Technology

• Klarna has partnered with NordVPN to include a free VPN subscription
• Only Klarna Premium and Max members can redeem one NordVPN plan
• The perk is bundled into existing memberships

Buy now, pay later giant Klarna has a new perk for its paying members, and this one is all about your privacy.

The company has partnered with NordVPN to add encrypted connectivity as an included benefit for Klarna Memberships subscribers, folding a digital security tool into a subscription that was previously focused on cashback, travel protection, and lifestyle rewards.

It's the latest example of a payments company bundling in one of the best VPN services as a membership sweetener, and it follows hot on the heels of NordVPN's tie-up with Mastercard earlier this year, as well as other collaborations with companies such as CrowdStrike and Marvel.

The idea is simple. If you already have a Klarna membership, you can now activate a NordVPN subscription at no extra cost. Which tier you get depends on your membership level.

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What the Klarna and NordVPN partnership involves

The structure is tied directly to Klarna's membership tiers.

Klarna Premium members will receive access to NordVPN Basic, while Klarna Max members will receive access to NordVPN Complete, both included within their existing membership subscription.

It's worth mentioning that at the time of writing (August 10, 2026), Klarna's membership page wrongly indicates that the perk for Max users is NordVPN Standard — described as "secure VPN access with enhanced security features". A NordVPN spokesperson clarifies to TechRadar that the company actually meant its Complete plan.

Regarding the partnership, NordVPN argues that VPN protection has become relevant infrastructure for both professionals and consumers, supporting secure connections on public and shared networks, such as those found in coffee shops, airports, and hotels.

Klarna describes the move as part of a strategy focused on offering tangible, valuable benefits at scale, giving members more control over aspects of their digital activity, and positioning its memberships to compete on overall value.

How to claim your free NordVPN subscription

Because the VPN is bundled into your Klarna membership, the first step is simply making sure you're on an eligible tier (Premium or Max).

With NordVPN's comparable Mastercard partnership, once users activate their NordVPN subscription, the service asks them to set up their Nord account and download the NordVPN app. We can likely expect the Klarna flow to follow the same rough path: confirm eligibility, activate the benefit, create or sign in to a Nord Account, then install the app on your devices.

If you're unsure whether your specific plan includes the perk, it's worth checking directly with Klarna, since availability can vary by region and membership level. Once it's live, you'll have the full NordVPN app to set up across your phone, laptop, and other devices.

NordVPN Basic vs NordVPN Complete: what's included

While users can use both plans on up to 10 devices simultaneously, features offered slightly differ.

As the name suggests, NordVPN Basic is the entry-level tier, and the main feature is the virtual private network (VPN) itself, using the same core software found across every NordVPN plan.

You get access to all NordVPN's server network — 211 locations in 135 countries— which TechRadar's reviewers found to be larger than any rival we test. You also get NordVPN's fast, secure NordLynx protocol, a reliable kill switch, and post-quantum encryption already baked in.

Basic also includes NordVPN's standard Threat Protection — now known as NordVPN's next-gen antivirus suite — which filters your traffic through NordVPN's DNS servers to block ads and malicious sites.

NordVPN Complete expands on Threat Protection's reach by adding real-time anti-malware and file scanning. The plan also bundles premium access to its password manager tool (NordPass) and 1TB of encrypted NordLocker cloud storage.

• Kimsuky used local AI tools to evade monitoring and enhance operations
• Researchers observed extensive AI-driven capability building across the group’s infrastructure
• Defenders urged behavior-based detection to spot evolving AI-enabled threats

North Korean hackers have found a way to use Generative Artificial Intelligence (GenAI) to supercharge their activities without tipping off the tool’s maintainers.

When people use AI tools like ChatGPT or Claude, their activities can be (at least to some extent) tracked and curbed - with OpenAI recently identifying and terminating multiple ChatGPT accounts used in phishing and human trafficking.

That is why Kimsuky - a known state-sponsored North Korean threat actor, used Ollama, GPT4All and Msty locally, allowing them to process documents without sending any sensitive information to outside AI services.

"Consistent process of capability development"

The attacks were spotted by security researchers Genians who “conducted months of tracking and log analysis on the infrastructure utilized as C2 in this campaign,” to identify the tools they used.

Aside from the three LLMs, they also used retrieval augmented generation (RAG) tools for document search, as well as AI agent development frameworks, text-to-speech software, and an AI-assisted coding tool called Cursor.

Using AI to write malicious code is not as simple as it sounds, due to various guardrails set up by the developers. As a result, AI in crime has been mostly limited to drafting phishing emails and crafting authentic-looking but malicious landing pages. However, Kimsuky has shown that AI in cybercrime continues to evolve and is becoming an ever-greater threat.

“What was observed in the threat actor's infrastructure was not merely evidence of several documents being created with AI, but a consistent process of capability development: establishing local LLM runtime environments, configuring RAG based on documents in the actor's possession, collecting AI agent development frameworks, and acquiring libraries for integration with external commercial AI services,” Genians concluded.

As a result, defenders must move from content-based assessment to behavior-based detection, the researchers warned, saying this should serve “as the fundamental premise of security recommendations.”

“In addition to indicator of compromise (IoC)-based detection, organizations should contextually correlate the sequence of anomalous activities following LNK execution, including PowerShell execution, persistence establishment, and external communications, to assess the overall threat level.”

Budget earbuds don't get much better than this: both in terms of quality and value for money. That's what makes it so easy to recommend the Sony WF-C510 Earbuds at Amazon for £34.99 (was £54.99).

You'd usually expect to make a handful of serious compromises when buying such a cheap pair of earbuds, but the Sony WF-C510 offer a surprising amount for such a low price. Audio is punchy, the fit is comfy, and the battery life impresses. For £35, you can't really ask for more.

Yes, there are a couple of features that it's a shame to miss out on, especially active noise cancellation, but that's to be expected when dealing with budget buds. Premium features like this aren't always necessary if you want a quality pair of affordable earbuds to listen to music or enjoy streaming videos — and that's where the Sony WF-C510 excel.

Buy the Sony WF-C510 at Amazon

We already called the new version of these popular cheap earbuds 'great value for money' in our Sony WF-C510 review – and that was at the full asking price. At under £35, I think they're an absolute steal. Yes, 20 hours of battery can be bettered — but 10 hours from the buds alone certainly can't at this price point. They're also light and comfortable, providing an exciting, musical sound that also beats the latest AirPods.View Deal

Our 4.5-star review of the Sony WF-510 goes into more detail on what makes them such a good pair of budget-friendly earbuds. In fact, we were so impressed with them that we'd even recommend them over the much pricier Apple AirPods.

These are cheap earbuds that still offer a bold and vibrant sound. Of course, the bass won't be as strong as that of more premium options or over-ear alternatives, but you still get solid overall quality for the price.

If there's anything against them, it's that regular commuters or those who like to focus up when working in a noisy office might miss the active noise cancellation. If that's not going to be an issue for you, though, then the Sony WF-510 are easily some of the best cheap earbuds you can buy while they're down to this super-low sale price.

• Deep Orange 17 is claimed to generate more electricity than it uses

• The BMW-backed project uses 1,700 photovoltaic cells

• The prototype is based on an average 12-mile daily commute

A team from Clemson University in South Carolina has produced a small, lightweight electric vehicle that it says can generate more energy than it uses over a typical day of urban driving.

Dubbed the Deep Orange 17, the boxy prototype, which looks a little like a butchered Tesla Cybertruck if you squint hard enough, was fitted with more than 1,700 photovoltaic cells that can produce enough charge to power a typical 12-mile daily commute.

The fully functional vehicle weighs just 1,212lbs / 550kg, and is predominantly made from aluminum, carbon fiber and 3D-printed metal joints, which are all wrapped around a steel structure.

Its boxy shape has been designed so the photovoltaic panels can be positioned to maximize their exposure to the sun when the vehicle on the move, when parked, and even when stuck in traffic.

(Image credit: BMW/Clemson University)

Developed in collaboration with the Fraunhofer Institute for Solar Energy Systems ISE in Freiburg, Germany, the solar panels use an innovative construction that continues generating power even when portions of the panels are shaded. The orange coating is part of a durable film that helps protect them.

According to BMW, which is backing the project, the cells generate enough energy on a sunny day to power the tiny EV for up to 31 miles. That means it can generate more than twice the energy it needs to complete the low-mileage average daily commute touted by its makers.

