AgenticAI
Rugved ChandekarBuild a "Multi-Agent System Simulator and Monitor". Architecture: - Frontend: A visual React interface that acts as an operations dashboard. It should show live task statuses ("Backlog", "In Architecture Design", "Code Review", "QA Testing") moving across a Kanban-style pipeline. Include an event log stream component that prints simulated log traces of what individual AI agents are communicating. - Backend: A modular backend with a clean state machine handling the workflow logic. Expose REST endpoints to initiate a new task simulation and pull active status. Include a helper utility that dynamically calculates simulated "token usage", "cost", and "time saved". - Database: Database tracking 'tasks', 'agent_logs', and 'efficiency_metrics'. - Quality Assurance: Write robust unit tests verifying the state transitions of the tasks to ensure no deadlocks or invalid states. The goal is to visually demonstrate how distinct LLM agents collaborate on technical tasks with highly explicit event streams.
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Task Dashboard
Live monitoring of AI agent collaborations across the pipeline — watch tasks move through Backlog, Architecture Design, Code Review, and QA Testing in real time.
Task Simulation Stages
Select a stage to inspect agent throughput
Architect Agent drafting system design and task graph.
No tasks currently in QA Testing
Drag a card to reprioritize the queue. Click any card to inspect agent activity and cost metrics.
Design authentication microservice schema
Implement REST endpoint for task creation
Refactor state machine transition guards
Add rate limiting middleware
Optimize database indexing for agent_logs table
Build WebSocket event stream handler
Write unit tests for token usage calculator
Deploy Kubernetes autoscaling config
Agent Event Stream
Efficiency Metrics
Simulated agent performance across the active pipeline
Active Tasks
Total Tokens Used
Time Saved
Average Task Duration
Watch AI Agents Collaborate
in Real Time
Visualize how distinct LLM agents work together on technical tasks with explicit event streams, Kanban pipelines, and live efficiency metrics.
Everything you need to simulate, monitor, and test
Live Kanban Pipeline
Watch tasks move dynamically across Backlog, Architecture Design, Code Review, and QA Testing stages in real time.
Event Log Stream
Simulated log traces of AI agent communications scroll continuously, showing every decision and handoff.
State Machine Testing
Verify every state transition to ensure no deadlocks or invalid states. Built for QA engineers who demand reliability.
Efficiency Metrics
Dynamically calculated token usage, cost per task, and time saved — visible on every completed simulation.
Interactive Kanban Pipeline
Tasks flow through distinct stages as AI agents collaborate — from initial backlog to verified completion.
API Authentication Flow
Payment Gateway Integration
Database Schema Migration
User Profile Endpoint
Rate Limiter Module
WebSocket Event Handler
Measurable Efficiency Gains
Ready to see AI agents in action?
Launch the dashboard to watch tasks flow through the Kanban pipeline, observe agent event logs, and inspect efficiency metrics — all in real time.
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