Where Zero Trust meets agentic AI runtime
TealTiger is a developer-first runtime governance SDK for agentic AI. This blog shares practical patterns, reference architectures, and hard lessons—from zero trust to blast-radius control.
Latest posts
-
Why Runtime Enforcement Beats Static Evaluation
Executive summary
-
Cost Is a Security Boundary in AI Systems
Most teams treat LLM costs as an optimization problem: reduce tokens pick a cheaper model cache more compress prompts
-
Zero Trust for Agentic AI: Runtime Verification, Not Network Slogans
Traditional Zero Trust works well for people and services accessing systems. Agentic AI breaks that model—because the risk is no longer just who is acting, but what an agent is about to do.
-
Why Prompt-Only Guardrails Fail in Production
Prompt engineering is powerful. Prompt engineering is useful. Prompt engineering is not enforcement.
-
Logging Is Not Governance
Executive summary
-
Blast-Radius Control for AI Agents
If you are building agentic AI systems, one truth becomes unavoidable very quickly:
``