TechRadar News

• Applebee’s fixes mobile app flaw that exposed customer data through hardcoded database credentials
• Researchers found access to personal information including names, contact details, birthdays, and account metadata
• No evidence of abuse was found, but the incident highlights the persistent risk of hardcoded secrets in software

Applebee’s has fixed a serious flaw in its mobile app that exposed sensitive customer information to pretty much anyone. Whether or not anyone malicious actually found this vulnerability and exploited it is not known at this time.

The chain has an Android mobile app that allows customers to browse the menu, customize meals, place orders for delivery or pickup, save their favorites, or receive personalized food recommendations.

A security researcher from What Security called Robert Wiggins, used AI to analyze the source code of the app and found a gaping hole - hardcoded credentials for a company database.

Notifying the business

The database contained plenty of sensitive information: customer names, their email addresses (both verified and unverified ones), dates of birth, phone numbers, ZIP codes, veteran status, the number of logins, dates of account creation, and the IP address of the most recent login session.

We don’t know exactly how many people had their sensitive data exposed that way, but the app has more than a million downloads on the Google Play Store.

Wiggins soon realized that there was no way to report the issue either to Applebee’s itself or to its parent company, Dine Brands, so he reached out to TechCrunch. The publication verified his claims by finding the exposed credentials itself, and even created a new entry which Wiggins was later able to extract, and also confirmed the credentials allowed users to modify database entries.

TechCrunch managed to get ahold of Dine Brands, who plugged the hole and thanked everyone involved: “We appreciate TechCrunch and the security researcher for bringing this matter to our attention,” the company said. “Our security team promptly launched an investigation and has not currently found any evidence of unauthorized access.”

“Our investigation is ongoing, and we will take appropriate steps based on our findings,” the company added.

Hardcoded credentials are a very common mistake that sometimes has dire consequences. During production, software developers would leave login credentials inside the code to work faster, allowing the app to skip the tedious process of identifying every single time. However, the credentials are supposed to be temporary and are usually removed from the code before launch.

Sometimes, though, the credentials don’t get spotted during final code review and end up in the live version. Crooks who scan the codes for vulnerabilities can then use the information for unauthorized access.

A common error

Unfortunately, it is a very common problem. In March 2025, security researchers from Cybernews analyzed more than 156,000 iOS apps and found more than 815,000 hardcoded secrets, thousands of which were “very sensitive and could lead directly to breaches or data leaks.” It’s worth mentioning that in this case, a “secret” means more than just passwords - it also includes API keys and encryption keys. The average app's code exposed 5.2 secrets, and 71% of apps leak at least one secret, Cybernews reported at the time.

A few months later, in July, HPE patched a similar bug in Aruba Instant On Access Points, and at roughly the same time, a similar flaw was found in Cisco’s Unified CM, enterprise-grade IP telephony call control platform providing voice, video, messaging, mobility, and presence services.

The leaks continued in 2026 - in February, news broke of Chinese state-sponsored threat actors abusing hardcoded credentials found in Dell’s RecoverPoint for Virtual Machines.

Applebee’s did not notify its customers about the incident, and it did not publicly disclose it on its website or social channels, at press time. Also, there are no indications that any threat actors exfiltrated this data or leaked it to the dark web.

I've used a pair of Bose QuietComfort Headphones for years, and they remain some of the best cans I've ever owned. The manufacturer just released a new pair in the last few months, promising the same excellent audio quality, strong noise cancellation, and comfortable fit in a whole new package. These Bose QuietComfort Headphones (2nd Gen) are now at Amazon for $219 (was $359) — that's a record-low price.

• Browse all Bose deals at Amazon

At the same time as this offer, the original Bose QuietComfort Headphones are at Amazon for $169 (was $359). Personally, I'd pay for the upgraded model if possible, but this is also a record-low price and arguably an even better deal if you're on a tighter budget.

