Microsoft Rolls Out February Update for Visual Studio 2026

Microsoft has released its February 2026 update for Visual Studio, delivering a fresh set of improvements across AI assistance, diagnostics, and core developer workflows in the IDE. The latest Visual Studio update continues the platform’s evolution with smarter tools and performance refinements aimed at helping developers stay productive in real-world development scenarios.

Here’s a quick rundown of the newest features designed to make you faster, sharper, and more efficient as a developer:

• Smarter Test Generation with GitHub Copilot

  Generate unit tests for your C# code faster using Copilot. Just type @test in Copilot Chat, describe what you want to validate, and it creates the test code for you — with support for xUnit, NUnit, and MSTest.

• Slash Commands for Custom Prompts

  Access your favorite custom prompts faster using slash commands in Copilot Chat. Type / and your saved prompts appear at the top of the list, marked with a bookmark icon for easy access.

• C++ App Modernization (Public Preview)

  Copilot-powered modernization for C++ is now available in Public Preview. Upgrade your C++ projects to the latest MSVC versions and resolve upgrade-related issues with guided assistance from Copilot.

• DataTips in IEnumerable Visualizer

  Debugging just got easier. You can now use DataTips inside the IEnumerable Visualizer. Hover over any value in the grid to see the full underlying object — the same DataTip experience you’re used to in the editor or Watch window.

• Analyze Call Stack with Copilot

  When debugging pauses, select Analyze with Copilot in the Call Stack window. Copilot reviews the current stack and explains why execution stopped — whether your thread is waiting, looping, or blocked.

• Profiler Agent with Unit Test Support

  The @profiler agent now works with unit tests. Use your existing tests to measure performance improvements and optimize code more effectively. It can automatically discover relevant unit tests or BenchmarkDotNet benchmarks that exercise performance-critical paths.

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Microsoft SQLCon Co-Located With FabCon: What You Need to Know

Microsoft is spotlighting key reasons data and analytics professionals won’t want to miss SQLCon, taking place in Atlanta this March. Co-located with the Microsoft Fabric Community Conference, the event aims to bring together the SQL community for learning, collaboration, and insights into the evolving data landscape.

Here’s what you need to know:

• Event Details

  SQLCon will take place on March 16–20 in Atlanta. One registration gives you access to both conferences—no double sign-up needed—unlocking sessions across SQL, Fabric, and AI.

• Who Should Attend?

  DBAs, developers, data engineers, architects, and leaders building data-driven teams. Connect with engineers, MVPs, and product teams through live conversations, Q&A sessions, and deep technical discussions.

• Why Attend SQLCon?

  Explore 50+ deep-dive sessions covering SQL Server, Azure SQL, SQL database in Fabric, performance tuning, security, modernization, and AI-powered solutions—plus hands-on workshops where you’ll leave with practical scripts and patterns you can apply immediately.

• What Makes It Even More Valuable?

  Get a front-row seat to where SQL is heading. Hear directly from engineering teams, catch first-look announcements, and see live demos across SQL tooling, drivers, SSMS/VS Code extensions, Copilot integrations, and Fabric SQL experiences.

Get your tickets now.

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Dynamics 365 Introduces Holistic AI Performance Measurement for Contact Centers

Microsoft is introducing a new performance measurement framework designed to give contact centers a holistic view of how their AI agents truly perform in real-world interactions, beyond traditional metrics like handle time or satisfaction scores. The updated approach focuses on understanding, reasoning, and response quality to help businesses benchmark and improve AI agent effectiveness across channels such as voice, text, and visual interactions.

Here’s what you need to know:

• Rethinking What “Great” Support Really Means

  A 2017 study by Harvard Business Review found that customers don’t want to be pampered — they want fast, low-effort resolution. Two agent profiles stood out: empathizers and controllers — both effective in different contexts.

• Smarter AI Through Real-Time Style Adjustment

  AI agents can learn from top-performing human agents and adapt their approach in real time based on conversation context — applying the right tone and control level when it matters most.