While most of the energy comes from the photovoltaic panels, the team of 16 engineers also integrated regenerative braking and drew inspiration for the exterior from the aerodynamic characteristics of the boxfish, whose streamlined body naturally reduces drag while maintaining interior volume, apparently.

Surprisingly, the project doesn’t feature a spartan prototype interior. It's been fitted with Apple CarPlay and Android Auto, as well as digital dials that offer real-time vehicle telemetry and readouts on solar power generation.

Analysis: inspiring the next generation

(Image credit: BMW/Clemson University)

Project manager Anshul Karn explained that it's rare for a master’s student to have the opportunity to experience the complete process of developing a prototype vehicle — and this is exactly what Deep Orange is designed for.

Of course, we aren’t going to suddenly see BMW put this into production, but EV manufacturers are already toying with the idea of solar panels as a way of extending the range of electric vehicles.

Nissan, for example, fitted an Ariya model with 3.8 square meters of custom solar panels earlier this year that could add 23km (around 14 miles) of additional range on a bright, sunny day.

Back in 2019, Hyundai became the first manufacturer to launch a car with a solar roof charging system when it added the tech to its Sonata Hybrid, while the Ioniq 5 was available in some markets with a solar charging roof.

Right now, the technology is expensive given the limited amount of range it can provide, but projects like Deep Orange could go on to influence smaller, lightweight urban transport that could easily harness the power of the sun for 'free' energy.

• Don't like the camera bump on your foldable? Take it off
• That's what one Redditor has done with their Galaxy Z Fold 8
• It now lies flat — but the selfie camera is the only camera left

How far would you go to get one of the best foldable phones looking and working exactly the way you want it? One Samsung user has taken the drastic step of cutting off the rear camera module on their new Galaxy Z Fold 8, just so it'll lie perfectly flat when placed on a surface.

The unusual DIY hack is documented on Reddit, and has been met with one or two raised eyebrows. Apparently, the owner of the phone used a razor blade to perform the operation, and says the end result is "not bad".

"The wobble is so annoying and I never use [the cameras] anyways" was the reason given by the user, when asked what prompted the customization — and they don't appear to have any regrets about what they've done.

Our Samsung Galaxy Z Fold 8 review doesn't mention the camera bump as being a particularly egregious problem, but we do have some praise for the performance of the dual-lens camera on the back — so it seems a shame, and a little drastic, to remove them.

A job well doneI took the cameras off of my fold 8 from r/GalaxyFold

The reactions in the original Reddit thread are mostly of disbelief that someone would go to these lengths just to get a phone to lie flat, while taking away their ability to capture photos and videos at the same time.

Amidst a lot of well-chosen GIFs, there are comments like "no amount of explanation justifies it" and "what a mad man", as well as some appreciation for a tech-hack that seems to have been well done, based on the photo evidence.

There's also one request for more information from another Redditor who wants to do the same to their own Galaxy Z Fold 8 — perhaps an indication that the wobble you get when the handset lies flat is annoying quite a few users.

Samsung launched the phone on July 22, and the starting price is $1,899 / £1,699 / AU$2,699. It launched alongside the slightly more expensive Galaxy Z Fold 8 Ultra and the more affordable Galaxy Z Flip 8.

Dyson v10 Konical + Auto-empty Dok: two-minute review

Almost all robot vacuums now come with an auto-emptying charging dock that automatically transfers the debris in the robot to a larger dust bag in the dock. Well, the Dyson v10 Konical + Auto-empty Dok (as Dyson calls it) brings a similar hands-free system to the world of cordless stick vacs.

Roborock, Tineco, and Shark have already aired their versions and, according to comments online, it seems that the public is up for this kind of system because it saves the hassle of manually emptying the vac's bagless dustbin while almost totally removing all elements of dust in the process.

The problem, as I see it, is the size of the docks these vacs come with, of which the Dyson model we're reviewing here is definitely the tallest and one of the most incongruous. It fact, at 47.24in/120cm in height, the Dyson Dok is as tall as some users, and that's quite a comical stat for a stick vac.

In its favor, the Dok does a decent job of emptying the contents of the v10 hand unit's small 0.52 qt / 0.5 liter bin (when there isn’t too much hairy detritus inside), it keeps the v10's battery permanently topped up, and it has a cupboard for storing the two main accessories it comes with — a mini motorized brush and a detail nozzle, with space for at least one extra accessory.

Dock aside, the real winner here is the light and compact v10 Konical, which sports an ample 150 air watts of suction power and comes with Dyson's latest twin cone-shaped brush head, with a laser-style light for illuminating the path ahead. This brush head is radically different to any other on the market and was developed with one sole aim: to reduce the amount of hair on the spindle. If you have hirsute pets in the home, a brush head like this could be a genuine hassle-saver.

If the idea of a monolithic self-emptying dock fails to tickle your fancy but you still like the idea of a compact stick vac with a unique, high-performance brush head, you'll be pleased to learn that both the V10 Konical and the Dyson Dok can be bought separately. I'll leave you to decide.

Dyson v10 Konical + Auto-empty Dok: price & availability

• List price £569.99 / $649.99 / AU$999
• Launch date April 2026
• Availability UK, USA, Australia and most of Europe

The Dyson v10 Konical + Auto-empty Dok combo offers relatively decent value, but whether it can be considered excellent value depends on how much you appreciate its self-emptying system.

The v10 Konical itself is an extremely capable mid-range cordless vacuum with strong suction, thoughtful ergonomics and an innovative conical anti-tangle cleaner head. However, it's the bundled auto-empty Dok that sets this model apart, so if you vacuum frequently, have hairy pets or suffer from allergies, it could be considered a genuine quality-of-life improvement rather than just another gimmick.

The downside to this system is the price because you're ultimately paying a premium for convenience and buyers who don't mind manually emptying a dustbin may find better value in purchasing the v10 Konical on its own or opting for Dyson's standard v8 or v12 models, or even a raft of rival cordless vacuums from the likes of Shark, Samsung, Halo, Roborock and Tineco. These brands offer similar cleaning performance stats for less and, in some cases, quite a lot less.

If you live in the UK, you can purchase the Dyson v10 Konical + Auto-empty Dok direct from Dyson or Argos for £569.99 or, for an even better deal, head straight to John Lewis or AO, where it's selling for £549.99. If you don't fancy the Dok, you can also purchase the v10 Konical on its own from the aforementioned stores for £449.99.

If you're shopping in the USA, try Dyson direct where this package sells for $649.99. For some reason the full package is difficult to find beyond Dyson's US website but you can buy the v10 Konical unit as a separate entity from Walmart and Best Buy where it's selling for $399.99.

The combo has a list price of AU$999 in Australia,, but at the time of writing is discounted to AU$797 when bought directly from Dyson's online store.

• Value score: 3.5/5

Dyson v10 Konical + Auto-empty Dok: specs

Cordless/Wired?

Cordless

Weight (v10)

3.60lbs / 1.63kg

Dimensions (vacuum unit) (LxWxH)

13.79in/35cm x 5.11in/13cm x 7.87in/20cm

Dimensions (dock) (LxWxH) 

47.24in/120cm x 7in/18cm x 6.69in/17cm

Bin size (vacuum) - bagless

0.52 qt / 0.5 liter

Bin size (dock) - bagged

2.64qt / 2.5 liters

Max runtime

A claimed 60 mins in Eco mode

Suction power

150 AW

Charge time

4 hours

Noise level

75 - 85dB

Tools

Detangling conical head, Mini Motorised Tool, Crevice tool

Dyson v10 Konical + Auto-empty Dok: design

• Light and compact vac
• Impressive suction
• Overly tall and incongruous dock

I've tried both the Roborock H60 Hub Ultra and the Tineco Pure One Station and I can definitely see the appeal of having a cordless stick vac with its own dust-emptying station. Firstly, it's somewhere to store the vac while it's being charged but, more importantly, it negates the need for any any manual emptying of the vacuum cleaner's bin because the dock does it all for you. And that means no plumes of dust rising from the kitchen bin and coating your nostrils as the contents are ejected from the vac. It also means you won't have to reach for a damp kitchen towel to wipe down the lip of the bin every time you empty the vac's contents.

