At Microsoft’s highly anticipated Build 2025 developer conference, the company delivered a barrage of announcements pointing to a new direction for the web, developer tools, and productivity platforms. Central to this vision is the emergence of the “open agentic web,” where artificial intelligence agents take on active, autonomous roles—not merely assisting users, but making real-world decisions and taking actions on their behalf. As Satya Nadella, Microsoft Chairman and CEO, outlined during his keynote, these developments are poised to fundamentally reshape both how software is built and how end-users interact with information, productivity tools, and the broader internet.
For years, much of the conversation around generative AI focused on conversational assistants: tools like Copilot, ChatGPT, and Google Gemini that answer questions, draft content, or support routine tasks. Build 2025 signals an acceleration beyond this paradigm. Microsoft’s latest offerings are agentic by design—capable not just of giving advice but of acting autonomously based on user intent, organizational rules, and contextual awareness.
This leap in capability is enabled by advances in underlying models, integration with repository context, and GitHub’s proprietary orchestration logic. Early demonstrations indicate tasks such as triaging and fixing mundane bugs, updating dependencies, or refactoring codebases can proceed in the background, freeing up human developers for higher-value architectural or creative work.
Yet, Microsoft is careful to stress the necessary guardrails: human-in-the-loop review remains vital for quality and safety. “Delegation is not abdication,” one engineer commented in a technical session, indicating that Copilot’s output—while impressive—should remain subject to code review for correctness and potential security issues. This dual-layer approach balances autonomy with control, a theme echoed throughout Build 2025.
The tuning process leverages a company’s internal datasets, preferred collaborations, and real-world workflows. For example, a legal firm might build an agent that drafts contracts in the firm’s established style, referencing both industry regulations and internal precedents. Users provide sample data and a few configuration choices; Copilot Tuning abstracts away the complexity of training, hosting, and maintaining the custom AI model.
Notably, all tuning occurs securely within the organization’s Microsoft 365 environment. Microsoft emphasizes that data does not leave the customer’s service boundary, an important point for regulated industries handling sensitive information. Early partner pilots are underway in healthcare, legal, and financial services, with Microsoft promising broader availability in the coming months.
Cross-referencing information from both Microsoft’s own Build 2025 documentation and xAI’s recent press releases confirms that Grok 3 is among the most powerful open models currently available, boasting performance on par with—if not above—current GPT-4 class models in several benchmarks. Integration into Azure Foundry allows enterprises to tap into Grok’s capabilities with the peace of mind and compliance features Azure is known for.
Further, a new Model Router handles dynamic selection in real time. When an agent receives a new task, the Model Router analyzes the nature of the request and automatically chooses the model best suited to respond—whether that’s for translation, code generation, creative writing, or complex math. This moves away from a one-model-fits-all approach and ensures organizations get the specialist performance they need.
Another innovative feature is Microsoft Entra Agent ID—a capability in preview that assigns unique, verifiable digital identities to every agent created in Copilot Studio or Azure AI Foundry. This means that, for the first time, organizations gain fine-grained visibility and policy control: an HR helpdesk agent can be granted access only to personnel records, for instance, while a sales automation agent gets scoped to CRM data. This reduces risk and makes AI adoption auditable—a requirement in sectors like healthcare and finance.
Websites adopting NLWeb endpoints essentially expose structured, conversational interfaces to both users and AI agents. For example, a travel booking site could offer not just a form, but an NLWeb endpoint, allowing an AI agent to negotiate itinerary changes, book tickets, or request refunds via natural language APIs.
Critically, every NLWeb endpoint operates as an MCP (Multi-Agent Control Protocol) server, facilitating standardized, discoverable access for agents across the web. This fosters a future where intelligent agents—whether operated by users, organizations, or third parties—can seamlessly transact, retrieve information, and perform tasks on behalf of their humans, all in a secure, auditable way.
Microsoft’s vision is bold, but it does not stand alone. Similar agentic web infrastructure is being proposed by other major players, including OpenAI, Google, and independent startups. However, Microsoft’s bet on integrating NLWeb directly into the broader Microsoft ecosystem (including Edge, Bing, and the Office family) gives it a major distribution advantage.
Microsoft Discovery promises to help research teams automate literature review, simulate experimental outcomes, identify promising development routes, and even draft documentation or regulatory submissions. Critical to its rollout is extensibility: labs can customize Discovery’s agents to address unique industry constraints, compliance concerns, and proprietary datasets.
