasts the design/content/UX with humor And finishes with 3–5 genuinely helpful improvement tips You can try it here: https://ai-roast-vert.vercel.app I wanted to: Practice fast idea-to-launch cycle (built in 2 days) Experiment with a viral-friendly product Monetize with a $0.55 pro version that gives a detailed roast + download Would love your feedback — on the idea, the tone, the usefulness — anything! Thanks in advance
Sep 2025 · ai-roast-vert.vercel.app
- 16IB
The main goal of this was to be able to not just run multiple Claude Code sessions at once, but actually manage them and keep track of what I was doing. Sometimes this is multiple attempts on the same task, sometimes I work several tasks at once. Really I was just sick of twiddling my thumbs waiting for the coding agent to finish, and I wanted it to be easy to work on/review/test another change while I waited.
2025 · github.com
- 17SR
Hi HN! Sipp is an open-source AI inference library for running local models in browsers with up to 3x faster decode speeds than alternative libraries. My background is in HCI (human-computer interaction) and graphics programming. Me along with my co-founder have been experimenting and thinking a lot about what the next user experience will look like when tokens are commodified to the point of being essentially “free.” A motivation for us was to try to move beyond the chat app and information retrieval use cases that are dominant now, and figure out how AI could instead act as a continuous…
Jun 2026 · sipp.sh
- 18AR
If you're interested in exploring what LLM-based agent systems these days actually do to solve certain benchmarks such as SWEBench or WebArena, we created a small leaderboard with our team, that allows to view a lot of public and OSS agent results including all the runtime traces (the step-by-step reasoning behind the scenes). Looking at traces is actually quite interesting, as they reveal a lot about the inner working and shortcomings of current agent system, e.g. see https://explorer.invariantlabs.ai/u/invariant/webarena--SteP... for an example trace.
2024 · explorer.invariantlabs.ai
- 19MD
We’re excited to share ML-Dev-Bench, a new open-source benchmark that tests AI agents on real-world ML development tasks. Unlike typical coding challenges or Kaggle-style competitions, our benchmark simulates end-to-end ML workflows including: - Dataset handling and preprocessing - Debugging model and code failures - Implementing new model architectures - Fine-tuning and improving existing models With 30 diverse tasks, ML-Dev-Bench evaluates agents across critical stages of ML development. To complement this, we built Calipers, a framework that provides systematic performance evaluation and…
2025 · github.com
- 20AL
Hi HN, I built this to address what I see as the fundamental problem with ReAct-style agents: compounding errors. Even a small mistake made early enough in the loop can snowball and ruin the final output. But with search, agents can look multiple steps ahead and backtrack before committing to a particular trajectory. This has already been shown in a few papers to help agents avoid mistakes and boost overall task performance, but there's no easy way to actually build these kinds of agents. So that's why I made this framework. I believe search will eventually become table stakes for building…
2024 · github.com
- 21AF
I’ve been working on a temporal database for agents that combines graphs, tables, and compute. While building it, I ended up needing an agent framework that could handle both simple tool-use tasks and more graph-based execution, so I pulled that out into a separate project, Agent Forge. Agent Forge uses a two-tier execution model: * a heuristic router decides whether a request is simple or complex * simple requests go through a lightweight agent loop with a single system prompt and tool-calling loop * more complex requests can use memory retrieval, reflection constraints, tree search, and…
Mar 2026 · github.com
- 22GT
Hi folks, I built this guide after watching AI agent prototypes repeatedly fail in production. It demonstrates transforming a monolithic marketplace assistant into a resilient multi-agent system using orra, an open-source platform I also built for production-ready multi-agent applications. The patterns shown are valuable *even if you're building your own orchestration layer*. Each stage builds on the previous one, showing the evolution from fragile prototype to resilient system. What makes this guide valuable: * Architectural transformation with working code examples - split monolithic…
2025 · github.com
- 23RR
Systematic testing of browser agents today is not easy: testing on real websites is flaky, rate-limited and potentially expensive (e.g. using proxies or bypassing Captcha), while static-HTML benchmarks lack state and dynamic behavior. Resurf gives your browser agent a realistic, stateful, instrumented framework — built on synthetic websites with failure-mode injection: - Realistic, dynamic, interactive environment - Deterministic & reproducible - Failure-mode injection (latency, payment errors, 5xx) - Auditable success eval (DB state, not LLM judge) - No dependency on live websites - Browser…
May 2026 · github.com
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