Microsoft shipped a new Agent Framework this week, merging Semantic Kernel and AutoGen into one open-source SDK for .NET and Python. The framework supports MCP for tool discovery, A2A for cross-runtime messaging, and OpenAPI integration, with a path to Azure AI Foundry for managed hosting. Meanwhile in a press release entitled “vibe working” Copilot Agent Mode arrived including in Excel and Word, bringing multi-step workflows to Microsoft 365, though only via web apps and gated through the Frontier early-access programme for now. Excel Agent Mode scored 57.2% on SpreadsheetBench compared to 71.3% for humans. This feature essentially brings the pro-active style mode from ChatGPT and pairs it with the files and tools on the 365 platform.
Somewhat frustratingly the launch pattern here is familiar. Microsoft announces, the business tech press covers it, but availability is not immediate. Agent Mode requires special access. Desktop app roll-out and parity is unclear. Frustratingly we’ve seen this before with Copilot features that took months to reach general availability by which time competitors have evolved. But these releases really do matter; Microsoft’s platforms constrain how millions of businesses adopt AI. Copilot is embedded across Office, Teams, and Windows. Semantic Kernel and now the unified Agent Framework shape what developers can build. If Microsoft gets this agentic package right, they unlock agentic AI for 300 million paying seats and countless more users of Azure hosted products. If they continue to fumble, they will continue to be a major bottleneck.
The agent framework itself looks like solid engineering. Unified SDK, open protocols, good observability, slick builder UI. But Copilot still lacks the capabilities that make Claude or other agent platforms compelling, like fully enabled long-form reasoning, sophisticated tool use, and long-running multi-turn task completion. The Office agents still feel fragmented and most of the millions of users wouldn’t have a clue what they can or can’t do. Solid document sourcing, security, approvals and other guardrails are there, but the impact still feels underwhelming.
Microsoft needs to go faster; ship software with desktop parity, stick to timelines, and make their products capabilities much clearer. They need to listen to real usage and adapt more quickly. The global economy won’t be “unleashed” by frameworks alone, or compute and data centres, but with truly usable tools that need to come soon (or new AI-native entrants such as Gamma could start to make inroads in Microsoft’s work platform dominance).
Takeaways: Microsoft operates within a unique position of constraint and opportunity. With nearly half-a-billion users, they could accelerate business AI adoption at an unprecedented rate if they got the formula right. This does require a mix of development tools and products as we have seen this week. This also requires actually shipping software to all users, maintaining open protocols, and taking a leap beyond Copilot catch-up. When will a Microsoft AI product be copied somebody else?