While much of the detail remains behind closed doors (specifics on model architectures and integration with lab data systems are mostly NDA-bound at this writing), prominent early adopters cited during Build suggest substantial productivity gains. Pharmaceutical researchers, for example, described slashing weeks from preliminary candidate screening—a potentially game-changing acceleration for drug development pipelines.
Organizations considering these new technologies should weigh both the strengths and challenges carefully. Adopting agentic AI, whether for code, research, or the web, offers rare opportunities for velocity, customization, and transformation. Yet, these gains come with a mandate for rigorous oversight, continuous evaluation, and flexible, transparent tooling.
Microsoft's powerful position in cloud, productivity, and platform technologies may give it the front-runner status in the agentic age, but its approach—open agents, transparent evaluation, secure customization—will serve as a litmus test for both technical and ethical progress. If it succeeds, the open agentic web may soon become as foundational as the transition to the cloud or the move to mobile. In this new era, the question for organizations is not whether to deploy AI agents—but rather, when, where, and with what oversight.
As the dust settles from Build 2025, it is clear that the agentic web is no longer a distant vision. It is here, it is actionable, and it is rapidly changing the expectations for software, productivity, and the very fabric of the Internet itself. Now, the challenge and opportunity fall to developers, enterprises, and users: to build the next generation of experiences—secure, vibrant, and powered by smart, responsible agents.
Source: The Tech Outlook Microsoft introduces new AI agents at its Build 2025 event - The Tech Outlook
The Rise of Autonomous AI Agents
For years, much of the conversation around generative AI focused on conversational assistants: tools like Copilot, ChatGPT, and Google Gemini that answer questions, draft content, or support routine tasks. Build 2025 signals an acceleration beyond this paradigm. Microsoft’s latest offerings are agentic by design—capable not just of giving advice but of acting autonomously based on user intent, organizational rules, and contextual awareness.GitHub Copilot Evolves: Introducing the Asynchronous Coding Agent
Copilot, originally conceived as a context-sensitive code-completion tool within the editor, is now recast as something much broader: an intelligent, asynchronous agent integrated directly into the GitHub platform. Developers can now “assign” their Copilot agent complete issues—such as bug fixes, the addition of new features, or ongoing code maintenance. Copilot goes to work autonomously, with the promise of reporting back upon completion, much like delegating to an exceptionally knowledgeable junior developer.This leap in capability is enabled by advances in underlying models, integration with repository context, and GitHub’s proprietary orchestration logic. Early demonstrations indicate tasks such as triaging and fixing mundane bugs, updating dependencies, or refactoring codebases can proceed in the background, freeing up human developers for higher-value architectural or creative work.
Yet, Microsoft is careful to stress the necessary guardrails: human-in-the-loop review remains vital for quality and safety. “Delegation is not abdication,” one engineer commented in a technical session, indicating that Copilot’s output—while impressive—should remain subject to code review for correctness and potential security issues. This dual-layer approach balances autonomy with control, a theme echoed throughout Build 2025.
Copilot Tuning: Domain-Specific AI Without the Hassle
A major hurdle to AI adoption for enterprises has been the challenge of customization. Most out-of-the-box models perform best on general tasks, struggling with company-specific terminology, workflows, and legal or regulatory constraints. Copilot Tuning is Microsoft’s answer—a low-code way for organizations to “tune” AI models and create custom agents directly within the Microsoft 365 boundary.The tuning process leverages a company’s internal datasets, preferred collaborations, and real-world workflows. For example, a legal firm might build an agent that drafts contracts in the firm’s established style, referencing both industry regulations and internal precedents. Users provide sample data and a few configuration choices; Copilot Tuning abstracts away the complexity of training, hosting, and maintaining the custom AI model.
Notably, all tuning occurs securely within the organization’s Microsoft 365 environment. Microsoft emphasizes that data does not leave the customer’s service boundary, an important point for regulated industries handling sensitive information. Early partner pilots are underway in healthcare, legal, and financial services, with Microsoft promising broader availability in the coming months.
Azure AI Foundry: Expanding Capabilities and Model Flexibility
Microsoft reaffirmed Azure’s role as the backbone for enterprise AI, showcasing a significantly upgraded Azure AI Foundry. The Foundry platform brings together tools for model customization, deployment, monitoring, and agent management under a unified developer interface. What’s most notable in this release are three core upgrades:Integration of xAI’s Grok 3 Models
Microsoft and xAI, an Elon Musk-led venture, have deepened their partnership: Grok 3 and Grok 3 Mini, two cutting-edge large language models, now join Foundry’s selection. This addition expands the options for organizations seeking state-of-the-art generative capabilities while maintaining flexibility in model selection.Cross-referencing information from both Microsoft’s own Build 2025 documentation and xAI’s recent press releases confirms that Grok 3 is among the most powerful open models currently available, boasting performance on par with—if not above—current GPT-4 class models in several benchmarks. Integration into Azure Foundry allows enterprises to tap into Grok’s capabilities with the peace of mind and compliance features Azure is known for.
