Loop guardrails checklist + decision framework

What you get

2 production-ready files:

✅ loop-guardrails-checklist.md: Pre-deployment checklist

• Max iterations limit (how many loops before forced stop?)
• Timeout budgets (how long should one agent action take?)
• Escalation triggers (when to ask for human help)
• Runtime enforcement (code that actually stops loops)
• Testing patterns (how to safely verify guardrails work)

📋 stop-retry-escalate-decision-tree.md: Operational framework

• STOP criteria: non-retryable errors (auth, validation, policy violations)
• RETRY criteria: transient failures (429, timeouts, connection errors)
• ESCALATE criteria: unclear errors, confidence drop, manual review needed
• Real error examples with decision logic
• Integration hints for your agent framework

How to use

1. Download the package
2. Print the checklist (or bookmark it)
3. Run checklist before deploy (catches 80% of loop issues)
4. Integrate decision tree into your agent's error handling
5. Set runtime constraints (max iterations, timeouts, escalation)

What this prevents

✓ Infinite loops from retry storms
✓ Cascading failures (one error triggering chain reaction)
✓ Unbounded cost (preventing 1000-call death spirals)
✓ Silent failures (agent looping without visibility)
✓ "Better prompt" syndrome (guards in code, not AI)

Real-world example

Without guardrails:

Agent tries task -> fails -> retries -> fails again -> retries -> ... (100+ attempts)
Cost: $50, API quota burned, user frustrated

With guardrails:

Agent tries task -> fails -> retries once -> fails -> 
Check: Is this retryable? No -> STOP and escalate to human
Cost: $0.05, human reviews in 2 minutes, clear path forward

When you need this

• Building production AI agents (not experimental chatbots)
• You've had agents loop forever in production
• Your team needs clear decision logic for error handling
• You want guardrails in code, not just prompt tweaks
• You need to hand off agent operations to on-call engineers

Decision logic reference

Related resources

• AI agents: why they loop and how to stop
• Backoff + jitter: the simplest reliability win
• Retry logic when resilience makes outages worse
• Prompt injection: defense in depth

Services

Building production AI agents? Need help designing guardrails or auditing your error handling? Let's work together ->

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