Modern C++ development spans platforms, build systems, and increasingly complex project structures. In this landscape, Visual Studio Code has carved out its distinct position as a lightweight, extensible editor that works where you do, with first-class extensions built on decades of C++ language services and build system integration. This year's update deepens both of those foundations and opens them up to AI-driven workflows powered by GitHub Copilot.
This session walks through what's new across three dimensions of C++ development in Visual Studio Code. For the inner loop, we'll cover practical improvements to everyday compile-test workflows, including CMake target bookmarks and Run Without Debugging. For writing and understanding code, we'll show how the C/C++ extension's language services now surface rich project understanding to GitHub Copilot, giving AI assistance real awareness of your code structure instead of relying on generic pattern matching. For your workflow, we'll demonstrate how AI capabilities compose across different modes of working: inline suggestions for hands-on editing, agent coordination for multi-file refactoring, and CLI sessions for long-running tasks and deeper codebase analysis you can revisit on your own schedule.
Throughout the session, we’ll use real-world C++ problems to demonstrate where these tools meaningfully improve productivity and where they intentionally stay out of your way. Finally, we’ll show you how to inform GitHub Copilot about your team's best practices and scale them across your code through extensibility points like skills, custom instructions, and custom agents.
Sinem Akinci graduated from the University of Michigan with a focus in Industrial Engineering and Computer Science. She now is the Product Manager at Microsoft working on Cross-platform and CMake developer experiences in Visual Studio and VS Code
Ben McMorran studied computer science at Worcester Polytechnic Institute. Since graduating, Ben has worked on C++ developer tooling at Microsoft as a Principal Software Engineer with a recent focus on AI-powered developer experiences.
Modern storage hardware has evolved at a breakneck pace. PCIe Gen 5 NVMe drives can push data at 10 GB/s, yet standard C++ file abstractions often leave them starving for data. Many developers think they need to abandon portability in favor of unmaintainable, OS-specific kernel bypasses to achieve the throughput necessary to saturate these drives. This session is for developers writing high-throughput, performance-critical applications who want to hit bare-metal speeds without sacrificing clean architecture, cross-platform support, or type safety.
Using a high-throughput cryptographic hashing engine as a concrete case study, this presentation demonstrates how to design a hardware-saturating data pipeline built entirely on the idioms of C++26. We will explore how the mathematical design of an algorithm - specifically BLAKE3's binary Merkle tree structure - can be mapped directly to wide SIMD vector lanes and concurrent CPU cores. We will walk through an execution model that completely bypasses the OS page cache, orchestrates memory without heap allocations on the hot path, and unifies OS kernel quirks in a portable way.
By the end of this presentation, you will learn how to replace rigid thread pools with lock-free, asynchronous execution graphs using Sender/Receiver paradigms (std::execution) and vectorization (std::simd). Crucially, we will focus on the build engineering required to make this work today. We will cover how to use advanced CMake tooling to safely compile multi-architecture vector binaries from a single source of truth, how to prevent LTO cross-contamination, and how to structure your pipeline today to seamlessly absorb upcoming C++ features in a world of trailing vendor toolchains.
In many languages, you can mock almost anything. Python has unittest.mock, Java has Mockito and PowerMock, and C# has Moq. In C++, you can usually mock only what was designed to be mockable — and little else. Want to mock a free function? Wrap it in an interface. A static method? Refactor to a template. A non-virtual member? Redesign the class hierarchy. The cost is real: developers either shape production code around testing-tool constraints instead of domain needs, or they simply leave hard-to-mock code untested.
This talk introduces [LibraryName], a new C++ mocking library we developed (and plan to publish soon as open source) that can mock almost any C++ callable — free functions, static methods, non-virtual members, private members, templates, lambdas, and even extern "C" routines — without modifying the code under test. Developed and battle-tested at [CompanyName] for three years across a very large C++/C codebase, it aims to deliver a first-class testing experience for C++. Under the hood it uses runtime binary patching — replacing function prologues with redirections at test time, restoring them on scope exit — all surfaced through familiar Google Mock syntax.
We'll show [LibraryName] in action, walk through the patching mechanism, and share how to get started -- you'll walk away ready to test almost any function, regardless of how it was designed. Strong test coverage has always been essential, and AI-assisted code generation only increases the need for reliable testing backpressure. C++ deserves mocking tooling that matches.
Ilya Ermakov graduated from Vanderbilt University with a major in Computer Science. Since graduating, Ilya has worked at Bloomberg where he is now a Software Engineer working on Distributed Systems and C++ tooling.
Brian Rudo-Hutt is a Senior Software Engineer at Bloomberg and organizes engineering-wide initiatives to improve testing, safety, and software maturity. Brian holds Computer Science and Electrical and Computer Engineering degrees from Cornell University and lives with his family in... Read More →
Clang is the C++ compiler used by hundreds of millions of developers every day, yet most of those developers have never looked inside it. The codebase can feel intimidating, with millions of lines of C++, an unfamiliar architecture, and a review process with its own customs. But once you know the map, contributing is surprisingly accessible.
This session is a live, code-first walkthrough of the full contribution cycle for Clang. Starting from a clone of the LLVM monorepo, we will configure a development build, locate the right subsystem for a real reported bug, write a regression test, fix the bug, and verify the fix. We will then extend that foundation to implement a small but complete language feature: adding a new diagnostic, walking through Sema, the AST, and the diagnostic engine as we go. Every step attendees see on screen can be replicated on their own laptops during and after the session.
Attendees will leave with a mental model of Clang's layered architecture (driver, frontend, Sema, CodeGen), a workflow for finding the code responsible for any given compiler behavior, and enough familiarity with the test infrastructure and review process to open their first pull request.