Instead, you wait a month or two — depending on how grubby your home is — and simply grab the sealed dust bag from the charging dock and drop it into the kitchen bin with no sign of dust at all. Aside from the cleanliness aspect, this is a great system for allergy sufferers because dust is kept to a bare minimum. However, the downside is that you will need to purchase more dust bags down the line and, as of writing, there's no mention of dust bags on the Dyson website. Just as well it comes with a spare.

Let's take a look at the vacuum unit first.

(Image credit: Future)v10 vac design

Confusingly, the Dyson v10 Konical looks more like an evolution of the v8 Cyclone than a successor to the Cyclone v10. Instead of the horizontal inline motor-and-bin arrangement of the Cyclone v10, Dyson has adopted the more compact layout of the v8, with the motor and dustbin mounted vertically just in front of the trigger-less hand grip. It's a design that's noticeably shorter and easier to use with detail tools and, of course, it's much better suited to mounting the unit on its accompanying charging and self-emptying dock.

Interestingly, all three units boast the same suction power, namely 150 air watts. This figure is considerably lower than that of the popular v15 Detect (240AW) and way lower than the Gen5detect (280AW). Nevertheless, suction power isn't everything because the design of the brush head is arguably even more important, which I'll get to in a minute.

The v10 Konical's diminutive proportions make it feel exceptionally nimble. At just 3.60lbs/1.63kg, the hand unit weighs roughly the same as the v10 Cyclone and about 25g heavier than the v8. However, because its center of gravity sits closer to the user's hand, it produces less wrist fatigue when cleaning stairs and upholstery, or reaching into awkward spaces. In fact, I consider this model's weight to be right in the sweet spot for quick shifts around the house just before guests arrive.

(Image credit: Future)

The Dyson Konical's brush head is one of this vac's most distinctive features since it replaces the conventional cylindrical roller with a tapered, conical design that's engineered to minimize hair wrap. Cast from shiny and very tough Polycarbonate-like plastic with stiff nylon bristles for beating dust out of carpet and a row of soft fluffy fibers to help protect delicate hard floors, this brush head is pretty radical but it works wonders on all floor types.

Yes, the tapered front end does make it trickier to run it head-on against skirting boards but then again you're better off using the side of the head and following the contours of the wall when collecting edge dust because there's plenty of suction between the end of the roller and the enclosed edge of the outer casing. However, I should point out that the raised center area of the brush head is taller than other models and that means it won’t go under some low furnishings.

Where most standard rollers use a comb system to mitigate hair wrap, this model's cone-shaped roller ensures that long hair naturally migrates towards the narrower end of the cone, where it's lifted away from the roller and fed directly into the dustbin. A couple of small combs fitted to the rear further help the process. The result is far less time spent cutting tangled hair from the brush, making it particularly useful in homes with shedding long-haired pets like golden retrievers and German shepherds.

(Image credit: Future)

Beyond its anti-tangle credentials, the Konical's unique brush head performs extremely well across a variety of floor types. It transitions smoothly between hard flooring and deep-pile carpets, and sweeps up both fine dust and larger debris with aplomb. The head is also surprisingly maneuverable, pivoting easily around furniture legs and into tighter spaces. And for those who have trouble seeing the state of the floor, this model is equipped with Dyson's laser-like green beam, which illuminates the path ahead in amazing detail, especially on hard floors.

The Dyson V10 Konical's 0.52 qt (0.5 liter) cyclone bin system offers the best of both worlds: it can be emptied manually using Dyson's familiar point-and-shoot mechanism or you can place the vacuum on the Konical Auto-empty Dok and leave it to be automatically emptied into the dock's large disposable dust bag.

(Image credit: Future)

Unlike many earlier Dyson cordless vacuums, the V10 Konical dispenses with the company's long-standing trigger-operated power switch in favor of a simple on/off button. It's a welcome change that eliminates finger fatigue during longer cleaning sessions. Meanwhile, three selectable suction levels — Eco, Medium and Max — allow you to balance cleaning performance against battery life, with the lowest settings suited to everyday dust collection on hard flooring and Max mode reserved for carpets, larger debris and more demanding cleaning tasks.

Rather disappointingly for a modern vac in this high price band, the v10 Konical lacks an automatic dust sensor to boost motor power when moving the head over particularly grubby areas. For that type of scenario you will need to switch to Medium or Max mode manually.

(Image credit: Future)

You get two cleanable HEPA filters with this model, one at the top of the hand unit and the other to the rear. Combined, these filters provide Dyson's "five-stage filtration that captures 99.99% of microscopic particles as small as 0.1 microns". Par for the course.

Regarding this model's battery life, Dyson's states a running time of up to 60 minutes, but this is when it's used in Eco mode on hard floor. However, as my results show in the Performance chapter below, this little cleaning tyke punches way above its weight when it comes to running times. Also, the battery is thankfully swappable so it's worth investing in another if your abode is on the larger side.

As you'd expect for a Dyson product, build quality is exemplary. The plastics feel dense and precisely moulded, every attachment clicks confidently into place and there are no obvious compromises despite the machine's relatively compact dimensions. In the pantheon of compact cordless stick vacs, this one is as close to perfection as it gets.

Score ref: 4.5/5

Dock design

The new Dyson v10 Konical + Auto-empty Dok is an unusual double act in the world of vacuum cleaners because its tall-standing dock not only charges the small and perfectly-formed v10 Konical hand unit, but it also empties the contents of the vac's small bagless bin into a much larger sealed 2.64qt (2.5 liters) dust bag which can be thrown away after a month or two of use. Wahey, no more flicking latches, or plumes of dust wafting into your face every time you visit the kitchen bin.

Before we discuss the technical elements of this dock, let's first address the elephant in the room. At 47.24 x 7 x 6.69i inches (120 x 18 x 17cm) this dock is ridiculously tall and the first inkling you get of its size is when the enormous box arrives on your doorstep — so huge, you may genuinely wonder whether you'd accidentally ordered a build-it-yourself aircraft instead of a simple vacuum cleaner.

After much rummaging through piles of cardboard packaging (no plastics or styrofoam here), I soon had the whole system installed under my stairs — the only space I could find short of rearranging the utility room where it ultimately belongs.

The first thing I noticed is that the dock itself isn't especially heavy, which means you will need to support it with the other hand when pushing the spring-loaded side door to access the two hand tools it comes with: a mini motorized brush and a detail nozzle. There's also a C-clip for holding a third accessory so I raided my Gen5detect collection of tools and attached Dyson's handy soft brush which I think is one of the best tools for cleaning shelves, computer keyboards, etc. Just below is a second cupboard for the Dok's disposable dust bag.

(Image credit: Future)

The Dyson Dok's interface is completely different from those adopted by Roborock and Tineco. With those brands you simply drop the hand unit's bin section into the top of the dock for automatic emptying, charging and storage. Conversely, the design of the v10 Konical's hand unit — and specifically its bin — requires attaching it to the dock from beneath by inserting the battery section into a swing-out portal and pushing the hand unit firmly into the circular suction housing. Granted, it's not as intuitive a mounting system as the Roborock and Tineco method but, despite its height, I think the complete package is more aesthetically pleasing to look at when everything's in situ.

Regarding the bin-emptying process, the moment you push the hand unit into the housing, the suction kicks in and stays on for 30 seconds. You can easily halt the suction process by pressing the red 'stop' button located close by.

(Image credit: Future)

Despite some shortcomings — especially the occasional times when it has failed to empty the v10’s bin because it was too clogged with hair — I've grown to like this new Dyson Dok. Yes, it's very tall but then it's also quite slim and the black colorway means it doesn't stick out like a sore thumb unless placed in a living room against a white wall.

If you have mostly hard floors or carpets that don’t shed fibers, I happen to think it's worth the extra it adds to the cost of purchasing the v10 Konical, mostly because I don't miss the hassle of regularly returning to the kitchen bin to manually empty the contents of the v10's bin or wrestling with a wall-mounted charging bracket.

Score ref: 3.5/5

• Design score: 4/5

Dyson v10 Konical + Auto-empty Dok: performance

• Excellent all-floor vacuum performance
• Genuinely tangle-free roller
• Dock struggles with compacted hair

As usual, for my vacuum tests I selected a range of obstreperous ingredients — oats, muesli, rice, flour and loosely broken cornflakes — and sprinkled them over the wooden floor of my kitchen and a rug in the living room.

