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OPERATIONS

Agegency Ops

Multi-Agent Dashboard

TYPEInternal Operations Platform
STATUSLive Internal Tool
STACKNext.js · Python · OpenAI · Supabase
BUILD TIME3 Weeks to V1

THE PROBLEM

Running multiple AI-powered products and agent pipelines creates an observability nightmare. Logs scatter across services, agent performance degrades silently, and debugging multi-step pipelines requires manually tracing execution across systems. Without centralized visibility, issues compound before they're detected.

THE APPROACH

Built an internal dashboard that aggregates agent execution data, performance metrics, and error logs across all Agegency products. The system provides real-time monitoring of agent pipelines, cost tracking per execution, and automated alerts when performance drops below defined thresholds. A replay feature allows re-running failed pipeline stages with modified parameters for rapid debugging.

OUTCOMES

  • Centralized monitoring across 4 products and 12+ agent pipelines
  • Mean time to detect issues reduced from hours to minutes
  • Cost-per-execution tracking with budget alerts
  • Pipeline replay feature cut debugging time by 70%

KEY INSIGHTS

Observability is a product requirement

Treating monitoring as an afterthought creates technical debt that compounds with every new agent or pipeline. Building observability into the architecture from day one pays for itself within the first month.

Cost tracking changes behavior

Making per-execution costs visible immediately changed how agents were designed. Teams started optimizing prompts and reducing unnecessary API calls once the cost was no longer abstract.

Replay > logs for debugging

Being able to re-run a failed pipeline stage with the same inputs but different parameters is exponentially more useful than reading through log files. It turns debugging from archaeology into experimentation.

STACK

Next.jsReactPythonOpenAI APISupabaseTailwind CSSWebSockets

BY THE NUMBERS

4PRODUCTS MONITORED
12+AGENT PIPELINES
70%FASTER DEBUGGING