Designing Agent Fallbacks and Graceful Degradation
Keep an agent safely useful when models, tools, data, or specialists fail—without fabricating success or silently weakening controls.
Topic
#observability
16 articles — updated daily
Production Monitoring for AI Agents
Turn traces, metrics, logs, and evaluations into selected production signals, thresholds, dashboards, and actionable alerts.
Caching Strategies for AI Agent Systems
Reuse expensive results only when identity, freshness, authorization, and side-effect semantics make reuse safe.
Rate Limits and Backpressure in AI Agents
Control overload before immediate retries turn constrained models, tools, or workers into a failure storm.
Scaling AI Agent Systems
Grow workload capacity safely by separating stateless runtimes from durable tasks and protecting constrained dependencies.
Agent Latency Explained
Why multi-step agents feel slow, where elapsed time accumulates, and how to improve speed without breaking the task.
Deploying AI Agents to Production
A practical path from a local agent prototype to a controlled, observable, and reversible production service.
Agent Stopping Conditions Explained
A practical, production-oriented explanation of agent stopping conditions, with examples, boundaries, trade-offs, and failure handling patterns.
Handling Tool Failures in AI Agents
A practical, production-oriented explanation of tool failure handling, with examples, boundaries, trade-offs, and failure handling patterns.
Idempotency in Agent Workflows
A practical, production-oriented explanation of idempotency in agent workflows, with examples, boundaries, trade-offs, and failure handling patterns.
Retries, Timeouts, and Failure Recovery in AI Agents
A practical, production-oriented explanation of retries, timeouts, and failure recovery, with examples, boundaries, trade-offs, and failure handling patterns.
Reliable AI Agent Architecture
A practical, production-oriented explanation of reliable AI agent architecture, with examples, boundaries, trade-offs, and failure handling patterns.
Human-in-the-Loop for AI Agents
A practical, production-oriented explanation of human-in-the-loop control, with examples, boundaries, trade-offs, and failure handling patterns.
AI Agent Security Explained
A practical, production-oriented explanation of the security model of an AI agent, with examples, boundaries, trade-offs, and failure handling patterns.
Observability for AI Agents
A production observability model for agent, model, retrieval, tool, sub-agent, and infrastructure signals—with privacy and redaction controls.
Agent Traces and Trajectories
Learn how traces and trajectories represent observable agent execution without requiring storage or exposure of private chain-of-thought.