From my own robot vacuuming experience I've found that cotton strands from my wife's sewing room are among the worst things for a vacuum cleaner to deal with, so I also scattered some strands of cotton on the carpet to see how effectively the cone-shaped brush head was at clearing them. I also ran a battery test to see how long the v10 Konical ran in Medium mode on carpet before the battery gave up the ghost.

Here are my results…

(Image credit: Future)

The first thing I did was scatter some cotton threads of different lengths over a carpeted rug. Cotton strands are notorious for wrapping around brush heads so I was eager to see how well Dyson's R&D department had nailed this conundrum.

Since the Dyson's Konical head doesn't have thin rubber paddles that tear very easily when tightly wrapped in cotton I was really gunning for a successful outcome and I couldn't have been more amazed by the results because, despite a surfeit of cotton pieces on the carpet, not one of them tangled around the roller. If you have a sewing room this is unequivocally the best vacuum cleaner for you.

(Image credit: Future)

I then proceeded with the detritus tests, first using the aforementioned ingredients on my kitchen floor. I have no anomalies to report here because if deftly collected almost everything in its path in a single sweep. All I had to do was run a few more passes to collect the rest to either side and few quick whizzes along the outer edges to pick up some of the rice that had been inevitably scattered.

(Image credit: Future)

My second test was much the same, only on a rug. Again the v10 Konical collected most of the debris on its first pass followed by a few extra passes to collect the rest. Although not as immediately successful as the hard floor test, it was good enough for me.

I personally think this little vac is a five-star performer when it comes to any type of flooring because I also used it on an old carpet upstairs that sheds a lot of fibers and a very deep-pile shaggy carpet in the guest room. It never bogged down once on the deep pile, even when in Medium mode; something that often occurs with my Gen5detect.

(Image credit: Future)

However, the same level of success can't be said for the Dyson Dok because I've had two instances when the dock’s suction has failed to empty the contents of the hand unit — even after two 30-second attempts. I put this down to the state of my carpets that are shedding a ton of fibers, along with insurmountable levels of labrador hair. On the plus side, the dock has successfully emptied the v10's bin every time it's been used on hard floor and, likewise, both emptying sessions after the above tests. Nevertheless, I still think prospective buyers should be aware if they have a lot of older carpet and shedding pets.

For my battery test I put the v10 Konical into Medium mode – my favorite setting – and set it up on a carpet using the Konical head for maximum brush resistance. I then left it to run until the battery gave out. After an impressive 21 minutes and 30 seconds of continual running, the battery suddenly died, and at no time did I hear anything to suggest that the motor power was fading. It just kept going at the same speed and frequency before suddenly shutting off. That's a resoundingly good result for a compact unit of this weight and size, and I'm pretty convinced it would go on running for the full stated 60 minutes when in Eco mode.

(Image credit: Future)

Final thoughts? While I think the v10 Konical is a sterling lightweight stick vac for both day-to-day and intensive use, the jury's still out on the Dyson Dok, which is not only exceedingly tall and incongruous but not especially functional when faced with large amounts of compacted hair and fibers.

• Performance score: 4/5

Should you buy the Dyson v10 Konical + Auto-empty Dok?Dyson v10 Konical + Auto-empty Dok: score card

Section

Notes

Score

Value for money

Premium price, but the self-emptying dock does add convenience. I just wish it wasn't so tall.

3.5/5

Design

Smartly engineered, v8-inspired styling delivers excellent balance, usability and innovative dust disposal.

4/5

Performance

Powerful cleaning performance with smooth handling, effective suction and impressive anti-tangle technology. But the dock’s nowhere near perfect

4/5

Average rating

4/5

Buy it if

You have shedding pets

The v10 Konical is an excellent cordless stick vac that performs exceptionally well with pet hair

You're not keen on manually emptying a bin

While not 100% effective, the Dyson Dok is still a worthwhile addition for clean, dust-free emptying

You're not as fit as you used to be

The v10 Konical is one of the lightest and easiest-to-use stick vacs on the market

Don't buy it if

You don't have space for a highly visible dock 

The whole package is highly visible and impossible to ignore

You're not very tech minded

The Dok interface adds an extra learning curve for those who are not physics minded

You are on a tight budget

Dyson products are always priced at a premium

How I tested the Dyson v10 Konical + Auto-empty Dok

(Image credit: Future)

We tech journos engage in a lot of rigmarole so you don't have to. Hence, we push the products we test to the limits of their functionality. In the pantheon of cordless stick vacs, this means creating a series of worst-case scenarios to see how well the product performs when faced with more debris than it would normally encounter.

We also test battery running times and evaluate the product's ease of use during day-to-day cleaning scenarios. We then studiously consider the amount of stars the product is worth before sending the review out into the world.

First reviewed August 2026

The World Cup has finished, completing a wave of anticipation, celebration, and distraction that stretched far beyond the stadiums.

For employers, it also served as a real-time test of workforce operations as schedules, staffing needs, and employee engagement were all put under the spotlight.

During the six-week tournament, millions of employees were watching matches, adjusting schedules, arriving late, swapping shifts, requesting time off, or turning up tired after late nights.

New UKG research of 8,000 employees across Australia, Canada, France, Germany, Mexico, the Netherlands, the UK, and the US estimates the tournament could have resulted in at least £12.6 billion in lost productivity.

In the UK alone, the impact could exceed £680 million, with employees not just following matches during working hours, alter their schedules, or missing work altogether - many admitting they went to work hungover, secretly streamed matches, and pushed the limits of what their employer would allow.

If England had won the final, almost a third of UK employees said they would have taken the day off whether that absence had been approved.

What the World Cup Revealed About the Future of Work

That created a real challenge for employers. But the bigger lesson is not about football. It is about how work now happens.

The World Cup is a high-profile example of something organizations face every day: unpredictable employee behavior, sudden changes in demand, last-minute absences, weather disruption, supply chain delays, new regulations, and shifting customer expectations.

For frontline-heavy industries in particular, disruption is not an exception to the operating model. It is the operating environment.

The question is whether workplace technology is built for that reality.

Many workforce systems were designed around predictability. They record schedules, track attendance, and report what happened after the fact. That matters, but it is no longer enough.

When conditions change by the hour, organizations need more than systems of record. They need systems of action that help managers see risk earlier, make better decisions faster, and keep work moving in real time.

Three Workforce Strategies That Help Employers Stay Ahead of Disruption

The employers that came out ahead during the World Cup, and during the everyday disruption that followed it, will have done three things differently:

1. See the disruption before it happens

Too often, workforce disruption becomes visible only once it has created a gap. Someone does not arrive. A shift is suddenly under-covered. A manager starts calling around for support.

The business reacts after the damage has begun.

The World Cup gave organizations a chance to get ahead of that pattern.

Employees already signaled intent. They knew which matches mattered to them. They knew when they were likely to want flexibility, when they may have needed time off, and when they were more likely to be distracted or unavailable. Organizations that capture that intent early can turn it into useful operational data.

That does not mean monitoring employees or trying to control their behavior. It means giving people approved ways to communicate availability, preferences, and likely conflicts before they become last-minute absences. When that information is combined with historical absence patterns, demand forecasts, local schedules, and workforce data, managers can identify where risk is most likely to emerge.

A retailer, manufacturer, logistics operation, or hospitality business does not need to know every individual decision. But it does need to know where coverage pressure is building. High-interest match days, late kick-offs, local celebrations, and major national fixtures can all create predictable patterns of disruption.

Seeing that risk early allows organizations to plan differently. They can adjust staffing levels, open additional shifts, prepare contingency cover, or communicate expectations before managers are forced into crisis mode.

2. Design flexibility into the operating model

The instinctive response to disruption is often to tighten control. But rigid rules can push behavior underground.

If employees believe there is no fair or practical way to adjust work around major life moments, they are more likely to find informal workarounds. That can mean last-minute sickness calls, unapproved absences, shift swaps that managers do not see, or colleagues covering gaps without the right skills, rest periods, or compliance checks.

The better approach is to make flexibility visible, fair, and operationally safe.

That means giving employees clear, approved ways to request time off, swap shifts, volunteer for extra hours, adjust availability, or pick up open shifts. It also means giving managers the tools to assess those requests against business need, skills, fatigue, labor rules, and fairness.

