Why Agentic AI Development Needs Reliability Guardrails
Agentic AI is dramatically accelerating code production, with GitHub projecting a 30‑fold increase in capacity needs. However, AI‑generated code introduces 1.7 × more defects per pull request, including 1.4 × more critical issues, raising reliability concerns. Experts recommend implementing programmatic reliability guardrails—particularly fault‑injection tests—as a CI/CD gate to catch failures before release. A core set of six tests can address the majority of common outage causes while keeping deployment speed.
The Hidden Reliability Risks in Your Agentic AI Workflows
Artificial intelligence has moved from conversational assistants to autonomous agents that act on behalf of enterprises, introducing new reliability challenges. The article highlights three primary risks: unstable network connections, cascading dependency failures, and the non‑deterministic nature of model outputs. It...
How Gremlin Makes Disaster Recovery Testing Easier and Faster
Gremlin has introduced a Disaster Recovery Testing feature that lets organizations simulate catastrophic failures across all services with a few clicks. The tool builds on pre‑built test suites to establish baseline reliability scores, then supports regular weekly testing of individual...