Like the "building blocks" mentality vs. "factory from scratch" mentality. Because... that's just how the real world works and if we are modeling intelligence off ourselves then why wouldn't that be the right approach?
Wanted to add, in terms of extensibility, we've really tried to make the key parts of the UX hookable. Most of what you see on this page like tool / reasoning calls, voice, loaders, approvals, etc are completely replaceable in a few lines of plain JS: https://www.persona-chat.dev/advanced.html
It means you can do interesting things like go straight to OpenAI or Elevenlabs voice for read-aloud while streaming the main chat from your framework.
I'd like to improve the shareability of what's created in the ecosystem, but we're not quite there yet.
If you have ideas for more hooks or extensions you'd like to see, we're very much in listening mode.
Thanks! Definitely interested in the game overlay use case.
My gut says you'll need want to hook into custom render functions and theme config to map to your game styles, since it's going to look very different than the standard OOTB options.
Appreciate it. And thank you for the work on WebMCP!
For everyone passing by, Alex created https://docs.mcp-b.ai/ and we use two of his libraries to enable WebMCP more cleanly. We found MCP-B after we built our own
It's interesting how experimental web tech vs. frameworks are. Kind of flipped once React and Next.js took off. Now we get to see what the browser can do again. Find the balance that works for each case
Note we actually use React / Vite and Next with Persona across a few of our products. It's nice in our case because the agent specific state (including event debug stream if you turn that on) doesn't need to interact with the main app at all. Keeps updates to agent UX from blowing up other parts of the app
Feels like the active discovery going on is trying to understand what is computer vs what is AI, for every product.
Agents help a ton with the discovery, but the act of building a product needs a deeper level of thought and validation to make it actually better than what came before. So IMO what you see is people still learning what needs to be understood and crafted first hand to make a product better (including economics)
Hopefully we can blend those two options together so it’s not a choice.
Personally I find being able lean on our heavily documented standards in /review gives me back time to dive into what I want to craft next.
Same with scheduling repetitive tasks an agent can do for me well once instructed well. I am freed up to do something else I want to focus actively on because I like it and want it to be great.
Now stress about OKRs and OKRS in general… that’s a different issue
At this point you have to use more than one to get a complete picture, which I’m doing now. Mainly because:
1) some are not always up to date (started on helicone but felt a lag on price updates)
2) they don’t return every model / provider I want (https://ai-gateway.vercel.sh/v1/models has rich data but is a subset, so I combine with helicone)
I always hope for the best when someone has a new list because of this. I want a de facto source!
I have 2 (CC and Codex) running within most coding sessions, however can have up to 5 if I'm trying to test out new models or tools.
For complex features and architecture shifts I like to send proposals back between agents to see if their research and opinion shifts anything.
Claude has a better realtime feel when I am in implementation mode and Codex is where I send long running research tasks or feature updates I want to review when I get up in the morning.
I'd like to test out the git worktrees method but will probably pick something outside of core product to test it (like building a set of examples)
Former co-founder / CEO @ Zing, acquired by BigCommerce in 2015. Been through the whole IPO thing.
nate (at) runtype.com