The digital landscape is on the cusp of a transformation not seen since the advent of the World Wide Web, and at the epicenter of this change stands Microsoft, reimagining how humans and computers interact. During Build 2025, CTO Kevin Scott described this pivotal moment as a new “golden age of building”—an era defined not just by smarter AI, but by the emergence of “agentic” software. This evolving concept has profound implications for developers, businesses, and end-users alike, promising a re-architected web shaped by intelligent agents that do more than passively serve up information.
Microsoft’s agentic web is not a whimsical phrase but a technologically grounded vision where AI agents aren’t just features—they’re the foundation of digital engagement. These agents interact, reason, and evolve, embedded deeply into the very structure of the web. Kevin Scott’s analogy to the early days of hypertext protocols underscores the ambition: just as the HTTP protocol enabled the explosion of the internet in the 90s, Microsoft’s Model Context Protocol (MCP) and other open standards could similarly enable a network that is as readable for agents as it is for humans.
The desire, as Scott notes, is to “build a web for AI agents,” allowing them to connect, collaborate, and operate across services just as humans traverse websites today. For this vision to materialize, AI agents need more than powerful models—they demand memory, context awareness, security, and the capacity to reason over time.
Perhaps most notable is the scale of AI model choice now available. With over 1,900 models—including the latest iterations such as Grok 3 and its compact variant from xAI—developers can fine-tune their stack to precise requirements for quality, speed, and cost. A new leaderboard and smart router facilitate optimal model selection. The router, according to Microsoft, provided up to 60% cost savings with comparable accuracy to direct invocation of flagship models like GPT-4.1. While cross-verification from multiple vendors remains limited as these features roll out, early enterprise feedback from Build demonstrations corroborated such figures, though the usual caveats about workloads and contexts apply.
Scott compares MCP to HTTP in its universality—highlighting that the protocol’s simplicity and ubiquity are crucial for agentic computing to scale industry-wide. Early technical documentation indicates MCP is REST-like, designed to securely expose resources and service endpoints for agent access. This focus on interoperability ensures developers—regardless of their preferred infrastructure—can participate in building the agentic web, sidestepping platform lock-in that could otherwise stifle innovation.
Early previews of MCP’s integration into Windows 11 hint at a future where personal computers are not just endpoints for agent consumption, but hubs for agentic orchestration across local and cloud resources. This layered approach—spanning OS, cloud, and even IoT edge—is a pivot from single-application use cases to pervasive, distributed intelligence.
The analogy Scott’s team draws to HTML is apt: just as HTML made content universally discoverable and traversable by browsers, NLWeb is envisioned to do the same for AI agents, transforming the web into a vast, interconnected, and machine-readable ecosystem.
Early pilot projects showcased at Build illustrated scenarios where customer support, internal documentation, or e-commerce inventories become instantly accessible to both human and machine consumers. Initial developer feedback praised the simplicity (with integration times measured in hours rather than weeks), though questions remain about long-term performance, privacy guarantees, and the robustness of open-source governance.
In agentic systems, the challenge is exacerbated by information fragmentation and the difficulty in aggregating long-term context across disparate interactions. Microsoft’s roadmap highlights work on neural memory architectures, persistent agent state, and decentralized storage to address these issues. Industry-wide, related research initiatives (such as vector databases and knowledge graphs) parallel these efforts, but the maturity and real-world impact of such systems still require careful scrutiny.
Azure AI Foundry touts security and trust as foundational design principles. This stance is bolstered by Microsoft Entra Agent ID, now in public preview, which offers a unified directory of AI agent identities—regardless of whether agents are created through Copilot Studio, Azure AI Foundry, or Microsoft Security Copilot. By centralizing identity management, Microsoft hopes to empower IT admins and security teams with the visibility and controls needed to prevent abuse, manage permissions, and ensure compliance.
Initial documentation and executive commentary—particularly from Jay Parikh, Executive Vice President—make clear that this is a generational challenge. As agentic applications evolve, identity management must extend beyond traditional user-centric paradigms to accommodate semi-autonomous actors that blur boundaries between automation, assistance, and agency.
Yet, this golden age of building is not without its risks. The abstraction and connectivity of agentic systems can mask complexity, increasing the likelihood of unintended consequences—from algorithmic biases and privacy leaks to adversarial attacks and systemic instability. While Microsoft’s commitment to protocols, open ecosystems, and in-built security measures is significant, many of these challenges, like memory consistency and agent-to-agent trust, are unsolved research problems as much as engineering tasks.
The immediate future promises a whirlwind of new tools, APIs, and protocols. Enterprises and individual developers alike are encouraged to experiment with Azure AI Foundry, test out NLWeb, and join the public previews of MCP and Entra Agent ID. As Scott suggests, the imagination of today’s builders will determine what the agentic web becomes, not a select few firms or foundations.