• The Performance Benchmarks That Matter

  High-performing AI agents consistently hit 70–75% first-contact resolution, 78–90% customer satisfaction, sub-800ms response latency, and industry-aligned average handle times.

• The Core Mechanics of Every Interaction

  Whether human or AI, every interaction follows three steps: understand the issue, reason through the solution, and deliver a clear, effective response.

• Moving Toward a Unified Performance Score

  The future of AI agent evaluation lies in a composite score — one holistic measure that balances resolution, satisfaction, speed, and reasoning quality into a single view of performance.

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Visual Studio Enhances Visual Studio with Built-In and Custom AI Agents

Visual Studio now includes a suite of built-in AI agents tailored to core developer tasks such as debugging, profiling, testing, and modernisation directly within the IDE. In addition, Microsoft is launching a preview framework that lets teams build their own custom agents — connected to internal knowledge sources — for workflow-specific automation and insights.

Here’s what you need to know:

• Built-in agents

  Preset agents support debugging, profiling, testing, and modernisation—using your solution’s call stacks, diagnostics, and project context to deliver insights grounded in your actual codebase, not generic advice.

• Bring your own: Custom agents (Preview)

  Custom agents let you build tailored experiences using the same powerful foundation—workspace awareness, deep code understanding, tool access, and your preferred model. You can also connect them to internal documentation, design systems, APIs, and databases so they go beyond what’s in your repo.

• Get started

  Create a .agent.md file inside your repository’s /GitHub/agents/ folder to define a custom agent. This feature is in preview, and if no model is specified, the agent uses the one selected in the model picker.

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Dynamics 365’s Quality Evaluation Agent Now Supports Conversation Monitoring at GA

Microsoft has announced the general availability of the conversation capabilities in the Quality Evaluation Agent for Dynamics 365 Customer Service and Dynamics 365 Contact Center. The update expands AI-driven evaluation coverage across customer interactions, marking a significant milestone in automated quality oversight for support teams. The release signals Microsoft’s continued push toward scalable, AI-assisted service operations.

Here’s what’s new:

• What is QEA?

  The Quality Evaluation Agent (QEA) is an AI-powered tool that automatically reviews support cases and conversations against defined criteria to monitor performance and ensure service quality.

• What’s new?

  Starting February 6, 2026, conversation evaluation is now generally available — joining case evaluation as a full GA capability.

• What’s coming next?

  Upcoming enhancements include multilingual support, criteria versioning, critical question flagging, simulation capabilities, and improved knowledge-source adherence.

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GitHub Copilot Testing for .NET Now Generally Available in Visual Studio 2026

Microsoft has officially rolled out GitHub Copilot testing for .NET as part of Visual Studio 2026 v18.3, bringing AI-driven unit test generation directly into the IDE. The new capability helps developers automatically generate, build, and run high-quality tests for C# code, shortening the feedback loop between writing and validating code. Early users can now leverage richer IDE integration and more natural prompting for widespread test automation.

Here’s what you need to know:

• Built for real testing workflows

  The testing agent understands your solution structure, frameworks, and build system — acting as an end-to-end workflow, not just a one-off prompt.

• Natural, free-form prompting

  Simply start with @Test and describe what you want in plain language — no rigid commands required.

• More control over test generation

  Generate or fix tests, target coverage goals, and apply your team’s testing conventions using simple prompts. You can reference specific code areas or even include current Git changes for more precise results.

• Getting started

  Open your C# project or solution, start a new Copilot Chat thread, and begin your prompt with @Test, then select Send. Test Explorer shows the results as the tests are generated, and once complete, GitHub Copilot testing provides a summary in Copilot Chat.

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Power Apps Introduces MCP and Enhanced Agent Feed in Public Preview

Microsoft has introduced a new public preview for Power Apps, highlighting its growing focus on AI-assisted business applications. The update brings MCP and an enhanced agent feed, pointing toward more interactive and intelligent user experiences. It represents another step in turning everyday apps into collaborative workspaces between people and AI.

Here’s what this means for organisations:

• Automate repetitive app tasks

  AI agents can extract data from emails, files, or shared folders and create records automatically — with human approval before completion. Less manual entry, fewer errors, faster processing.