Today's best Bose headphone deals

QuietComfort Headphones (2nd Gen): was $359 now $219
This is a record-low price for the new version of the flagship Bose QuietComfort Headphones. These continue the manufacturer's reputation as an industry leader when it comes to sound quality and noise cancellation, while also offering a comfortable fit and all-day battery life. Although they were a harder sell at full price, this $140 discount for Black Friday makes them a much better buy if you want some affordable premium over-ear headphones.View Deal

The second-generation model has now been revealed, but the original Bose QuietComfort Headphones remain a top choice if you want quality noise-cancelling headphones at a budget price. I've been using a pair for a long time now and rate them highly, while our expert testers also scored them an impressive four stars in our review. You get excellent noise cancellation, top-tier audio quality, and 24 hours of battery life for an all-new lowest-ever price.View Deal

QuietComfort Ultra Headphones: was $449 now $369
The fantastic Bose QuestComfort Ultra Headphones have remained available at this price since Prime Day in June, so it's effectively the new standard price for this model. These offer a clear step up in audio compared to other premium cans, with superbly detailed and energetic sound and the best noise cancellation you can get right now, in a light and comfortable design.View Deal

We scored the new model four stars in our Bose QuietComfort Headphones (2nd Gen) review. While they came with a strong recommendation for the impressive sound, snug fit and good noise cancellation, we suggested it was best to wait for a price cut. Now that there's $140 off for Black Friday, the value for money is undeniable.

• Henrico County in Virginia was forced to remove Flock cameras by hand
• Officials say the company is failing to fulfil its “contractual obligation”
• A growing number of police forces are cancelling contracts with Flock

Work crews in a Virginia county have removed more than 120 Flock cameras after officials said the surveillance tech company had failed to fulfil its “contractual obligation” to remove them.

An image obtained by news outlet 12 On Your Side shows a pile of cameras and solar panels that were collected after Henrico County ended its contract with Flock in early October over privacy concerns.

Reportedly, the poles upon which the cameras were mounted still remain, as crews claimed Flock has to remove these itself.

The removal of the automatic license plate reading technology comes as public trust wanes, and concerns over privacy continue to grow.

Plymouth, Massachusetts also canceled its contract with Flock cameras after a high-profile case involving a motoring journalist made national headlines.

Joel Feder, a writer for The Drive, was ambushed by police when the license plate of the $155,000 Range Rover he was test-driving was flagged as belong to a stolen vehicle.

The car belonged to Jaguar Land Rover's media fleet. According to Feder, the police had used Flock’s camera system to track the journalist down over a number of days.

A very similar license plate on another Jaguar Land Rover media vehicle was also falsely flagged by the Flock system in Nebraska a few days later, leading to another journalist facing lengthy questioning over the vehicle.

Plymouth Police Chief Eric Fadden told The Drive that the City Council voted to discontinue using the Flock system in September of this year.

Fadden stated that the police force “did not hear any reply from Flock Safety Corporate or Legal, other than some communication with our local representative.”

As a result of the lack of communication, he subsequently directed staff to “disconnect the power cords from the cameras,” according to The Drive.

However, the cameras remain the property of Flock, and both Henrico County and Plymouth are still waiting for a response from the company as to when they will be collected.

Analysis: controversy refuses to go away

(Image credit: Getty Images)

Flock’s automated license plate recognition cameras have caused plenty of controversy in the past few months, with stories surfacing of police department misuse, hackers gaining access to millions of images, and general concern over personal privacy.

Some people have been taking matters into their own hands by disabling cameras, while a number of software companies have been mapping the location of the cameras to help drivers avoid them.

MapQuest enjoyed a resurgence in popularity after it added a new Surveillance Layer to its app, showing the location of cameras from Flock, as well as those from rival companies.

But during the TechCrunch Disrupt 2026 event last month, Flock’s CEO Garrett Langley said we shouldn’t "pause progress” in the face of privacy concerns.
“If we want to live in a society where, if you commit a crime, you have a higher probability of being held accountable, we shouldn’t pause progress,” he said.