But imagination alone is not enough. It must be matched by vigilance, transparency, and ongoing dialogue among technologists, policymakers, and users. Only then can the promise of this new golden age be fully realized—offering agency not just to machines, but to the humans at the center of digital life.
Source: Analytics India Magazine “Wish I Were 25 Again,” Microsoft CTO on the Golden Age of Building | AIM
The Agentic Web: Microsoft’s Vision of a Connected Digital Future
Microsoft’s agentic web is not a whimsical phrase but a technologically grounded vision where AI agents aren’t just features—they’re the foundation of digital engagement. These agents interact, reason, and evolve, embedded deeply into the very structure of the web. Kevin Scott’s analogy to the early days of hypertext protocols underscores the ambition: just as the HTTP protocol enabled the explosion of the internet in the 90s, Microsoft’s Model Context Protocol (MCP) and other open standards could similarly enable a network that is as readable for agents as it is for humans.The desire, as Scott notes, is to “build a web for AI agents,” allowing them to connect, collaborate, and operate across services just as humans traverse websites today. For this vision to materialize, AI agents need more than powerful models—they demand memory, context awareness, security, and the capacity to reason over time.
Unpacking Microsoft’s Agentic Stack: Azure AI Foundry and MCP
At the heart of this shift is Azure AI Foundry, Microsoft’s answer to the complexities facing today’s developers. The platform promises a robust foundation for creating, deploying, and orchestrating AI agents and traditional applications, both in the cloud and at the edge.Streamlined Lifecycle, Massive Scale
The latest updates to Azure AI Foundry introduce a comprehensive toolkit: streamlined model selection, intuitive fine-tuning, seamless deployment, and holistic monitoring—all accessible through integrations with Visual Studio Code, GitHub workflows, and rapid-start templates. Microsoft claims that this approach can reduce the time from idea to deployment from weeks to mere minutes—an assertion that, while ambitious, is backed by the increasing sophistication of modern developer experience (DX) tooling.Perhaps most notable is the scale of AI model choice now available. With over 1,900 models—including the latest iterations such as Grok 3 and its compact variant from xAI—developers can fine-tune their stack to precise requirements for quality, speed, and cost. A new leaderboard and smart router facilitate optimal model selection. The router, according to Microsoft, provided up to 60% cost savings with comparable accuracy to direct invocation of flagship models like GPT-4.1. While cross-verification from multiple vendors remains limited as these features roll out, early enterprise feedback from Build demonstrations corroborated such figures, though the usual caveats about workloads and contexts apply.
The Nuts and Bolts: MCP and Agent-To-Agent Protocols
Integral to this ecosystem are the Agent-to-Agent (A2A) protocol and the Model Context Protocol (MCP). A2A allows for seamless agent collaboration, while MCP provides a standardized means for agents to communicate, reason, and interact over various services and content sources.Scott compares MCP to HTTP in its universality—highlighting that the protocol’s simplicity and ubiquity are crucial for agentic computing to scale industry-wide. Early technical documentation indicates MCP is REST-like, designed to securely expose resources and service endpoints for agent access. This focus on interoperability ensures developers—regardless of their preferred infrastructure—can participate in building the agentic web, sidestepping platform lock-in that could otherwise stifle innovation.
Early previews of MCP’s integration into Windows 11 hint at a future where personal computers are not just endpoints for agent consumption, but hubs for agentic orchestration across local and cloud resources. This layered approach—spanning OS, cloud, and even IoT edge—is a pivot from single-application use cases to pervasive, distributed intelligence.
NLWeb: Making Every Website AI-Accessible
Microsoft’s open-source NLWeb project serves as another crucial pillar. Acting as a “natural language layer” above any website, NLWeb empowers developers to make their site’s content queryable through AI-driven natural language prompts. More than an interface convenience, each NLWeb deployment doubles as an MCP server, automatically exposing site content to the agentic web.The analogy Scott’s team draws to HTML is apt: just as HTML made content universally discoverable and traversable by browsers, NLWeb is envisioned to do the same for AI agents, transforming the web into a vast, interconnected, and machine-readable ecosystem.
Early pilot projects showcased at Build illustrated scenarios where customer support, internal documentation, or e-commerce inventories become instantly accessible to both human and machine consumers. Initial developer feedback praised the simplicity (with integration times measured in hours rather than weeks), though questions remain about long-term performance, privacy guarantees, and the robustness of open-source governance.
Memory, Context, and the Challenge of Agent Recall
Despite all technical advancements, Kevin Scott identifies “memory” as the single most conspicuously missing quality in today’s AI agents. Current systems, even large language models, typically operate with limited context windows—a constraint leading to transactional, ahistorical interactions. The analogy Scott draws to biological memory is instructive: human recall is imperfect but “broad,” enriched by cognitive tools and an ability to learn from patterns over time.In agentic systems, the challenge is exacerbated by information fragmentation and the difficulty in aggregating long-term context across disparate interactions. Microsoft’s roadmap highlights work on neural memory architectures, persistent agent state, and decentralized storage to address these issues. Industry-wide, related research initiatives (such as vector databases and knowledge graphs) parallel these efforts, but the maturity and real-world impact of such systems still require careful scrutiny.