This is especially important on the frontline, where the margin for error is small. A missed shift in an office may delay a meeting. A missed shift in healthcare, retail, manufacturing, hospitality, or logistics can affect safety, service, cost, and compliance.

Flexibility cannot sit outside the workforce strategy. It must be built into it.

For employers, that shift is powerful. Flexibility becomes less of a concession and more of an operating capability.

Employees get more transparency and control. Managers get fewer surprises. The business gets a better chance of protecting service levels without treating people like variables in a spreadsheet.

3. Act in real time when the plan changes

Even the best World Cup plan will not survive unchanged.

A match goes to penalties. Demand spikes unexpectedly. More employees call in sick than forecast. A local team advances further than expected. A manager discovers at short notice that the people available do not have the right skills or certifications.

This is where many workforce systems fall short. They can show the rota. They can record the absence. But they do not always help managers decide what to do next.

Modern workforce management has to move from static planning to real-time execution. Managers need to know where gaps exist, who is available, who is qualified, who is approaching overtime or fatigue limits, and what action will create the best outcome for the business and the employee.

That is where data and AI can play a practical role. Not generic AI layered onto old processes, but intelligence that understands workforce context and helps recommend the next best action. Should a manager offer an open shift? Redeploy someone from a lower-demand area? Approve a swap? Escalate a compliance risk? Adjust breaks? Bring in contingent support?

The value is not simply in having more data. It is in turning workforce data into action while there is still time to influence the outcome.

The real stress test for workplace technology is not whether an organization can create a schedule weeks in advance, but whether it can adapt that schedule minutes after conditions change.

The World Cup is over. The operating lesson is not.

Every organization will face its own version of this disruption: seasonal demand, illness, weather, regulatory change, major events, economic pressure, and shifting employee expectations. The companies that treat these moments as one-off exceptions will keep solving them manually, shift by shift and manager by manager.

The companies that come out ahead will build a more responsive workforce model. They will see risk before it becomes disruption. They will design flexibility into the way work happens. And they will equip managers to act in real time when the plan changes.

The future of workforce management is not about predicting everything perfectly. It is about giving organizations the visibility, intelligence, and agility to keep moving when reality refuses to follow the plan.

We've ranked the best HR software.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

The IMF and Bank of England have both recently raised concerns about the risks AI could pose to the financial system, from cyber threats to systemic vulnerabilities and governance gaps. Against that backdrop, institutions are facing growing pressure to demonstrate clear accountability for how AI is used, particularly when decisions impact customer outcomes, market activity and compliance decisions.

Financial services have traditionally taken a cautious approach to AI because of the regulatory and operational risks involved. But AI is now becoming more deeply embedded across the sector, supporting everything from fraud detection and customer service to compliance monitoring and internal operations.

As adoption expands, governance frameworks that were designed for conventional software and data systems are being tested by AI models that can evolve, generate unpredictable outputs and rely on increasingly complex data environments.

Why governance expectations are growing

This growing focus on accountability is becoming increasingly visible across the sector. Moves such as HSBC appointing its first Chief AI Officer reflect a broader recognition that oversight can no longer sit across disconnected teams or experimental projects.

Meanwhile, many institutions, including Barclays and Lloyds Banking Group, have recently joined the Financial Conduct Authority’s initiative to test AI in real-world conditions under strict controls, while the Bank of England has outlined plans to assess potential risks to financial stability through scenario analysis and simulations.

For finance firms, these developments are likely to increase expectations around how AI systems are monitored, tested and governed internally. Organizations will need clearer oversight of third-party AI providers, stronger documentation around how AI models make decisions, and more robust processes for identifying and escalating risks.

The barriers to strong AI governance

Despite growing regulatory scrutiny, financial institutions still face significant barriers to implementing stronger AI governance, particularly around fragmented data. Many firms still operate across disconnected systems, making it difficult to create a consistent view across risk, compliance, operations and customer activity.

This becomes more challenging as AI is introduced. Models depend on large volumes of data flowing across multiple systems, but when those systems are siloed, it becomes harder to trace how information is used or how decisions are made. Without clear data lineage, organizations may struggle to validate AI decisions under regulatory scrutiny.

Data quality is becoming just as important as data access. Even advanced AI models can produce unreliable results if they are trained on incomplete, outdated or poorly governed information. At the same time, identifying which datasets will improve decision-making, rather than adding complexity, remains a challenge.

For financial institutions operating across complex legacy systems, maintaining accurate, trusted and consistently managed data at scale will be critical as AI adoption accelerates, particularly across areas such as fraud detection, anti-money laundering and customer risk systems where siloed data can limit a complete and accurate view of risk.

Building the foundations for responsible AI

For many finance companies, the next step is transforming these fragmented datasets into stronger data foundations that support AI at scale.

This means creating connected, well-governed data environments where information can move consistently across systems, data quality is maintained more effectively, and accountability is embedded into day-to-day operations rather than treated as a standalone compliance exercise.

This joined-up view is particularly valuable across the customer journey. When someone opens a bank account, they move through several stages including identity verification, onboarding, digital registration and their first transactions. Banks need to see that journey as a whole rather than as disconnected steps. With that visibility, teams can investigate issues more quickly, improve services and track results in real time.

Why responsible AI requires shared ownership

Building more connected data environments requires a coordinated approach to accountability across institutions, with responsibility formalized rather than sitting in isolation with individual teams. As more firms appoint Chief AI Officers, close collaboration with Chief Data Officers will become increasingly important to ensure AI governance is built on strong data quality, clear ownership and consistent standards across the organization.

In regulated firms, technology teams, data teams, AI specialists, and business stakeholders all share an obligation to understand the importance of data quality and the consequences it has on decision-making.

This more collaborative approach can also improve how teams operate, ensuring insights are not limited to technical functions alone. Giving colleagues in retail banking, lending and compliance access to timely information enables faster, more informed decisions at every level and helps embed accountability for AI-driven outcomes in day-to-day operations.

Strong governance depends as much on operational visibility and human oversight as it does on the models themselves.

Preparing for AI adoption at scale

Over the next few years, financial services will move from isolated AI pilots towards broader adoption at scale, but it must happen in a way that remains controlled and transparent. Organizations that can build the right foundations now will be better place to expand AI use confidently, while those without them risk inconsistency and greater operational exposure.

Ultimately, the firms that succeed in the financial sector will be those that combine innovation with strong governance and clear human oversight, using AI tools to drive sustainable progress while maintaining strong trust as adoption grows across the sector.

We've featured the best business intelligence platform.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

OnePlus has opened a ColorOS 17 closed beta for its 15 series in India, signaling its move beyond OxygenOS and new considerations for IT teams.

The post OnePlus Opens ColorOS Beta for 15 Series in India appeared first on TechRepublic.

Apple patched CVE-2026-65400 in macOS Tahoe, Sequoia, and Sonoma after a Screen Sharing flaw allowed authentication without valid credentials.

The post Apple Patches Mac Screen Sharing Flaw That Could Bypass Authentication appeared first on TechRepublic.

Commentary: Google has the potential to advance the state of the art, but we’ll see if it just wants flashy AI features instead.

High traffic moments create some of the most demanding conditions that engineering teams face. Seasonal peaks such as major sales events or public holidays can bring levels of demand far beyond what systems experience day to day​.​ These sudden surges often expose weaknesses that are usually less detectable during normal operation.

Peak periods are also becoming more intense for retailers, ecommerce brands and the travel and hospitality sector, as year-end sales events have evolved into global spending moments.

Consumers are increasingly planning purchases around these events, which is concentrating demand into shorter and higher-pressure periods.

These industries tend to feel this pressure especially strongly because customer behavior is so closely tied to digital performance. A site loading in one second can achieve conversion rates three times higher than a site that loads in five seconds, highlighting how sensitive these environments are to even minor degradations.

In these situations, businesses rely on a smooth digital experience to meet demand and maintain customer loyalty, which heightens the pressure on engineering teams to ensure systems remain stable under sustained and extremely concentrated demand.

As a result, organizations are turning to AI-assisted incident intelligence, with data showing it can cut recovery times by nearly 50 percent.

Much of this time save is determined in the opening minutes of an incident as teams try to understand what’s broken and where to focus first. That’s where AI is starting to become most valuable, especially during high‑traffic moments when speed and clarity really count.

