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Agentic Engineering
  • Fundamentals
  • Agent Architecture
  • Tool Calling
  • RAG Engineering
  • Context Engineering
  • Memory & State
  • Planning
  • MCP — Model Context Protocol
  • Multi-Agent Systems
  • Human-in-the-Loop
  • Evaluation & Testing
  • Observability
  • Guardrails & Security
  • Reliability Engineering
  • Frameworks
Agentic/Learn/Reliability Engineering

Reliability Engineering

Failure scenarios and their mitigations: retries, fallbacks, limits, budgets, caching.

Reliability Overview: The Seven Failure Scenarios
▶ interactive

Production agents fail in a small number of recurring ways; each has a known mitigation, and a reliable system is one that has a planned response for all seven before launch.

Failure Scenarios: Detection and Runbooks

Each of the seven production failure scenarios has a characteristic signal in traces and metrics and a concrete runbook; knowing both turns a 3 a.m. page into a ten-minute fix.

Budgets, Limits and Termination

An agent loop must be bounded by hard limits on steps, tokens, cost and wall-clock time, with loop detection and a graceful degradation path, all enforced in code outside the model.

Fallbacks, Caching and Model Routing

Provider fallback chains keep the product up, prompt caching and result caching cut cost and latency, and routing by difficulty sends each request to the cheapest model that can handle it.

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