THE AGENTWACH LIBRARY
Learn agent observability.
Deep guides on the patterns, failure modes, and defenses that decide whether your autonomous agents stay useful or run your bill into the ground.
Guides
What is agent observability?
7 MINAgent observability is the discipline of knowing what your autonomous AI agents are doing, what they cost, and when they go wrong — before your users (or your bill) tell you.
How to stop runaway AI agent costs
9 MINRunaway-cost incidents are the most common way teams discover their agent infrastructure is broken. Here is how to prevent them — and how to limit the blast radius when one slips through.
Detecting prompt-injection in production agents
8 MINPrompt-injection is the SQL-injection of the LLM era — and most teams have no defense against it deployed in production. Here is the practical detection playbook.
Coming next
- OpenTelemetry for AI agents: a practical guide
- Token budgets vs hard stops: choosing the right guardrail
- Loop detection patterns for autonomous agents
- Comparisons: agentwach vs LangSmith, Helicone, Langfuse, AgentOps