Guardrails
Guardrails on Beyond Market Intelligence: a running collection of 2 stories we have gathered and hand-picked because they are worth your time. Every post here touches on guardrails in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around guardrails, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Brex built its AI agent policy by watching what agents actually do, not by writing rules first
Brex addressed a critical challenge in agent security by observing actual agent behavior rather than relying on predefined rules. Recognizing that traditional guardrails struggle to contain agents wielding real-world credentials like API keys, they developed CrabTrap, an open-source HTTP/HTTPS proxy. This innovative platform uses an LLM-as-a-judge to evaluate network requests, learning from real-time agent activity to enforce policies. This approach, detailed further in "The agent security gap," represents a shift towards centralized network control and empowers organizations to confidently deploy AI agents.
Amazon AGI director says AI agent reliability, not capability, is blocking enterprise deployment at VB Transform 2026
Amazon AGI director Bryan Silverthorn identifies a critical obstacle to enterprise AI agent deployment: reliability, not simply capability. Addressing VentureBeat's Transform 2026 audience, Silverthorn highlighted a concerning trend—85% of enterprises pilot AI agents, yet only 5% reach production. He proposes a framework of consistency, robustness, predictability, and safety to measure agent performance, noting that many agents excel in internal evaluations but falter in real-world use. Ultimately, successful deployment hinges on strong management practices, not just advanced models.