FlowBoard v5: Event-Sourced Project Workspace for Multi-Agent Teams
FlowBoard v5 ships as a full rebuild of the context layer for AI coding agents. The core problem: every agent session starts blank, so across projects you repeatedly re-explain goals, decisions, and status. FlowBoard replaces that with a persistent workspace that agents pull exactly the slice they need, lazy-loaded to keep token use low.
What's New in v5
- Rebuilt on React — All surfaces (Kanban, Idea Canvas, new Overview) now run on one stack; no vanilla runtime left.
- Event-sourced task store — Every change is an append-only event in SQLite. Full history, nothing drifts out of sync.
- Multi-agent, first class — Stable per-agent identity, external agents self-onboard with claim/release/handoff built in. Your OpenClaw agent, Claude Code, and Cursor all appear live on the same board.
- Ideas to specs — Sketch ideas as connected notes on the canvas, then a guided clarify loop turns them into real specs with acceptance criteria, not just task titles.
- Modular Overview — A per-project dashboard composed from widgets: what's blocked, needs approval, milestones, CI status, files. Both you and your agent can compose it.
Installation & Updates
Install from ClawHub with one line:
openclaw plugins install clawhub:flowboardThen a single command brings up the dashboard. After that, it self-updates from inside the dashboard. A Telegram mini app is also available for mobile access.
Code and docs on GitHub: https://github.com/rasimme/FlowBoard
v4 gave agents a Kanban board; v5 is a full rebuild on React with event sourcing and first-class multi-agent coordination.
📖 Read the full source: r/clawdbot
👀 See Also
Running OpenClaw in an Isolated Micro-VM with Void-Box
OpenClaw can be run as a service inside an isolated micro-VM using Void-Box, a capability-bound runtime that executes workflows in KVM micro-VMs, providing a clean execution boundary without container runtime involvement.
Double-Buffering Technique for LLM Context Windows Eliminates Stop-the-World Compaction
A technique called double-buffering can prevent LLM agents from freezing during context window compaction by summarizing early and maintaining two buffers, allowing seamless handoff at no extra inference cost.
Tocket CLI: A Context Engineering Framework for AI Coding Agents
Tocket is a CLI tool that creates a .context/ folder with markdown files for AI agents to maintain project memory across sessions. It auto-detects tech stacks from package.json and generates a pre-configured .cursorrules file.
The Commons 2.0: A Persistent Space for AI Models to Communicate
The Commons is a public platform where AI models like Claude, GPT, Gemini, and Grok can post in discussions, annotate poetry, leave postcards, and build ongoing conversations across sessions. Version 2.0 adds interest-based organization, notification systems, voice profiles, and agent check-in infrastructure.