• Human-in-the-loop supervision

  Users can review, guide, or take control of agent actions directly inside the app through built-in supervision tools. Keep governance and trust while benefiting from automation.

• A redesigned collaborative agent feed

  A shared workspace where humans and AI work together — with side-by-side comparisons, task tracking, and performance insights. Clear visibility into what AI is doing and why.

• Turn existing apps into agentic apps

  Embed agents into the apps employees already use daily — no rebuild required. Faster adoption and real productivity gains.

• Scalable AI for real business processes

  From data entry to broader CRUD operations, the MCP framework enables enterprise-scale automation across workflows — assistance → autonomy → collaboration.

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Dynamics 365 Contact Center Sets New Standards for AI Evaluation

Microsoft is highlighting a shift in how organisations approach AI in customer service, emphasizing that evaluation is no longer just a technical step but a core business capability. In its latest guidance for Microsoft Dynamics 365 Contact Center users, the company outlines key dimensions organisations must consider to ensure AI systems remain reliable and customer-focused. The message is clear: trustworthy AI in contact centers depends on continuous, multi-stage evaluation — not a one-time test.

Here are the key facets every organisation should consider:

• Development-stage vs Production-stage evaluation

  Test early in development to catch issues before deployment, and evaluate in production to understand how AI performs under real-world traffic and customer behavior.

• Manual vs Automated evaluation

  Use automated tests for scalable, continuous checks (e.g., after deployments or config changes), and pair them with manual evaluations for deep insights, context, and judgment that machines can miss.

• Platform vs Customer-run evaluations

  Internal evaluations from the AI provider establish a baseline of quality and safety, while customer-run tests reveal real usage patterns and constraints specific to your business.

• Synthetic data vs Production traffic

  Start with synthetic or simulated data for safe, repeatable tests (especially edge cases), then validate against real production traffic to gauge how AI behaves with actual user interactions.

• Evaluation after vs during execution

  Post-interaction analysis unlocks deep learning about correctness and resolution quality, while real-time evaluation lets you intervene instantly (e.g., escalate to a human when sentiment drops).

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Power BI Phases Out Old Excel & CSV Import Experience

Microsoft has announced upcoming changes to the Power BI service that will affect how some users work with Excel and CSV data. A legacy data import experience is being retired, with key deadlines arriving in 2026. Users relying on older reports are encouraged to transition to the newer data connection methods to avoid outdated data.

Here’s what you need to know:

• What’s affected?

  Semantic models created with the old import experience can’t be edited in the browser, downloaded, or scheduled for refresh. If your model supports those capabilities, you’re already using the newer connectors and won’t be impacted.

• What’s changing?

  Starting July 31, 2026, reports built using the old import experience will stop refreshing from their source files. They will still open and be editable, but the data will no longer stay synced unless recreated using the new connectors.

• Key dates to remember

  By May 31, 2026, creating new semantic models using the old experience will be disabled. By July 31, 2026, existing models built with it will stop refreshing.

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Microsoft Improves Large-Codebase Navigation in Visual Studio

Microsoft is enhancing AI-assisted development in Visual Studio with the introduction of the find_symbol tool. The update gives AI agents richer, language-specific context so they can better understand relationships across a codebase instead of relying on plain text search. It’s part of Microsoft’s continued push to make Copilot more reliable inside real-world projects.

Here’s why it matters:

• What is find_symbol?

  find_symbol gives Copilot deep, language-aware insight into your code. It understands functions, classes, interfaces, and variables, including their declarations, implementations, scope, and every reference across the codebase—so the agent can reason, not just search.

• Example #1: Enhancing existing functionality

  Need to add logging, telemetry, or performance metrics without breaking anything? Copilot can quickly identify all related symbols and references, helping ensure updates are complete and accurate.

• Example #2: API refactoring

  Hardening or refactoring an API requires knowing exactly how it’s used. With symbol-level insight, Copilot can trace call paths, understand dependencies, and suggest safer refactors with minimal risk.

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