Security and Trust by Design
Security is a recurring theme across Microsoft’s narrative. The scale and autonomy of agentic systems make them both attractive and risky: agents capable of browsing, orchestrating workflows, or transacting on a user’s behalf must operate within secure, well-governed boundaries.Azure AI Foundry touts security and trust as foundational design principles. This stance is bolstered by Microsoft Entra Agent ID, now in public preview, which offers a unified directory of AI agent identities—regardless of whether agents are created through Copilot Studio, Azure AI Foundry, or Microsoft Security Copilot. By centralizing identity management, Microsoft hopes to empower IT admins and security teams with the visibility and controls needed to prevent abuse, manage permissions, and ensure compliance.
Initial documentation and executive commentary—particularly from Jay Parikh, Executive Vice President—make clear that this is a generational challenge. As agentic applications evolve, identity management must extend beyond traditional user-centric paradigms to accommodate semi-autonomous actors that blur boundaries between automation, assistance, and agency.
A Golden Age, Not Without Challenges
Kevin Scott’s offhand wish to “be 25 again” captures the excitement and promise of this era. For a new generation of builders, the tools, protocols, and platforms on offer dwarf even the leaps enabled by Moore’s law decades ago. The anecdote of Scott’s daughter and her friends developing a working app without any traditional coding mirrors a broader democratization underway. With low-code and no-code interfaces, paired with robust AI backends, the ability to create meaningful software is coming within reach for millions previously sidelined by the technical barriers of classic programming.Yet, this golden age of building is not without its risks. The abstraction and connectivity of agentic systems can mask complexity, increasing the likelihood of unintended consequences—from algorithmic biases and privacy leaks to adversarial attacks and systemic instability. While Microsoft’s commitment to protocols, open ecosystems, and in-built security measures is significant, many of these challenges, like memory consistency and agent-to-agent trust, are unsolved research problems as much as engineering tasks.
Critical Analysis: Strengths, Opportunities, and Open Questions
Notable Strengths
- Open Protocols and Ecosystem Play: By designing MCP and advocating for ubiquitous, open standards, Microsoft avoids the perils of lock-in and fosters innovation ecosystem-wide. This mirrors the early web’s success with universal standards.
- Integration and Scalability: Azure AI Foundry’s integration with the wider Microsoft stack (VS Code, GitHub, Bing, SharePoint) provides instant scale and familiarity, boosting developer productivity and adoption.
- Security-First Identity Management: Entra Agent ID, with its holistic approach to managing synthetic agentic identities, sets a precedent for responsible agent deployment at scale.
- Developer Experience: With quick-start templates and existing toolchain integration, Microsoft eliminates much of the historical friction from ideation to deployment—a clear productivity win.
Potential Risks and Unanswered Questions
- Memory and Context Limitations: The lack of persistent, broad agentic memory remains an unsolved problem, risking transactional (rather than transformative) interactions.
- Security by Complexity: The interconnected nature of agentic systems increases attack surfaces and demands new paradigms for authentication, authorization, and auditability. Legacy approaches may not suffice.
- Governance and Privacy: As agents traverse and interconnect ever more datasets, robust privacy guardrails and open governance models become essential. The opacity of complex agent chains could hide bias, leakage, or even malicious activity.
- Standards Fragmentation: While openness is emphasized, history shows multiple competing “open” standards can proliferate, splintering the ecosystem and hindering ubiquity.
- Democratization vs. Control: As the power to build software is democratized, so too is the risk of accidental (or intentional) harm from poorly governed, widely distributed agents. Enforcement mechanisms are needed, but risk stifling openness and innovation.
The Road Ahead: An Evolving Digital Social Contract
Microsoft’s actions at Build 2025 make clear that the agentic web is both a technical project and a profoundly social one. The analogy to the early web rings true: enabling a generation of developers and users to imagine, construct, and benefit from a new kind of online experience. If openness, accessibility, and security prevail, this transformation could rival—if not surpass—the impact of the original World Wide Web.The immediate future promises a whirlwind of new tools, APIs, and protocols. Enterprises and individual developers alike are encouraged to experiment with Azure AI Foundry, test out NLWeb, and join the public previews of MCP and Entra Agent ID. As Scott suggests, the imagination of today’s builders will determine what the agentic web becomes, not a select few firms or foundations.
But imagination alone is not enough. It must be matched by vigilance, transparency, and ongoing dialogue among technologists, policymakers, and users. Only then can the promise of this new golden age be fully realized—offering agency not just to machines, but to the humans at the center of digital life.
Source: Analytics India Magazine “Wish I Were 25 Again,” Microsoft CTO on the Golden Age of Building | AIM
