Tag: AI safety
How to Build a Durable Change-Control Gate for AI Agents
Daniel Martin | | agentic AI, AI agents, AI automation, AI Governance, AI safety, approval workflows, change control, devops, durable workflows, human-in-the-loop, idempotency, LangGraph, NIST AI RMF, policy enforcement, production deployment, release controls, tool-using agents, workflow governanceAI agents that trigger real-world changes need more than confidence scores. A durable change-control gate should recheck policy, require approval for consequential actions, enforce idempotency and verify the result before retrying ...
Anthropic Makes Claude Code’s Auto Mode the Default, Betting Automation Beats Manual Review
Tom Smith | | agent permissions, agentic coding, AI code generation, AI coding agents, AI Governance, AI guardrails, AI permissions, AI safety, AI security, Anthropic, autonomous coding agents, Claude Code, Claude Code auto mode, Claude Code security, coding automation, developer productivity, developer tools, human engineering the loop, human-in-the-loop, permission fatigue, prompt injection, Pull Request Automation, secure AI agents, software development, software engineeringAnthropic is making Claude Code’s auto mode the default for Pro, Max and Team users, replacing constant permission prompts with classifier-based guardrails designed to catch risky actions without slowing developers down ...
The Death of the Four Golden Signals: Designing Telemetry for Non-Deterministic Infrastructure
Jyostna Seelam | | AI architecture, AI compliance, AI Governance, AI guardrails, AI infrastructure, AI monitoring, AI observability, AI operations, AI operations strategy., AI performance metrics, AI platform monitoring, AI reliability, AI resilience, AI safety, AI SLIs, AI SLOs, AI system reliability, AI telemetry, AI trust, Enterprise AI, generative AI monitoring, guardrail intervention rate, hallucination detection, LLM monitoring, LLM observability, modern SRE, non-deterministic systems, Observability Engineering, OpenTelemetry, platform engineering, production AI, RAG observability, RAG systems, semantic drift, site reliability engineering, SRE, time to first token, token throughput, TTFT, vector database monitoringIn complex software systems, our traditional definition of operational health has always been comfortably binary. For over a decade, site reliability engineering (SRE) teams have relied on the industry-standard ‘Four Golden Signals’ ...
When AI Goes Really, Really Wrong: How PocketOS Lost All Its Data
Steven J. Vaughan-Nichols | | AI agent, AI coding agent, AI safety, Anthropic, Anthropic Claude, autonomous agents, backups, Claude, Cloud Security, Cursor, data loss, PocketOS, RailwayYou can't make this crap up. You just wish you could. Jer Crane, founder of the small vertical software company, PocketOS, reported on X that the AI Cursor coding agent and a ...
