Project Info

BossRoom - Gamifying Work Across 900+ Apps

Devpost

Inspiration

AI agents are powerful, but interaction is still tool-centric: prompts, configs, dashboards. We built an interface where delegation is spatial and direct — like walking up to a coworker and stating the outcome. What It Does BossRoom is a real-time multiplayer 3D office where AI agents are persistent coworkers. Real Execution (Not Chat) Agents execute real work across 900+ enterprise integrations : Messaging & Communication: Slack, Microsoft Teams, Discord, WhatsApp Business Email & Calendar: Gmail, Outlook, Google Calendar Docs & Knowledge: Notion, Confluence, Google Docs/Drive, Airtable Whiteboarding & Design: Miro, Figma Project & Issue Tracking: Linear, Jira, GitHub, GitLab CRM & Sales: Salesforce, HubSpot DevOps & Cloud: AWS, GCP, Azure Databases & Infra: PostgreSQL, MongoDB, Supabase Commerce & Payments: Stripe, Visa Intelligent Commerce (MCP) Search & Data: SERP APIs, live product search, external data sources All actions execute in real user-scoped accounts via secure OAuth — no API key's, no configuration. Dynamic Multi-Agent Teams A Receptionist receives a goal (e.g., “research competitors + write report”). It dynamically spawns 3–12 agents via tool calls. The LLM decides roles, skills, and leadership. A lead agent delegates subtasks to workers. Workers post updates to a shared scratchpad feed. The lead compiles and finalizes output. All agents and workspace state persist in PostgreSQL. No hardcoded bots. Every workspace builds itself from the goal. Interaction Layer Push-to-talk voice input Real-time transcription → execution → spoken response Agents have visible states (listening, thinking, working, done, error) Proximity-based player voice chat (WebRTC spatial audio) World Layer Procedurally generated chunked terrain (simplex noise, LOD) Physics-based controls Multiple avatar models In-world 3D speech bubbles + visual state indicators - In-world integrated views from your favorite apps Architecture Frontend Next.js 16 + React 19 + TypeScript + Tailwind v4 React Three Fiber + drei Rapier physics Zustand (14 stores) synced via WebSocket 46 typed WebSocket message types, validated with Zod shadcn/ui for panels, scratchpad, product cards Backend Node.js WebSocket game server (domain-driven modules) PostgreSQL 15 + Drizzle ORM (7 tables) Dynamic agent creation + runtime skill system Vercel AI SDK (streamText, multi-step tool calls) Vercel AI Gateway (Gemini / Claude / GPT-4o swappable) Composio OAuth for Gmail, Calendar, Linear, Stripe etc MCP support for external tool servers (Visa Intelligent Commerce) Voice Two independent spatial pipelines (shared AudioContext): Agent voice loop Mic → WebSocket → Deepgram (STT) LLM execution Inworld TTS → HRTF spatial playback Agent voice loop Mic → WebSocket → Deepgram (STT) LLM execution Inworld TTS → HRTF spatial playback Player voice PeerJS WebRTC HRTF panner per remote player Distance-based rolloff Player voice PeerJS WebRTC HRTF panner per remote player Distance-based rolloff Infrastructure Terraform-managed infrastructure Google Cloud Run (WebSocket server, 3600s timeout) Cloud SQL (Postgres) Cloudflare Pages (frontend) Firebase Auth (Google Sign-In) Cloud Build → Artifact Registry → Docker deploy Fully deployed. Not localhost. Challenges Building a physics-based 3D world with responsive third-person controls Real-time multiplayer state sync (positions, agent state, scratchpad, products) over a single multiplexed WebSocket connection Designing and validating 46 typed WebSocket message types (end-to-end Zod schema enforcement) Dynamic agent spawning (3–12 agents per workspace) with persistent storage and zero race conditions during streaming tool calls Multi-step LLM tool orchestration (up to 25 steps/turn) without blocking or state corruption Maintaining per-agent memory, role separation, and runtime skill creation Dual spatial audio pipelines (agent TTS + WebRTC player voice) sharing one AudioContext without interference Real-time STT → LLM → TTS voice loop with spatial playback tied to 3D coordinates OAuth scoping per user across 900+ integrations (secure isolation per Firebase UID) MCP tool server integration (Visa Intelligent Commerce) with fallback payment rails Cloud Run WebSocket deployment (HTTP/1.1, 3600s timeout, SQL proxy sidecar, keepalive strategy) Streaming AI responses while preserving deterministic game-state updates Procedural chunked terrain generation with LOD and performance constraints - Shipping production infra (Terraform, Cloud Build, Docker, Cloud SQL, Cloudflare Pages) during a 36-hour hackathon Accomplishments Turned “agent workflows” into a game loop: walk up → ask → watch progress → get the outcome. Made non-technical users effective on day one — no prompt craft, no dashboards, no setup rituals. Converted messy, multi-step execution into a single clear interaction: users state intent, the system handles planning + delegation + tool actions. Made agent work observable: you can see who’s doing what and hear responses spatially, instead of guessing in a black box. Built a collaborative feel (multiplayer + proximity voice) so delegating to AI feels like working in a room, not using a tool. Shipped real-world execution end-to-end (emails, tickets, meetings, payments) inside a fully deployed product in 36 hours. ~179 commits 6,000+ lines of TypeScript 46 WebSocket message types 14 Zustand stores 7 database tables Full infrastructure-as-code deployment This is a working system, not just a prototype. What We Learned The interface layer matters as much as the model. Dynamic team creation — letting the LLM design the org structure per task — was the key architectural unlock. Coordination becomes intuitive when agents are embodied, stateful, and observable. What’s Next Automatic model routing per task type Visible in-world agent-to-agent collaboration Cross-workspace skill marketplace Expanded MCP integrations Deeper in-world commerce flows Every team will manage fleets of AI agents. BossRoom is the interface layer.

Analysis

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Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • CSSIn code
  • FirebaseIn code
  • JavaScriptIn code
  • Next.jsIn code
  • OpenAIIn code
  • PostgreSQLIn code
  • ReactIn code
  • Tailwind CSSIn code
  • TypeScriptIn code
  • Vercel AI SDKIn code
  • Google GeminiClaimed
  • Node.jsClaimed

10 of 12 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

  • Claude CodeConfig
  • CursorCommits

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

973 KB

Source files

203

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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