AI Agent Guardrails
AI agents that do not loop forever
Bounded execution, prompt injection defense, safe tool calls, and observability for production AI agents. Research-backed guardrails, not marketing hype.
What you will find here
Practical guardrails for production AI agents: bounded execution, loop control and token budgets, prompt injection defense, safe tool-call patterns, approval gates, and audit trails. Research-backed principles applied to real agent architectures — no abstract theory.
Who this is for: engineers deploying AI agents with tool-calling capabilities (GPT-4o, Claude, open-source LLMs) in production environments where runaway loops, unsafe actions, or escalating costs are unacceptable.
Failure pattern library
Documented failure modes for production AI agents
Infinite Loops
Agent keeps calling the same tool without termination
Prompt Injection
User input hijacks agent instructions
Tool Misuse
Agent calls tools with invalid or dangerous parameters
Context Overflow
Agent loses track of conversation state
Guardrail tools
Interactive tools for AI agent reliability engineering
Articles
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How to Stop AI Agents from Looping Forever: Guardrails & Stop Rules
Stop AI agents from calling the same tool repeatedly in production. Learn retry budgets, loop detection, human-in-the-loop escalation, idempotency keys, and guardrails that prevent runaway token costs and duplicate side effects. Code examples included.
PyTorch Training Workflow: Best Practices for Efficient Model Development
Learn how to structure and optimize your PyTorch training workflow. This guide covers dataset preparation, defining models, training loops, evaluation, and essential b…
Building Image Recognition Models with ML.NET: From Pixels to Predictions
Discover how to build powerful image recognition models using ML.NET. This comprehensive guide covers everything from data preprocessing and model training to deployme…
Resources
Free downloads and runbooks
More resources coming as the agent guardrails library grows.
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