The first 20 minutes of an outage

The first moments of an outage often set the tone for how long disruption will last. Many teams still begin with manual checks to identify issues, but the sheer volume of alerts makes it difficult to gain a clear view of the problem this way.

Engineers turn to signals such as bounce rates, session drop offs and real user monitoring to understand how systems are behaving under pressure. However, these signals are often buried within a much larger flow of alerts that compete for attention. This avalanche makes it difficult to isolate the one that points to the root cause.

The challenge is not simply the volume of information but the complexity of modern environments. Even experienced engineers can struggle because modern systems contain many interdependent components. Problems can emerge in unexpected areas and teams frequently need to investigate several routes from the beginning, which continues to add delay.

Reducing alert noise under pressure

Modern environments generate large volumes of notifications, many of which are duplicates or low value alerts presented with the same urgency as critical issues.

Industry surveys report that 63 percent of organizations deal with duplicate alerts, making it harder to distinguish real problems from background noise.

During peak demand, this becomes even more difficult for engineers to manage. Between 20–30 percent of alerts are ignored or never investigated, simply because the volume is too high.

Under this pressure, response times become slower and trust weakens in alerting systems, leaving teams unsure which issues require immediate attention.

Observability’s impact on issue resolution

To address this, teams need a clearer view of what is actually happening across their systems.

Observability, combined with AI, goes beyond traditional network monitoring by connecting data across applications, infrastructure, and user experience to explain what is failing, and why. By linking related signals, teams can quickly identify the root cause of an issue and understand its impact on users. What may look like separate problems at first glance, such as CPU spikes, latency increases or error logs often point back to a single fault affecting multiple layers of the system.

Research shows that observability reduces overall alert noise by 27 percent compared with manual monitoring. When looking at repetitive, low-impact notifications that distract teams from genuine outages, known as ‘noisy alerts’, this impact becomes even clearer, with AI-enabled teams reducing these from over 70 percent to 46 percent.

The result is a shift from reactive firefighting to informed and targeted problem solving, allowing engineers to spend less time chasing symptoms and more time resolving the underlying cause.

How AI is reshaping performance during peak demand

Retail, e-commerce, travel and hospitality businesses all depend heavily on peak trading periods and even short disruption can impact overall earnings for the year. A high-impact outage costs retailers a median of $1 million per hour, per the 2025 Retail & eCommerce Observability Report by New Relic.

That financial exposure is driving a shift in how companies approach reliability. In 2025, 50% of retail respondents said AI was the primary reason they invested in observability – 11 points higher than the all-industry average. Retailers increasingly see AI as the mechanism for automating troubleshooting, accelerating post-incident reviews, and enabling remediation actions like rollbacks or configuration updates.

Investing in AI is translating directly into faster recovery. Mean Time to ​​​​Close (MTTC) shows how quickly teams can recover from disruption and is increasingly used as a measure of performance. During peak periods in May 2025, AI-enabled teams averaged 26.75 minutes per issue, compared with 50.23 minutes for non-AI users. Across the full calendar year, AI users resolved issues around 25 percent faster.

Beyond resilience, these gains free up engineering capacity – essential for delivering new features and supporting growth. On average, AI-enabled teams have been shown to ship code at an 80% higher frequency than non-AI users. During peak demand periods, this gap becomes even more visible, with non-AI teams averaging 87 deployments per day compared with up to 453 for AI-enabled teams.

The advantage of faster insight

Peak trading periods tend to expose how well teams can see what is happening and respond in real time. Observability and AI help by reducing noise and surfacing the signals that actually matter, making it easier to move from detection to resolution.

This ability to act with clarity under pressure is increasingly what separates leading teams from those that struggle when demand is at its highest.

We've ranked the best customer experience tools.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

High traffic moments create some of the most demanding conditions that engineering teams face. Seasonal peaks such as major sales events or public holidays can bring levels of demand far beyond what systems experience day to day​.​ These sudden surges often expose weaknesses that are usually less detectable during normal operation.

Peak periods are also becoming more intense for retailers, ecommerce brands and the travel and hospitality sector, as year-end sales events have evolved into global spending moments.

Consumers are increasingly planning purchases around these events, which is concentrating demand into shorter and higher-pressure periods.

These industries tend to feel this pressure especially strongly because customer behavior is so closely tied to digital performance. A site loading in one second can achieve conversion rates three times higher than a site that loads in five seconds, highlighting how sensitive these environments are to even minor degradations.

In these situations, businesses rely on a smooth digital experience to meet demand and maintain customer loyalty, which heightens the pressure on engineering teams to ensure systems remain stable under sustained and extremely concentrated demand.

As a result, organizations are turning to AI-assisted incident intelligence, with data showing it can cut recovery times by nearly 50 percent.

Much of this time save is determined in the opening minutes of an incident as teams try to understand what’s broken and where to focus first. That’s where AI is starting to become most valuable, especially during high‑traffic moments when speed and clarity really count.

The first 20 minutes of an outage

The first moments of an outage often set the tone for how long disruption will last. Many teams still begin with manual checks to identify issues, but the sheer volume of alerts makes it difficult to gain a clear view of the problem this way.

Engineers turn to signals such as bounce rates, session drop offs and real user monitoring to understand how systems are behaving under pressure. However, these signals are often buried within a much larger flow of alerts that compete for attention. This avalanche makes it difficult to isolate the one that points to the root cause.

The challenge is not simply the volume of information but the complexity of modern environments. Even experienced engineers can struggle because modern systems contain many interdependent components. Problems can emerge in unexpected areas and teams frequently need to investigate several routes from the beginning, which continues to add delay.

Reducing alert noise under pressure

Modern environments generate large volumes of notifications, many of which are duplicates or low value alerts presented with the same urgency as critical issues.

Industry surveys report that 63 percent of organizations deal with duplicate alerts, making it harder to distinguish real problems from background noise.

During peak demand, this becomes even more difficult for engineers to manage. Between 20–30 percent of alerts are ignored or never investigated, simply because the volume is too high.

Under this pressure, response times become slower and trust weakens in alerting systems, leaving teams unsure which issues require immediate attention.

Observability’s impact on issue resolution

To address this, teams need a clearer view of what is actually happening across their systems.

Observability, combined with AI, goes beyond traditional network monitoring by connecting data across applications, infrastructure, and user experience to explain what is failing, and why. By linking related signals, teams can quickly identify the root cause of an issue and understand its impact on users. What may look like separate problems at first glance, such as CPU spikes, latency increases or error logs often point back to a single fault affecting multiple layers of the system.

Research shows that observability reduces overall alert noise by 27 percent compared with manual monitoring. When looking at repetitive, low-impact notifications that distract teams from genuine outages, known as ‘noisy alerts’, this impact becomes even clearer, with AI-enabled teams reducing these from over 70 percent to 46 percent.

The result is a shift from reactive firefighting to informed and targeted problem solving, allowing engineers to spend less time chasing symptoms and more time resolving the underlying cause.

How AI is reshaping performance during peak demand

Retail, e-commerce, travel and hospitality businesses all depend heavily on peak trading periods and even short disruption can impact overall earnings for the year. A high-impact outage costs retailers a median of $1 million per hour, per the 2025 Retail & eCommerce Observability Report by New Relic.

That financial exposure is driving a shift in how companies approach reliability. In 2025, 50% of retail respondents said AI was the primary reason they invested in observability – 11 points higher than the all-industry average. Retailers increasingly see AI as the mechanism for automating troubleshooting, accelerating post-incident reviews, and enabling remediation actions like rollbacks or configuration updates.

Investing in AI is translating directly into faster recovery. Mean Time to ​​​​Close (MTTC) shows how quickly teams can recover from disruption and is increasingly used as a measure of performance. During peak periods in May 2025, AI-enabled teams averaged 26.75 minutes per issue, compared with 50.23 minutes for non-AI users. Across the full calendar year, AI users resolved issues around 25 percent faster.

Beyond resilience, these gains free up engineering capacity – essential for delivering new features and supporting growth. On average, AI-enabled teams have been shown to ship code at an 80% higher frequency than non-AI users. During peak demand periods, this gap becomes even more visible, with non-AI teams averaging 87 deployments per day compared with up to 453 for AI-enabled teams.