Model Leaderboard and Real-Time Model Routing
To solve the perennial question of “which model is best for which kind of task,” Microsoft has introduced a Model Leaderboard within Foundry. Here, models are scored across a broad array of categories—reasoning, summarization, code, natural language processing, etc.—allowing developers to quickly compare and choose based on empirical results. This transparency is a marked improvement over marketing-heavy model selection, and could drive higher-quality outcomes overall.Further, a new Model Router handles dynamic selection in real time. When an agent receives a new task, the Model Router analyzes the nature of the request and automatically chooses the model best suited to respond—whether that’s for translation, code generation, creative writing, or complex math. This moves away from a one-model-fits-all approach and ensures organizations get the specialist performance they need.
Foundry Observability and Agent Identity
With scale comes complexity: keeping AI deployments compliant, cost-effective, and performant across thousands of intelligent agents requires excellent observability. Azure AI Foundry now ships with built-in metric dashboards tracking not just latency or uptime, but nuanced metrics for performance, quality, cost accountability, and safety—plus detailed tracing of agent activity across time.Another innovative feature is Microsoft Entra Agent ID—a capability in preview that assigns unique, verifiable digital identities to every agent created in Copilot Studio or Azure AI Foundry. This means that, for the first time, organizations gain fine-grained visibility and policy control: an HR helpdesk agent can be granted access only to personnel records, for instance, while a sales automation agent gets scoped to CRM data. This reduces risk and makes AI adoption auditable—a requirement in sectors like healthcare and finance.
Agentic Retrieval in Azure AI Search
A less headline-grabbing but technically consequential enhancement is “agentic retrieval” for Azure AI Search. In standard AI retrieval systems, a model surfaces data in response to prompts; with agentic retrieval, specialized AI agents themselves can perform deep document discovery, iteratively refine search strategies, and synthesize results according to task complexity. It’s a move from “search and respond” to “search, analyze, and act,” unlocking richer, more nuanced answers for researchers and business users alike.NLWeb: Semantic Interfacing for a New Kind of Web
Perhaps the most forward-looking proposal at Build 2025 is the introduction of NLWeb. Microsoft positions NLWeb in a way analogous to the birth of HTML—but whereas HTML made human-readable web pages, NLWeb is about surfacing machine-readable, semantically rich interfaces for the agentic web.Websites adopting NLWeb endpoints essentially expose structured, conversational interfaces to both users and AI agents. For example, a travel booking site could offer not just a form, but an NLWeb endpoint, allowing an AI agent to negotiate itinerary changes, book tickets, or request refunds via natural language APIs.
Critically, every NLWeb endpoint operates as an MCP (Multi-Agent Control Protocol) server, facilitating standardized, discoverable access for agents across the web. This fosters a future where intelligent agents—whether operated by users, organizations, or third parties—can seamlessly transact, retrieve information, and perform tasks on behalf of their humans, all in a secure, auditable way.
Microsoft’s vision is bold, but it does not stand alone. Similar agentic web infrastructure is being proposed by other major players, including OpenAI, Google, and independent startups. However, Microsoft’s bet on integrating NLWeb directly into the broader Microsoft ecosystem (including Edge, Bing, and the Office family) gives it a major distribution advantage.
Microsoft Discovery: Accelerating R&D With Agentic AI
In research and development-heavy industries, the journey from initial idea to final product is slow, costly, and often bottlenecked by data analysis and experiment coordination. With the new Microsoft Discovery platform, Microsoft provides a suite of agentic AI tools designed explicitly to transform this process.Microsoft Discovery promises to help research teams automate literature review, simulate experimental outcomes, identify promising development routes, and even draft documentation or regulatory submissions. Critical to its rollout is extensibility: labs can customize Discovery’s agents to address unique industry constraints, compliance concerns, and proprietary datasets.
While much of the detail remains behind closed doors (specifics on model architectures and integration with lab data systems are mostly NDA-bound at this writing), prominent early adopters cited during Build suggest substantial productivity gains. Pharmaceutical researchers, for example, described slashing weeks from preliminary candidate screening—a potentially game-changing acceleration for drug development pipelines.
