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News
Real-Time AI Guardrails on the TrueFoundry Gateway
3+ hour, 1+ min ago (555+ words) That raises the question most platform teams are asking right now: how do you validate every prompt and every response your AI produces without turning safety into an engineering project of its own? Today we're answering it. Arthur now integrates…...
Toxicity Detection for Agents: Context Matters
1+ week, 3+ day ago (848+ words) An unsafe output reaching a user is a trust failure, and trust in AI agents is already fragile. One bad response at the wrong moment can permanently change how someone thinks about your product. So teams reach for a toxicity…...
Supervised vs. Unsupervised Evals for AI Agents
2+ week, 6+ day ago (603+ words) Best Practices for Building Agents Recap | READ HERE If you are evaluating an AI agent, the first decision you make is not which metric to track. It is whether your eval has access to a known correct answer. That single…...
OpenInference vs OpenTelemetry GenAI for Agent Tracing
1+ mon, 2+ day ago (659+ words) Best Practices for Building Agents Series | READ HERE When teams set up observability for AI agents, they usually focus on two decisions: which tracing library to instrument with, and which backend to send traces to. There's a third decision sitting…...
Self-Correction Loops for AI Agents, Explained
1+ mon, 2+ day ago (576+ words) Best Practices for Building Agents Series | READ HERE Most teams treat guardrails as a binary filter. A response either passes or it gets blocked. When it gets blocked, the user sees an error, or someone gets pulled in to review…...
Agent Development Toolkit | Build, Test & Monitor AI Agents
3+ mon, 2+ week ago (434+ words) Best Practices for Building Agents | Part 5: Guardrails | READ HERE An open-source toolkit for building, testing, and monitoring AI agents in production. Keep prompts versioned, tagged, and promotable across environments. Roll back in seconds when something regresses. Test prompt changes, model…...
From Scattered Tools to a Unified Agent Command Center: A New Way to Scale AI Systems
3+ mon, 3+ week ago (698+ words) Best Practices for Building Agents | Part 4: Experiments & Supervised Evals | READ HERE Your team builds agents. Your agents work. But understanding what they're doing? That's where things get messy. You're clicking through five different screens to trace a single conversation. Your…...
LiteLLM Supply Chain Attack: What AI Teams Need to Know Now
3+ mon, 3+ week ago (265+ words) Best Practices for Building Agents | Part 4: Experiments & Supervised Evals | READ HERE On March 24, 2026, LiteLLM, a Python package with over 95 million monthly downloads used by AI teams to route calls across LLM providers — was compromised in a supply chain attack. A…...
Managing AI Agent Sprawl: Governance That Scales
4+ mon, 2+ day ago (598+ words) Best Practices for Building Agents | Part 4: Experiments & Supervised Evals | READ HERE Enterprises don't suffer from too little AI, they struggle with too many agents - both known and unknown - running without robust oversight. As autonomous systems scale across teams, cloud environments,…...