basically trying to see what a vertically integrated agent looks like, where the agent has deep access inside a framework and it operates from within a framework, so like, instead of reading files, opening processes etc - it gets a bunch of framework specific runtime tools(logs are the easiest example)
Frontman creator here.
Thanks for posting about it!
Just to be clear, its not just brower-based. but also vertically integrated into the framework. we allow for much easier flow for semi-technical/non-technical people.
By being visual we allow our users to just easily work. and by integrating deeply into the framework we're seeing much better results even then claude code and with smaller models(Frontman is very good even with Gemini Nano)
i understand what you're trying to say, but a junior will ship broken code to prod.. even with agents.
he might keep delegating to agents to fix it, but that cycle will produce more brittleness(like the folks at claude code folks keep discovering).
but eventually the organization will push back and ask why it's so brittle and costs more(time/money/people)
This is cool and i keep thinking about CRDTs as a baseline for version control, but CRDTs has some major issues, mainly the fact that most of them are strict and "magic" in the way they actually converge(like the joke: CRDTs always converge, but to what).
i didn't read if he's using some special CRDT that might solve for that, but i think that for agentic work especially this is very interesting
what bothers me is, while CRDTS converge, the question is to what. in this case, it seems like there's a last-write-wins semantic. which is very problematic as an implicit assumption for code(or anything where this isn't the explicit invaraint)
WebMCP is a protocol for exposing tools the AI can call from your running web app.
the point isn't "consume API tokens", it's "let the AI do stuff in your app" (click buttons, fill forms, read DOM state). The Gemini integration is just the orchestrator for the example implementation. not the protocol
i found this extremely frustrating for a various issues:
- when dealing with complex state apps, it's super hard for the AI to understand both the data and the UI
- keep juggling screenshots and stuff between terminal and the app wasnt fun
- it was just not fun to stare at a terminal and refresh a browser.
Agent looping is a brutal problem to debug. Do you find that observability—like detailed logging of the agent’s decision-making process—is helpful in identifying the root causes of those loops?
the signal-to-noise ratio has definitely gotten worse. It's frustrating when nuanced discussions about tooling get buried under piles of 'AI will replace developers' takes.
basically trying to see what a vertically integrated agent looks like, where the agent has deep access inside a framework and it operates from within a framework, so like, instead of reading files, opening processes etc - it gets a bunch of framework specific runtime tools(logs are the easiest example)