Super cool approach. What ended up being the hardest part of bypassing macOS’s lack of monitor mode—was it USB throughput constraints or getting reliable timing for TX/RX?
Hey HN, Rachel here, another member of the team on the product/design side. Happy to answer questions about the use cases or where we're taking the UX. Matt covered the technical bits well but please let me know if any UX enhancements or bugs you think of or run into with this!
This validates something we keep seeing-the bottleneck for AI agents isn't intelligence, it's that tooling isn't yet built for how they actually work. Structured specs and parseable errors > docs written for humans. Really cool to see this ship.
Correct for now. We've got a ways to go to hammer out the real details of enterprise. We wouldn't want a world where not having the enterprise-y add-ons would hinder the core value prop.
Fair question. The core will always stay open source and free. We’ll monetize around it with things like managed hosting, enterprise support, and compliance options (HIPAA, SOC2, etc). Basically, we make money when teams want someone to stand behind it in production, not for using the software itself. But let us know if you have other ideas! We're still new to open source
Yep! We were working on an authentication startup (https://news.ycombinator.com/item?id=30615352) and built it to $1.5M in ARR, but then we saw even a bigger pain point; local AI is hard. When we tried building a corporate knowledge base with RAG and local models, we hit the same wall: a painful gap between prototype and production.
Production-ready enterprise AI requires solving model management, RAG pipelines, model fine-tuning, prompt engineering, failover, cost optimization, and deployment orchestration. You can’t just be good at one or two of these, you have to be great at all of them or your project won't succeed. And so Llamafarm was born!
Monetization-wise - We’re open source and free forever, with revenue coming from enterprise support, managed deployments, and compliance packages—basically, companies pay for confidence, not code.
Hey thanks! I'm Rachel from LlamaFarm; we actually use LlamaIndex as one of our components. It's great for RAG, and we didn't want to reinvent what they've already done. LlamaFarm is about bundling the best of open source into a complete, production-ready AI project framework. Think of us like the integration and orchestration layer that makes LlamaIndex, plus model management, plus prompt engineering, plus deployment tools all work together seamlessly.
Where LlamaIndex gives you powerful RAG primitives, we give you the full production system - the model failover when OpenAI is down, the strategy system that adapts from development to production, the deployment configs for Kubernetes. We handle all the boring stuff that turns a RAG prototype into a system that actually runs in production. One YAML config, one CLI command, and you have everything from local development to cloud deployment. :)
Hey, great feedback. The ease of onboarding comes from simply clicking a link in your email (or from a text message) to become a user of a product--striping away the need for passwords and loaded forms that typically hinder entry to a new experience.
Sorry the use of the snippet on the page wasn't clear, we'll work on highlighting that better. The snippet is being demonstrated on the page via the hub in the left corner and is connected to the "submit" button to capture email and authenticate users. By putting the snippet on your site, you can skip building a full on sign in/sign up flow and authenticate your users with our hub.
Hope this helps! We're grateful for your feedback!
Hi Hacker News! I'm a co founder and heading up design at Rownd. Looking forward to feedback and questions about your experiences trying out our product!