Critical Analysis: Strengths, Challenges, and Broader Implications
Microsoft’s announcements at Build 2025 paint a cohesive, ambitious picture of the agentic future. The technical strength is apparent: unified platforms, secure customization, and seamless integration with both cloud infrastructure and productivity suites.Notable Strengths
- Unified, Secure Ecosystem
By tightly coupling agentic AI capabilities within Microsoft 365, Azure, and Github, Microsoft ensures broad reach without sacrificing data security—an essential requirement for regulated customers. Microsoft is explicit in stating that customer data used for Copilot Tuning remains within the organization’s service boundary. - Open Model Choice and Transparent Evaluation
Incorporating external models (such as xAI’s Grok 3) alongside Microsoft’s own, and making model selection empirical via the Leaderboard, offers rare transparency and flexibility. It counters the risk of AI monocultures and “black box” model deployments. - Agent Identity and Compliance-Grade Controls
Assigning unique Entra Agent IDs represents an industry first, enhancing auditability and permissioning. As AI agents take on more autonomous roles, knowing exactly “who” or “what” performed a given action is critical for trust. - Future-Proofing with Semantic Web Standards
The commitment to NLWeb sets the stage for a generational shift in web architecture—not just making sites “AI friendly,” but reimagining web transactions and discovery for a mixed-agent, mixed-human future.
Challenges and Risks
- Over-Autonomization Risks
AI agents that take irrevocable actions without sufficient human oversight may introduce new forms of risk, from accidental data leaks to regulatory violations or catastrophic system errors. While Microsoft advocates a “human-in-the-loop” approach, the temptation for full automation—especially in routine code maintenance, research, or customer support—may prove hard to resist. - Vendor Lock-In and Standards Fragmentation
Microsoft’s ecosystem is vast, and integrating so deeply within its stack has clear benefits—but also risks furthering platform lock-in. If other NLWeb-like protocols are developed by rivals and remain incompatible, users may find themselves siloed by their AI choices. - Opaque Model Customization and Tuning
Copilot Tuning aims to simplify model customization, but enterprises will need to trust that IP, sensitive data, and compliance rules are strictly respected by the black-box tuning process. Microsoft’s promises of security are credible, but ultimately, third-party review and compliance certification of these processes will be necessary. - Unverified Productivity Claims
While early pilots boast significant time-savings (such as pharmaceutical screening going from weeks to days), independent, peer-reviewed studies are still required. The high-stakes domains—like medical research or legal drafting—warrant the utmost scrutiny to ensure that agentic AI is not introducing subtle but significant errors. - Ethical and Regulatory Frontiers
With AI agents acting as autonomous actors, questions arise regarding liability, accountability, and transparency. If an agent creates, deletes, or modifies user data in error who is responsible? Microsoft’s Entra Agent IDs help, but broader policy and regulatory developments will need to keep pace.
Opportunities for Developers and Organizations
For developers, the Build 2025 announcements open up vast fields of opportunity:- Agentic Automation
Routine tasks that sap time can now be delegated, freeing up capacity for engineers, scientists, and analysts to focus on high-value problems. - Custom Business Logic
Through Copilot Tuning and Foundry, organizations can encode unique expertise directly into AI agents, driving outcomes that are tailored and competitive. - Semantic Web Integration
Early adopters of NLWeb stand to gain significant discoverability on the future agentic web; businesses should experiment now to build competitive advantage.
The Road Ahead: From Agents to Ecosystems
Looking beyond the headlines, Microsoft’s Build 2025 signals that the future of work, research, and the web itself will be shaped by collaborations—not just between humans and machines, but between populations of AI agents acting on our behalf.Organizations considering these new technologies should weigh both the strengths and challenges carefully. Adopting agentic AI, whether for code, research, or the web, offers rare opportunities for velocity, customization, and transformation. Yet, these gains come with a mandate for rigorous oversight, continuous evaluation, and flexible, transparent tooling.
Microsoft's powerful position in cloud, productivity, and platform technologies may give it the front-runner status in the agentic age, but its approach—open agents, transparent evaluation, secure customization—will serve as a litmus test for both technical and ethical progress. If it succeeds, the open agentic web may soon become as foundational as the transition to the cloud or the move to mobile. In this new era, the question for organizations is not whether to deploy AI agents—but rather, when, where, and with what oversight.
As the dust settles from Build 2025, it is clear that the agentic web is no longer a distant vision. It is here, it is actionable, and it is rapidly changing the expectations for software, productivity, and the very fabric of the Internet itself. Now, the challenge and opportunity fall to developers, enterprises, and users: to build the next generation of experiences—secure, vibrant, and powered by smart, responsible agents.
Source: The Tech Outlook Microsoft introduces new AI agents at its Build 2025 event - The Tech Outlook