Microsoft Imagines An ‘Agentic Web’ Where AI Systems Collaborate & Remember
To make this interoperability a reality, Microsoft is throwing its support behind the Model Context Protocol (MCP).
As the AI race accelerates, Microsoft is laying out a bold vision: a connected ecosystem where artificial intelligence agents from different companies not only collaborate seamlessly but also remember past interactions to serve users more intelligently. This ambitious goal was unveiled by Microsoft’s Chief Technology Officer Kevin Scott ahead of the company’s flagship Build 2025 developer conference in Seattle, which kicks off on May 19.
A Common Language for AI Agents
Speaking to journalists and analysts at Microsoft’s Redmond headquarters, Scott emphasised the need for industry-wide standards that would allow AI agents — systems designed to perform specific tasks autonomously — to work together across platforms. These agents could be tasked with anything from debugging code to organising meetings, and Microsoft wants them to communicate as easily as browsers handle hyperlinks.
To make this interoperability a reality, Microsoft is throwing its support behind the Model Context Protocol (MCP) — an open-source initiative originally introduced by Anthropic, a company backed by Google. Scott drew parallels between MCP and the hypertext protocols that fueled the rise of the web in the 1990s.
“It means that your imagination gets to drive what the agentic web becomes, not just a handful of companies that happen to see some of these problems first,” said Scott.
The aim is to democratize AI development by enabling diverse AI systems to plug into a shared “agentic web,” potentially reshaping how digital assistants and task-specific bots function in the enterprise and consumer space.
Giving AI a Better Memory
Another key challenge Microsoft is tackling is how AI agents remember — or more often, forget — user interactions. As it stands, most AI conversations are “very transactional,” Scott noted, lacking any meaningful memory of prior tasks or context.
Microsoft hopes to change that through a method called structured retrieval augmentation. This technique involves capturing and storing small, relevant pieces of each user interaction, which together form a coherent roadmap of the conversation. Instead of forcing the AI to recall everything from scratch, this roadmap acts as a memory scaffold, improving the agent’s ability to learn from and adapt to a user’s past behaviour.
“This is a core part of how you train a biological brain – you don't brute force everything in your head every time you need to solve a particular problem,” explained Scott.
Balancing Innovation and Infrastructure Costs
While the benefits of smarter, more collaborative AI agents are clear, Scott acknowledged the cost barrier that comes with improving AI memory. Enhancing an agent’s recall abilities means increasing the computational load, which can be expensive at scale. Microsoft is working to make these systems more efficient without compromising on performance.
With Build 2025 just around the corner, the company is expected to unveil a range of new tools aimed at helping developers create next-generation AI systems rooted in these principles. If Microsoft’s vision pans out, we may be heading into an era where AI agents not only work harder, but work together and remember why.
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