Blog
Engineering insights into AI execution governance.
Why LLM-Based Guardrails Will Always Fail: The Guardrail DoS Problem
Security researchers proved that poisoned documents can trap LLM-based guardrails in 148x slowdown thinking loops. Why deterministic governance is the only fix.
How to Stop LLM Unauthorized Executions in Production
Why RAG and prompt engineering fail to prevent destructive tool calls—and the infrastructure required to actually fix it.
LangChain Enterprise Security: Orchestration ≠ Governance
LangChain is brilliant at orchestration, but devoid of native execution governance. Here is how to secure your AgentExecutors in production.
CrewAI vs AutoGen for Production
Comparing the two leading multi-agent frameworks. Which orchestration model scales best, and why both are inherently unsafe without external governance.
Enterprise compliance for AI Agents: The Engineering Guide
Why traditional IAM falls apart when non-human entities execute code, and how to build cryptographic audit trails to satisfy Enterprise-grade requirements.
The Verification Penalty: Why Human-in-the-Loop AI is a Bridge to Nowhere
The hidden labor cost of human-in-the-loop AI systems. Why advisory AI fails to deliver workflow automation ROI and how to achieve safe autonomous execu...
The Origin Story: Zero Trust for AI Execution
An inside look at why existing AI agent frameworks lack an execution boundary, and how Exogram provides deterministic tool call governance.