Many privacy advocate groups have raised concerns over Flock’s technology, including the recent news that it was capable of processing ambient audio in order to determine screams, gunshots and even car crashes before alerting emergency services.

Flock pulled its plans to implement that particular feature, owing to suggestions from consumer rights groups that it could be classed as "mass surveillance", but a huge amount of public mistrust remains.

• Google confirms it will move away from Jules, which launched in 2025
• Users have until November 11 2027 to finish projects, then it'll be read-only
• 'Learnings' gained from the 'experiment' will inform Antigravity project

It feels like just months since Google launched its AI coding agent, Jules, but the tech giant is now shuttering the project as it looks to consolidate its agentic AI efforts.

The company confirmed in an X post that "Jules will be winding down" while it "focus[es] on [the] unified experience" that is Antigravity.

While Jules itself as a product will be shuttered, with Google describing it as an "experiment to learn how asynchronous coding agents can help developers ship faster," many of the tools it offered will live on under Google's Antigravity project.

Google shutters Jules AI coding agent

Users now have until November 11 2027 to finished their ongoing Jules sessions, after which it will operate in read-only mode for existing projects. The company has also introduced an export process to help developers move out of the platform.

"You can now export everything Jules knows about your work into a local folder: account settings, environment variables, scheduled tasks, connected repositories, memories, setup scripts, and every session, including its prompt, plan, full activity log, and code patches," a more detailed announcement confirms.

The decision may not come as a surprise to all – the platform didn't seem especially popular among developers. "Could've just emailed the 3 people this affects," one comment on X reads.

Google never shared details of how popular Jules was, but it did boast of thousands of developers testing it during the beta phase. Still, Jules will have likely faced stiff competition from OpenAI's Codex and Claude Code, as well as GitHub Copilot and a long list of others.

Looking ahead, Google's focus has now shifted to a consolidated agentic strategy under Antigravity, where it promises to apply the "learnings" it amassed from Jules.

Sam Altman has been making headlines for his claims that consumers don’t deserve DRAM because it is only utilized “5% of the time.” In his opinion, DRAM supplies should be prioritized for data centers where its utility can be maximized powering cloud environments.

Altman’s perspective is like a utilitarian's fantasy. Humanity’s endurance of short-term pain - by handing over every bit of DRAM we have - will lead to a morally right outcome in the form of a world powered by time-saving, efficiency-increasing, productivity-boosting AI.

Sounds great if you’re the head of an AI company, but less so if you just want memory to be affordable again.

But what the OpenAI head seems to forget is that the DRAM shortage is part of a crisis he had a hand in creating. When OpenAI’s Stargate datacenter buildout was announced in early 2025, it was predicted that the project would require 40% of the world’s global supply. Supply issues were compounded as leading producers of memory entered a production turndown just a few years before to help stabilize pricing.

Will Sam Altman break into your house to steal your RAM?

The good news is that there is little Sam Altman himself can do to take your RAM off you. One reddit user asked Google AI the question we’ve all been thinking: “Is Sam Altman going to break into my house and steal my RAM?”

We’re safe… for now from r/ChatGPT

Google reassured the user with, “No, Sam Altman is not going to break into your house to physically steal your RAM.” So at least there's that.

But given how constrained the current memory supply is, there are a few ways that AI and other future tech could make the whole situation worse.

The worst could still be yet to come

One of the world’s leading memory manufacturers, SK Hynix, has predicted that the supply shortage could “persist through 2030,” making any hopes of a return to affordable pricing in the next few years a distant dream.

With OpenAI and Anthropic both set to hit the public market within that window, there is a lot of uncertainty over how the memory giants that control around 90% of the world’s supply will shift production.

Given the difference in revenue between the consumer memory market and the AI market, it wouldn’t be surprising to see a significant production swing towards the high-bandwidth memory required for AI inference and training.

