Models are making capability leaps every few weeks but AI-native product innovation hasn’t kept up.
Most products are forcing AI into existing UX patterns rather than rethinking an AI-native experience from first principles. Parallels to early mobile (2007-2010) - for years, mobile meant shrinking your website into your phone until Uber reimagined transportation.
To be clear, there are lots of amazing AI-first products. See NotebookLM, Lovable, Stitch, Flow. But the pace of innovation on models has been faster, for a lot of reasons which I will explore in future posts."
It’s wired and very finicky. Basically a 10 year old solution to this problem. I have on in my collection. It’s cool but not really useful or in same tier as the other products being mentioned.’
I've been playing around with agents, MCP servers and embedded systems for a while. I was trying to figure out the best way to connect my real-time devices to agents and use them in multi-agent workflows.
At OpenServ, we have an API to interact with agents, so at first I thought I'd just run a specialized web server to talk to the platform. But that had its own problems—mainly memory issues and needing to customize it for each device.
Then we thought, why not just run a regular web server and use it as an agent? The idea is simple, and the implementation is even simpler thanks to MCP. I define my server’s endpoints as tools in the MCP server, and agents (MCP clients) can call them directly.
Even though the initial idea was to work with embedded systems, this can work for any backend.
Just wanted to share and would love to hear your thoughts—especially around connecting agents to real-time devices to collect sensor data or control them in mutlti-agent workflows.
I've been experimenting with OpenServ, a platform for managing multiple AI agents working together. It lets you create teams from an agent pool to handle specific tasks, and you can build agents via their UI or TypeScript SDK. Each agent is basically an Express app with capabilities as routes, so you can integrate any agentic framework you like. I've built some and shared them on my GitHub.
I’m starting to feel like most agentic frameworks are more theoretical than practical—except for easy-to-implement text embedding capabilities like those in LangChain and AutoGen. That said, I think platforms like OpenServ, which provides SDK while allowing devs to leverage other agents from the same ecosystem, will be the ones to win. I’m also planning to explore other platforms like LangFlow, CrewAI, n8n, etc., to compare different approaches.
