The AI Control Plane Is Becoming the New Shadow IT

<p>The request arrives. The model answers. For most teams, everything in between is invisible — a gateway rule, a load balancer entry, maybe a classifier someone wrote three

<p>The interesting part of OpenAI and Codex on AWS is not that another cloud menu got more model names.</p> <p>That part is useful. Enterprises want strong models. Developers want

Many employees already use shadow AI tools at work without security review. Adaptive Security breaks down how teams can build practical AI governance without adding friction for

The first wave of enterprise AI concern was straightforward. It was simply employees pasting sensitive data into public AI tools. Security teams responded with usage policies,

arXiv:2604.05229v1 Announce Type: new Abstract: Agentic AI systems plan, use tools, maintain state, and produce multi-step trajectories with external effects. Those properties

<h2> The Hidden Tax on Every MCP Request </h2> <p>Here is something nobody talks about when they demo MCP integrations: token costs at scale.</p> <p>I have been running MCP setups

<p>Hosted agent runtimes are making a lot of infrastructure feel like a solved problem.</p> <p>Long-running sessions, context compaction, tool execution, sandboxes, and subagent

<!-- SC_OFF --><div class="md"><p>Had a lot of conversations recently about agentic control planes and seen a lot of confusion so wanted to quickly provide an overview of what an