The advantage of faster insight

Peak trading periods tend to expose how well teams can see what is happening and respond in real time. Observability and AI help by reducing noise and surfacing the signals that actually matter, making it easier to move from detection to resolution.

This ability to act with clarity under pressure is increasingly what separates leading teams from those that struggle when demand is at its highest.

We've ranked the best customer experience tools.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

Summer holidays are a great time for soaking up the sun, but if your booked trip location is a little hotter than you were expecting this year — dare I say it, slightly too hot — it's worth making a plan to keep yourself comfortable enough to enjoy the break. Below, I've rounded up my keep-cool kit list for tackling too-balmy summer days.

To start off, arm yourself with a portable fan. Both Shark and Dyson have come out with stellar options this summer. The Shark ChillPill has a cooling plate and misting function, for a multi-pronged attack on the heat, while the Dyson HushJet Mini Cool is just a straightforward fan... but an extremely effective one (we preferred the HushJet in our side-by-side tests). If you're holidaying more locally, I've also included a couple of cordless desktop fans that would be great for more general use, including in the bedroom while you're trying to sleep.

I'd also seek out some good insulated containers for your food and drinks — Yeti and Hydro Flask make my favorite water bottles (go for a straw cap to encourage you to keep sipping on-the-go) and soft coolers. Finally, I've included some cheaper products for a quick hit of instant coldness: snappable cold towels and a sleep mask you can pop in the freezer.

Cool customers

Sukeen Cooling Towel (4 pack)

Yeti Daytrip 5L Lunch Box

Dyson HushJet Mini Cool Fan

Read our full review

Shark ChillPill

Read our full review

Shark FlexBreeze HydroGo Misting Portable Fan

Read our full review

Manta Sleep Cool Sleep Mask

Hydro Flask 21oz / 620ml with Flex Straw Cap

Meaco MeacoFan Sefte 8" Portable Battery Air Circulator

Read our full review

Pros

• Perfectly portable
• Operates quietly
• Strong airflow
• Rechargeable
• Automatic fan speed adjustment

Cons

• Oscillation limited to 70 degrees
• Battery unlikely to last all night
• System beeps may be loud and high-pitched for some

Yeti Hopper M12 Backpack Soft Cooler

Summer holidays are a great time for soaking up the sun, but if your booked trip location is a little hotter than you were expecting this year — dare I say it, slightly too hot — it's worth making a plan to keep yourself comfortable enough to enjoy the break. Below, I've rounded up my keep-cool kit list for tackling too-balmy summer days.

To start off, arm yourself with a portable fan. Both Shark and Dyson have come out with stellar options this summer. The Shark ChillPill has a cooling plate and misting function, for a multi-pronged attack on the heat, while the Dyson HushJet Mini Cool is just a straightforward fan... but an extremely effective one (we preferred the HushJet in our side-by-side tests). If you're holidaying more locally, I've also included a couple of cordless desktop fans that would be great for more general use, including in the bedroom while you're trying to sleep.

I'd also seek out some good insulated containers for your food and drinks — Yeti and Hydro Flask make my favorite water bottles (go for a straw cap to encourage you to keep sipping on-the-go) and soft coolers. Finally, I've included some cheaper products for a quick hit of instant coldness: snappable cold towels and a sleep mask you can pop in the freezer.

Cool customers

Sukeen Cooling Towel (4 pack)

Yeti Daytrip 5L Lunch Box

Dyson HushJet Mini Cool Fan

Read our full review

Shark ChillPill

Read our full review

Shark FlexBreeze HydroGo Misting Portable Fan

Read our full review

Manta Sleep Cool Sleep Mask

Hydro Flask 21oz / 620ml with Flex Straw Cap

Meaco MeacoFan Sefte 8" Portable Battery Air Circulator

Read our full review

Pros

• Perfectly portable
• Operates quietly
• Strong airflow
• Rechargeable
• Automatic fan speed adjustment

Cons

• Oscillation limited to 70 degrees
• Battery unlikely to last all night
• System beeps may be loud and high-pitched for some

Yeti Hopper M12 Backpack Soft Cooler

• Elite Swiss audio specialist Goldmund launches Telos 9800 amplifier
• Looks like Eve from Wall-E
• Costs $500,000 / £370,000 (around AU$705,000)

You can get Wall-E toys for about $10, but if you want a huge-scale prototype model of Eve (which also plays your music), it'll cost you a little bit more… 

I jest, of course. Swiss home audio company Goldmund has unveiled the Telos 9800, a new amplifier which looks inspired by the Pixar movie — or, to my eyes, one of the robots from Love, Death & Robots' Three Robots episodes.

This amplifier costs $500,00 / £370,000 (about AU$700,000), so it's a lot more expensive than a toy — and let me be clear, this is no toy. It's a serious product for hi-fi enthusiasts-slash-audiophiles and a luxury item, to be sure.

What does Telos mean? According to a brief Wikipedia search (after a brief Google search, in which AI Overview gave me something totally irrelevant), it's a term Aristotle used to refer to the intended end state of a natural creature. Deep.

The power tower

(Image credit: Goldmund )

In our case, the Goldmund Telos 9800 is the end state of your home hi-fi set-up, and not just because it'll blow every last penny out of your budget.

It offers a whopping 1,560W of power at 8 ohms, with a built-in transformer (9.7kVA capacity), to avoid frying your hi-fi kit.

As you'll see in the images, there are two stages of the Telos: one is a power supply and the other is the amplifier, connected but not pressed up against each other.

It connects via XLR or RCA, with S/PDIF input and output too.

As you can imagine from the pictures, this thing is pretty huge. It's 1.367 meters tall, with a base of 50 x 50cm. The unit weighs 360kg too, so if you're ordering one, you really do need to factor in shipping and delivery costs.

Ultimately, it's not built for the average home hi-fi set-up. It's built for the "money no object" buyer, and for those of us unburdened by delivery costs. That is not this writer. But one can still dream…

• Elite Swiss audio specialist Goldmund launches Telos 9800 amplifier
• Looks like Eve from Wall-E
• Costs $500,000 / £370,000 (around AU$705,000)

You can get Wall-E toys for about $10, but if you want a huge-scale prototype model of Eve (which also plays your music), it'll cost you a little bit more… 

I jest, of course. Swiss home audio company Goldmund has unveiled the Telos 9800, a new amplifier which looks inspired by the Pixar movie — or, to my eyes, one of the robots from Love, Death & Robots' Three Robots episodes.

This amplifier costs $500,00 / £370,000 (about AU$700,000), so it's a lot more expensive than a toy — and let me be clear, this is no toy. It's a serious product for hi-fi enthusiasts-slash-audiophiles and a luxury item, to be sure.

What does Telos mean? According to a brief Wikipedia search (after a brief Google search, in which AI Overview gave me something totally irrelevant), it's a term Aristotle used to refer to the intended end state of a natural creature. Deep.

The power tower

(Image credit: Goldmund )

In our case, the Goldmund Telos 9800 is the end state of your home hi-fi set-up, and not just because it'll blow every last penny out of your budget.

It offers a whopping 1,560W of power at 8 ohms, with a built-in transformer (9.7kVA capacity), to avoid frying your hi-fi kit.

As you'll see in the images, there are two stages of the Telos: one is a power supply and the other is the amplifier, connected but not pressed up against each other.

It connects via XLR or RCA, with S/PDIF input and output too.

As you can imagine from the pictures, this thing is pretty huge. It's 1.367 meters tall, with a base of 50 x 50cm. The unit weighs 360kg too, so if you're ordering one, you really do need to factor in shipping and delivery costs.

Ultimately, it's not built for the average home hi-fi set-up. It's built for the "money no object" buyer, and for those of us unburdened by delivery costs. That is not this writer. But one can still dream…

I tested top nonprofit payroll platforms and found OnPay offers the best value, SurePayroll is the most affordable, and Gusto is the easiest to use.

The post The Best Payroll Software for Nonprofits in 2026 appeared first on TechRepublic.

I’ve never particularly enjoyed running, especially when training solo, but it takes the least effort for me to prepare for in the morning compared to my preferred activities — cycling or badminton — and it’s also a nice cross-training option.

After reading about my colleagues using AI to build training plans, I thought it could be an opportunity for me to change how I feel about running, so I turned to Google Gemini and asked it to build a training plan to prepare for a major running event here in Australia, the Sydney City2Surf.