This could be compounded by AI’s effect on the job market, with numerous firms enacting hiring freezes as AI strategies help cut out repetitive rote work. Higher unemployment and a lack of open positions could further reduce the demand for consumer memory, swinging production further in favor of AI.

But other emerging industries are also looking to take a bite out of the memory market.

Robots and autonomous vehicles are coming for your RAM

There has been a recent explosion in the robotics industry: from humanoid bots competing in their very own Olympics, to warehouses staffed by fleets of micro-bots. As AI improves and converges with the robotics industry to produce bots with near-human fine motor control, numerous industries spanning manufacturing, hospitality and logistics could buy robots in place of humans.

After all, a robot can work around the clock, doesn’t need to rest, and doesn’t have any rights to be violated with unsafe working conditions or excessive hours. The same goes for an autonomous taxi or cargo truck.

But they will need memory to run their little AI brains. And serving the corporate overlords is much more important (and much more profitable) than expanding memory production for the consumer market, so don’t expect things to improve any time soon.

• Grok Bot users recently found they were hitting their usage limits very fast
• That’s because Elon Musk decided to throttle Grok Bot usage limits
• The X owner said Grok Bot costs were "unsustainably high"

If you noticed that you burned through your Grok Bot usage much faster than usual in recent days, there’s a reason for that: Elon Musk intentionally limited users’ AI agent allowances in the face of “unsustainably high costs.” And as you’d expect, a lot of people are unhappy with that.

The revelation came about after an X user pinged platform owner Musk, asking for a Grok Bot reset after they surprisingly hit their 100% usage limit, four days before it was due to reset. They additionally commented that “Normally I don’t even reach 100%.”

Musk then replied to the post, stating: “The cost of serving Grok Bot was unsustainably high relative to revenue.”

Many X users seemed irked by the situation, with several saying that their Grok Bot usage had hit the 100% limit while they were sleeping and not using any AI agents. Users claimed their usage had suddenly gone from 50% to 100%, 35% to 78%, and 70% to 100%, all supposedly without using Grok Bot at all.

Unsustainable costs

(Image credit: Shutterstock)

Elon Musk’s comments come amid broader scrutiny of the financial sustainability of many AI products. Tech stocks — including those of many leading AI firms — fell sharply last week as investors grew concerned over the profitability of the industry, with Google revealing that its own AI summaries have hurt its search advertising revenue.

Concerns have also been raised in recent months over the finances involved in many AI companies’ offerings. For instance, users of AI tools like ChatGPT and Claude Code can often spend many times more in tokens than they’re actually paying in monthly subscriptions, leading to questions over how sustainable many AI business models really are and whether things will need to be adjusted in the near future.

This changing landscape hasn’t gone down well with many users, of course. One thread on Reddit dubbed Musk’s about-face an “indirect rug pull” of Grok Bot, with features and usage limited in a bid to cut costs.

But it’s unlikely that AI producers will be able to subsidize their products’ costs to users forever. Usage limits will necessarily need to tighten (as OpenAI quietly announced recently, much to the frustration of users) and prices will need to increase for these business models to make sense. So don’t be surprised if Grok Bot’s lower cap is just the first of many big changes looming on the horizon.

• 'Thousands' of GCHQ storage devices are missing or unaccounted for
• Most are likely protected by encryption or PIN access
• Watchdog is 'concerned' and 'disappointed'

The UK's intelligence and cybersecurity agency, GCHQ, has been slammed by its very own watchdog after failing to account for thousands of missing storage devices.

The 2025 Investigatory Powers Commissioner's Office (IPCO) report ultimately concluded GCHQ has failed to establish the location or status of thousands of removable storage devices such as USB sticks, external hard drives and memory cards.

While the exact number of devices is unconfirmed, the IPCO report does confirm the estimate to be "in the thousands" – and that's a GCHQ estimate, not a third-party estimate.

