Rachid Jeffali

Really interesting positioning especially the clinical foundation. From a safety perspective, how do you ensure consistency in responses over time? Is Anna aligned through fine-tuning, or do you rely on structured prompting and guardrails on top of a foundation model? In mental health use cases, stability and drift control seem crucial, curious how you approach that.

The 25+ agents supervised by a central coordinator is interesting. From an architecture standpoint, how do you manage latency when multiple agents run within a single campaign flow? Are they fully parallelized and event-driven, or is there queuing/step orchestration to prevent cumulative delays? Curious how you balance agent specialization with responsiveness at scale.

Clawdbot feels like more than just a tool, it almost sounds like the operating system of the club. Is it bundled as a core part of the Tinkerer experienc, or positioned as a separate product? And long term, do you see it becoming the central layer for members to automate and build on top of? Love the “own your stack” philosophy, curious how tightly OpenClaw anchors that vision.

You mention C1 handles UI generation and runtime under the hood that’s super interesting. From a builder perspective, I’m curious: is the rendering primarily client-side, server-driven, or hybrid? And when generating something like a multi-series chart during a live conversation, how do you keep the experience responsive? Really excited about the idea of LLMs returning structured, interactive...

Having console error copy built right into the dock is the kind of detail that shows you actually built this while using it yourself. Clean. What's your stack for the floating dock rendering across platforms?

Smart move to detect existing abstractions like Tailwind classes instead of injecting inline styles, that's how you keep a codebase clean at scale. The .inspectorrules file for team conventions is a nice touch too.