CppCon 2026

The next evolution of C++ has officially arrived, bringing a massive wave of enhancements to both the core language and the Standard Library. But with hundreds of committee proposals officially baked into the standard, where do you start? Continuing the tradition from previous releases, this fast-paced session delivers a comprehensive look at the new and updated features that define C++26.

We won’t get bogged down in the minutiae of every single ISO proposal—covering everything in detail is impossible in just one hour. Instead, you'll get a high-level, curated overview of the most impactful changes, from the major game-changers down to the small quality-of-life gems. If you want to get up to speed with the new standard and see how it will shape your codebase, this session is for you.

The session will touch on the following core language and Standard Library topics.

C++26 core language changes include - Reflection - Contracts - Unnamed placeholder variables - = delete("reason"); - Pack indexing - #embed - constexpr exceptions, constexpr placement new - Variadic friends - ...

C++26 Standard Library changes include - Execution control library - New libraries such as , , , , , and more - std::inplace vector: dynamically-resizable vector with fixed capacity - std::philox engine: counter-based random number engine - std::text_encoding: text encodings identification - More constexpr for containers and container adaptors - Saturation arithmetic - New SI prefixes - Printing Blank Lines with std::println() - ...

Where applicable, I’ll point you toward other specialized CppCon sessions for those ready to dive even deeper into specific topics.

How to Choose and Use the Right Container in Modern C++: Part 1, Classic Containers

Choosing the right container and using it correctly can have a profound impact on the performance of a program, but doing so is harder than you might think. In Part 1 we will survey the containers and adaptors in the C++17 Standard Library, and discuss how to choose the best tool for the job and extract the best performance from it. We will consider the abstractions they model and the practical limitations they impose, and find that choosing between them requires an understanding not only of the speed and size tradeoffs of each container, but also of the difference between algorithmic complexity and actual behavior. And we will flag aspects of the standard containers that, without this understanding, can lead you to the wrong choice.

How to Choose and Use the Right Container in Modern C++: Part 2, New and Future Containers

Choosing the right container and using it correctly can have a profound impact on the performance of a program, but doing so is harder than you might think. In Part 2 we will survey the new containers and adaptors introduced to the Standard Library in C++23/26, and discuss how to choose the best tool for the job and extract the best performance from it. We will consider the abstractions they model and the practical limitations they impose, and find that choosing between them requires an understanding not only of the speed and size tradeoffs of each container, but also of the difference between algorithmic complexity and actual behavior. And we will examine a proposal for a future container that diverges from the historical STL design principles and ask: what makes for a good container design?

Every mature codebase carries history and technical debt. The challenge is modernizing without stopping the world or introducing big re-write failure risks.

In this talk, we’ll explore how to modernize legacy C++ codebases incrementally using a mix of deterministic code transformations and AI-assisted refactoring .

After delving into some of the common problems with legacy modernization, we'll start tackling the simple "boring" stuff that deliver huge leverage of changes via clang tooling . These represent repeatable, deterministic reviewable upgrades that can be automated and applied at scale.

Then we can look at more difficult transformations that can be AI assisted with more aggressive transformations including API improvements and how to prevent it going off the rails. This will be backed by Compiler diagnostics, static analysis and testing to keep changes maintainable and correct .

The goal is not to replace engineering judgment, but to accelerate it: turning modernization into a continuous, low-risk workflow instead of a disruptive project.

Attendees will leave with a repeatable playbook for modernizing legacy codebases incrementally, safely, and at scale—using the right tool for each class of change

For decades, lock-free programming has been the go-to optimization for the most contended parts of concurrent programs. The reasoning was simple: locks are slow under contention, so eliminate the locks. This made sense on the hardware of the time, and I should know—I've given several talks explaining how and why to do it. The hardware has changed. Modern CPUs are highly optimized for the operations that make locks fast: cache-line transfers, memory ordering, and speculative execution through lock acquisitions. To set the stage, we will briefly establish why, under high contention, a well-written lock consistently outperforms lock-free atomics and CAS loops. (As an aside, I'll hand you a concrete recipe for a spinlock that actually holds up under extreme contention—and show why systematic backoff, by batching cache-line ownership, is what protects the shared interconnect.) But the core of this talk addresses a completely flipped reality: at low contention, lock-free code decisively outperforms spinlocks, for the most surprising reason. Conventional wisdom assumes an uncontended spinlock is practically free. Using raw hardware performance counters, we will see why it isn't: the implicit synchronization a spinlock imposes—even with no contention at all—is deeply unfavorable to modern out-of-order pipelines, while a single lock-free XADD or CAS, an indivisible read-modify-write, is not. The path everyone assumes is free turns out to be the quietly expensive one. Putting these two facts together—locks winning high contention via cache-line batching, atomics winning low contention by staying out of the pipeline's way—points to a concrete design. I will present a highly optimized MPMC (multi-producer, multi-consumer) queue built on a dual-domain structure that deliberately segregates the contended path from the uncontended one, letting each run on the mechanism the hardware actually favors. We will then walk extensive benchmarks across modern silicon—Intel, ARM server (Graviton/Grace), and Apple (M3)—showing this queue is the fastest, often by wide margins, across most operating regimes. We will also see why the tradeoffs play out so differently per chip, in ways that aren't obvious from the spec sheet, and why "ARM vs x86" is the wrong axis entirely—what matters is the chip's target market, not its instruction set. Finally, no benchmark is complete without honest caveats. I will detail the specific corners where this design can still be beaten, the hidden system costs you pay elsewhere to buy this throughput, and why systems that strictly require progress guarantees—deadlock avoidance, priority inversion, safe execution in a signal handler—mean traditional lock-free programming is not dead. It has simply relocated. If you've ever reached for a complex lock-free algorithm to speed up a highly contended hot path—or wondered what your CPU is actually doing during a mutex unlock—this talk will change your mind about where lock-free programming truly belongs.