AI Agents
expert
~55 hours
Self-Healing Multi-Agent Pipeline with Observability
Build a multi-agent system (researcher, writer, reviewer) with self-healing: automatic retry, fallback strategies, anomaly detection, and a real-time observability dashboard showing agent health and cost.
Skills Demonstrated
Multi-agent orchestration
Self-healing with circuit breakers
Cost tracking and budget governance
Distributed tracing and observability
Implementation Steps
- Define agent roles with typed input/output schemas
- Build orchestrator with DAG-based execution plan
- Implement circuit breakers and retry with exponential backoff
- Add self-healing: detect failures, swap models, adjust prompts
- Build cost tracker logging tokens/cost per agent per step
- Create real-time dashboard: agent status, latency, cost, errors
- Add budget governance: per-run limits with graceful degradation
Interview Relevance
Why this project matters for interviews
Multi-agent systems are the next wave. Self-healing and observability show production maturity beyond 'it works on my laptop'. Critical for senior roles at Anthropic, LangChain, CrewAI, and enterprise AI teams.