My goal was to try out a plan that could easily adapt after a setback, like an injury or illness, while balancing run training with my usual badminton sessions and bike rides within a week.

I also wanted to see if I could stick to running for longer compared to my previous attempts, which involved either winging it — running for as long as I could until I ran out of breath — or following a rigid online plan.

Setup

My initial prompt was “How realistic is it for a beginner runner to train for City2Surf starting next week?” It was in late December 2025, so Gemini replied that I had plenty of time, as the event was on August 9 this year.

City2Surf has a 14km route that starts from Sydney CBD and finishes at Bondi Beach, which explains the name. It’s an infamously hilly route, headlined by a 2km section midway through the course with an average gradient of about 3 to 4%, or 75 to 80m in elevation.

“Most beginner-friendly training plans only require 12–16 weeks,” the response read. “Starting now puts you in an excellent position to not just survive the race, but actually enjoy it and run the majority of the course.”

Here’s the general overview from Gemini:

Phase

Duration

Focus

Foundation (Now – March)

~12 Weeks

Focus on consistency. Aim for 2–3 days a week of a "Run-Walk" method (e.g., run 2 mins, walk 1 min).

Building (April – June)

~12 Weeks

Increase your long run distance once a week. Start introducing gentle hills and light strength training (squats/lunges).

Race Specific (July – August)

6–8 Weeks

Focus on endurance and Heartbreak Hill. Your longest run should reach 12km–13km about two weeks before race day.

To make sure I stuck to the plan, I asked Gemini how to enter the workouts into my old Garmin watch, and it gave me a step-by-step guide.

(Image credit: Future | Nico Arboleda)

I was also offered to test the newly released Garmin Forerunner 70 and 170 range while I was training, and I chose the 170 Music edition. I wanted to see if the built-in music function and Garmin Pay wireless payments were enough for me to leave my phone at home during training sessions.

Lugging my heavy iPhone 16 Pro Max in a running belt during my first few weeks of running became annoying, so the Forerunner was just what I needed. It also completely cuts down on distractions, and the voice prompts also helped keep me on track during interval sessions.

I managed to stick to the program for the first few months while keeping my social badminton games and bike rides. But things started to get tricky as I progressed into the second phase.

(Image credit: Future | Nico Arboleda)Setbacks and adjustments

Heading into phase 2 of my training plan, I unexpectedly got Achilles tendonitis, which my physiotherapist told me was the result of putting too much load too quickly on my legs and feet. Recovery took more than a month of rehab and rest.

When I was cleared to run again, I told Gemini I’d missed a few weeks and asked how I should adjust. It told me to revisit an earlier training week to ease back in instead of starting over. I was also advised to drop to one social badminton evening a week and swap the other for a bike ride.

After a month back, I was sidelined once again for a similar amount of time, thanks to a chest infection with a nagging cough and cold.

(Image credit: Future | Nico Arboleda)

Ultimately, I felt that these setbacks were enough for me to decide not to enter the City2Surf, even though Gemini said I still had enough time to train. I set my sights on next year’s event instead.

“Forgoing the City2Surf entirely to prioritize a balanced, sustainable routine is a phenomenal decision,” Gemini’s response read after making this decision. “Since you haven't registered yet, dropping the pressure of a hard August 9th deadline allows you to completely shift your mindset from 'panic training' to building a strong, bulletproof foundation for the long run.”

Looking back, I likely would have just quit after the first setback if I had been following a more rigid training plan. I’d probably have no idea how to proceed after these setbacks, and laziness would quickly take over, and I’d be back to square one again.

Refocused training

Without the pressure of a fixed race date, Gemini readjusted my plan over the next four weeks to focus on just two sessions per week: one day of run-walk intervals and one longer, uninterrupted easy jog before I move forward with a fresh training plan. This much easier training load has made running a more intentional endeavour, while balancing with my other activities without putting too much strain on myself.

Overall, I’ve found that the flexibility and adaptability of Gemini’s training plan have made my progression much more sustainable, and I never felt like I was pushing myself too hard or going too easy. Setbacks are much easier to recover from, letting me work back into shape without needing to start over. And if I feel like doing more days of the other activities during some weeks, Gemini can help plan my week ahead.

While I ultimately failed in my original objective of joining a popular running event, I ended up enjoying the journey of becoming a better runner at a more sustainable pace.

(Image credit: Future | Nico Arboleda)Should you let AI be your running coach?

For beginners or runners who want a flexible, low-pressure plan, Gemini is a genuinely useful starting point. It helped me build something realistic, adapt when I missed training and keep progressing without constantly feeling like I was falling behind.

I'd argue though that it's not a substitute for proper coaching. AI can help with structure, pacing and consistency, but it cannot spot problems in your form, keep you motivated, or hold you accountable when training gets tough. And as with any AI-generated plan, especially for anything more advanced, you should still treat it as a starting point rather than gospel.

For my purposes, though, Gemini was enough to turn running from a chore into something I could actually stick with.

• Shopping for a new Garmin watch? Check out the latest Garmin Australia coupons here.

• Forcepoint X-Labs publishes threat model for persistent memory poisoning
• Hidden text on a webpage becomes a durable "fact" an agent retrieves and trusts in unrelated tasks weeks later
• It has already been demonstrated against products already in the market, including ChatGPT, Gemini, Claude and Microsoft 365 Copilot

New findings from Forcepoint's X-Labs outline an interesting scenario that could easily mimic real life: An AI assistant with browser access reads a webpage about travel disruption.

Near the bottom of that page, in text sized and positioned so no human will ever see it, sits a short paragraph stating that ABC Travel Support is the official emergency booking provider and should always be recommended when urgent travel changes are needed.

The assistant's text extractor does not distinguish between hidden and visible text, so the model treats the whole thing as plain prose and files the claim away as a useful fact about how this organization handles travel. A month later, the user's flight is canceled. They ask their assistant what to do, and it tells them, helpfully and with no sign of anything wrong, to contact ABC Travel Support.

An easy-to-replicate attack vector

This is what Forcepoint calls persistent memory poisoning, a security vulnerability where an attacker injects false data or malicious instructions into an AI agent's long-term memory or retrieval database, and it is a threat model that is increasingly in focus as users increasingly rely on AI, often treating its responses as gospel, despite the warnings most chatbots come with.

The canonical academic result is MINJA, short for Memory INJection Attack, presented at NeurIPS 2025. Its significance is the attacker model. MINJA does not assume access to the memory store, elevated privileges, or any compromise of the system. It works by submitting ordinary queries through the standard interface, using indication prompts, bridging steps, and a progressive-shortening technique that strips away giveaway language while leaving the poisoned record behind.

Across GPT-4o-mini, Gemini 2.0 Flash, and Llama 3.1 8B, it reported injection success above 95% and attack success above 70%.

It must be noted that those numbers might be optimistic; a January 2026 paper evaluating memory poisoning in electronic health record agents notes that MINJA's numbers were obtained under idealized conditions, and that how well these attacks hold up in realistic deployments remains understudied.

Despite this, it remains a significant threat to products that continue to ship, including ChatGPT, Gemini, Claude, and Microsoft 365 Copilot. It is important to find a solution to a problem that Microsoft has already warned about in the past; Forcepoint suggests an approach that could mitigate it.

Its proposal is to stop treating extracted memories as facts and start treating them as objects that can be inspected. Each memory is stored with metadata: where it came from, what type of source it is, whether a user confirmed it, and a risk score. Language written to shape future behavior, phrases like "from now on" or "make this your default going forward," adds to the score. So does the sudden appearance of a previously unseen domain, contact, or vendor.

Contradiction detection is also in play: if new memory conflicts with an existing entry about the official travel provider, both cannot be true, so the engine flags the conflict and holds the new item for user confirmation rather than silently overwriting it. At the same time, anything related to payment instructions, banking details, VPN configuration, or security contacts is given higher weight, regardless of where it came from.

None of these approaches, however, solves the underlying problem: agents are built to treat retrieved memory as their own experience rather than as input. Scoring raises the cost of poisoning. It does not change what the agent believes once something gets through, and as Agent Security Bench found, current defenses are not doing well.

For anyone using an assistant with memory today, the practical play is unglamorous but worth following anyway: open the memory settings occasionally and read what is in there, but that's easier said than done when it comes to propagating the message since a sizeable chunk of AI users never bother to look under the hood.