by CPI Staff | Oct 19, 2026 | AI Agents, AI Governance & Risk Management, Blog, Microsoft Agent Framework
In this blog post Microsoft Agent Framework Release Cadence and Version Governance we will explain how to keep production AI agents stable while Microsoft continues to release new features, fixes and security improvements. The problem is familiar. An AI agent works...
by CPI Staff | Oct 17, 2026 | AI Agents, AI Governance & Risk Management, Blog, Microsoft Agent Framework
In this blog post Microsoft Agent Framework Release and Upgrade Governance Guide we will explain how to adopt frequent framework updates without turning every release into a production risk. The problem is familiar. Your AI agent works today, a new framework version...
by CPI Staff | Oct 15, 2026 | AI Agents, AI Governance & Risk Management, Blog, Microsoft Agent Framework
In this blog post Microsoft Agent Framework Python 1.21 and .NET 1.24 Readiness we will explain what the October releases mean for organisations trying to move AI agents beyond pilot projects. Many businesses now have an agent that works in a demonstration, but they...
by CPI Staff | Oct 15, 2026 | AI Governance & Risk Management, Blog, Microsoft Agent Framework, Microsoft Purview
In this blog post How to Guard Streaming AI Agents with Microsoft Purview Policies we will explain how to stop sensitive information escaping while an AI agent sends its answer to a user in real time. Streaming makes an AI assistant feel fast because words appear as...
by CPI Staff | Oct 12, 2026 | AI Agents, AI for Business & AI Strategy, Blog, Microsoft Agent Framework
In this blog post What New Microsoft Agent Framework Releases Mean for Enterprise AI we will explain how Microsoft’s latest updates affect the way organisations should design, secure and operate AI agents. Many businesses now have an AI assistant that works well in a...
by CPI Staff | Oct 12, 2026 | AI Agents, Azure Monitor, Blog, Microsoft Agent Framework
In this blog post How to Operationalise Microsoft Agent Framework in Production we will show why an agent that performs well in a demonstration can still become slow, expensive or unreliable once employees depend on it. The real challenge is not getting an answer from...
