Layering is not complicated. It’s the process of adding and removing layers of clothing to keep your body comfortable in changing weather and temperature conditions.

Billions of dollars have been spent trying to optimize this process (and sell you stuff), but it’s really very simple: Put clothing on when you’re cold, take clothing off when you’re hot. Which clothing? That’s the rub, as they say. But don’t worry. We’ll walk you through what each layer is, how to layer, and when you’ll want it. Once you’re done here, check out our guides to the Best Base Layers, Best Puffer Jackets, Best Merino Wool, and Best Rain Jackets for more.

Updated February 2026: We’ve updated our advice based on new experiences, and put in a few new picks culled from all the gear we’ve tested in the last year.

Layering Basics

The key to layering is knowing what the layers are for and when to add and remove them. The high level overview looks like this:

• Base layer: The layer that touches your skin. These provide some warmth, but they’re primarily important for wicking sweat away from your skin. Being damp means being cold.
• Mid layer: The layer that’s—wait for it—in the middle. This is the layer where you actually start insulating, or trapping body heat. This is the key to the whole system and should usually be more than one layer (e.g., a lightweight fleece and a puffer jacket).
• Outer layer: The top layer is the waterproof, windproof layer that makes sure that nature does not steal all that precious heat you’ve retained in the mid layer. This is sometimes referred to as a “shell.”

While you won’t always be wearing all of these, especially when you’re exerting yourself while walking, running, et cetera, it’s usually worth carrying all three. If it’s cold, you can start with all three on and peel them off as you get warmer. When it’s hot you can do the opposite, pulling out a shell when you stop on a windy ridge. Obviously there are situations where you don’t need to carry all of them. Hiking the Florida trail in July? Skip the mid layer, ya lunatic.

Base Layers

SmartWool

Merino Classic Long-Sleeve

Let’s start with underwear. Whether boxers, briefs, boxer briefs, or bras, go for materials that are going to help move moisture away from your skin. I have found merino wool to be ideal for underwear, but it’s worth trying different fabrics to find which works best for you.

Next comes what we generally think of as base layers: relatively tight-fitting but not overly restrictive pants and shirt with the dual purpose of insulating in cold weather and wicking sweat in hot. Again, there is a wide array of fabrics. If you opt for merino wool here, you benefit from wool’s natural ability to smooth out temperature variation across your skin, keeping you more evenly warm/cool (I call this temperature modulation).

There are also other options for fabric here, which includes Nuyarn. It has much of the benefits of merino (it’s usually more than half merino) but adds some nylon to provide extra strength and durability, as well as speeding up drying times. The latter can be important in very wet climates. In my experience, synthetic base layers do not perform as well at either insulation or moisture removal, though they will often dry faster, last longer, and are often cheaper.

The Wireless Broadband Alliance (WBA) has published a report outlining an industry-wide perspective for device manufacturers, network operators, enterprise IT and policymakers on how artificial intelligence (AI) and machine learning (ML) can be integrated across the full Wi-Fi ecosystem.

The AI/ML for Wi-Fi: Enabling scalable, intelligent Wi-Fi ecosystems report was developed by the WBA AI/ML for Wi-Fi Project Group, and led by Intel with Airties, Cisco and HPE.

The founding viewpoint from the WBA is that traditional rule‑based management approaches for Wi‑Fi technology are no longer adequate as they are now asked to support increasingly support demanding applications such as enterprise collaboration, industrial automation, immersive media and AI workloads. The report outlines business benefits including lower operational costs, stronger reliability and security, and an improved user experience.

The report shows how AI and ML are becoming foundational to Wi-Fi, enabling a shift from reactive troubleshooting to predictive, proactive and self-optimising network operations capable of managing dense deployments and real-time performance demands.

In addition, it highlights how intelligent Wi-Fi has clear business value. AI/ML reduces operational costs (OpEx), improves reliability and security, and delivers a more consistent quality of experience (QoE). Moreover, the report argues that AI will not just sit at the router: instead, it will combine client, access point, edge and cloud intelligence to achieve the best performance.

However, it also observed that data is the primary bottleneck, and that achieving continued success and new use cases with AI/ML in networks requires shared datasets, federated learning and strong governance models. Fragmentation also remains a major barrier.

Going forward, WBA advises that standardisation should focus on frameworks and not algorithms. It added that interoperability will need to include data models, telemetry, application programming interfaces and model lifecycle management. WBA also believes that AI/ML-native Wi-Fi is the long-term technological direction and that features of Wi-Fi 8 (IEEE 802.11bn), such DBE and MAPC, will work optimally when driven by an AI/ML engine.

Commenting on the report, Tiago Rodrigues, Wireless Broadband Alliance president and CEO, said: “Wi-Fi is now expected to perform like critical infrastructure across homes, enterprises and cities, yet operational complexity is rising fast. AI and machine learning are becoming essential to keep networks reliable, secure and efficient at scale. The industry must align on common data, interfaces and governance, so that intelligent Wi-Fi can work across real-world multi-vendor environments and deliver value for all who use it.”

Matthew MacPherson, wireless chief technology officer at Cisco, added: “As Wi-Fi becomes the primary connectivity technology for mission-critical enterprise applications, the complexity of managing these environments has outpaced traditional manual methods.

“This report provides a vital framework for the industry to transition from reactive troubleshooting to a proactive, self-optimising architecture,” he said. “By leveraging AI and machine learning through interoperable standards, we are enabling organisations to reduce operational overheads and deliver a more resilient, high-quality experience for every user and device.”

Eric McLaughlin, vice-president and general manager of Intel, said: “AI/ML is transforming the future of Wi-Fi, and it has become a strategic imperative. We are excited to collaborate with our WBA partners and the broader ecosystem to accelerate its advancement to enable self-organising, proactive, and more reliable networks with improved QoE across the industry.”

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