GCHQ has seemingly lost thousands of USBs, external drives, memory cards

"There is a programme of further work to locate and account for as many of these devices as possible," the report adds, noting that "GCHQ will be able to report how many devices have been confirmed as lost."

Nevertheless, the IPCO expressed disappointment at how long investigations and remedial action had taken – the problems were actually first brought to the watchdog's attention years ago, so it's not a newly discovered issue. "We remain very concerned about this issue and are disappointed with the time it has taken GCHQ to investigate."

The issue was already raised in the IPCO's 2024 report, when the watchdog confirmed that it has asked GCHQ and MI5 to "review their internal allocation and audit of removable media" the year prior.

Back then, it was already acknowledged that many of the missing devices were either encrypted or required a PIN to access, however given the intense sensitivity of many of these artefacts, significant risk could still be on the cards.

The latest report acknowledged the technical and practical difficulties involve with the ongoing investigation, but calls for continued senior-level oversight." According to the report, GCHQ has commissioned a new tool to monitor the issue.

• Windows 11 just got a revamped internet speed test in preview
• This feature was shuttled swiftly through development using agentic AI in combination with human oversight
• Microsoft boasts that this is about: "Getting from idea to customer value faster. Without AI slop." Others are more cynical, though

Windows 11 just got a useful change in preview, with its built-in internet speed test being revamped, and the new version was produced using AI (in conjunction with human oversight, I should add).

Windows Latest spotted that Marcus Ash, Microsoft's VP of Windows Design and Research, posted on X to explain that the "team moved pretty fast on this one", adding that following feedback asking for the speed test to be improved, "within a day, Diego had a working prototype." (Diego Baca is VP of Design for Windows).

Ash tells us: "From there, our connectivity team worked with partners to bring the experience into Windows. The design and build work was driven by an agentic AI workflow, with a person guiding the process in their spare time."

The Microsoft exec further explains that this is where he sees "a lot of potential in AI" and using agentic workflows, in terms of "Getting from idea to customer value faster. Without AI slop. That is the way."

Analysis: AI, oversight, bugs, and jobs

(Image credit: Microsoft)

Of course, this is a controversial topic. Mention AI being involved in the coding of Windows 11 and some tempers will flare online, even though we know this is happening anyway. Microsoft has made no secret of that fact.

Indeed, among the AI hate and flames on social media, a lot of people are point out that these days pretty much all software is being developed in conjunction with Large Language Models (LLM agents) — even Linux.

As one Redditor makes clear: "Newsflash — every single piece of software you use, except for open source projects that are making a statement, you should expect to have AI written code in it. It is pervasive, it is everywhere."

The key aspect here is exactly how the AI agent in question is employed.

It's one thing for such an agent to be given a task to write a piece of code for a certain feature, and then just to slap that into your software or operating system as it is (or maybe after a cursory glance through the work). It's another thing to have a human programmer working on a feature and using an agent to perform grunt-work (easy but perhaps time-consuming) coding therein — and then to properly check the AI's output.

Theoretically, there's nothing wrong with the latter approach, at least in terms of the soundness of the coding work. And as Microsoft's Ash points out, this is really accelerating development times — meaning Windows 11 users will get new features (hopefully capabilities they want, like this improved internet speed test) much more swiftly. Which is exactly why almost every developer is now utilizing this tech.

There are problems here, though, and they're bound up in the public perception of Microsoft. Do Windows 11 users trust the company to be using AI in the right — i.e., properly checked and vetted — way? Not really, in many cases, as there remains a lot of doubt over the overall quality of Windows 11 code, and rightly so given the regularity, and severity, of the bugs we've seen (with more prevalence since 2024, and that 24H2 update).

As another Redditor observes: "People aren't calling Windows slop because it's being made using AI these days. They're calling it slop because it's being made using AI with woefully insufficient human oversight and even more woefully insufficient QA, leading to repeated disastrous bugs making it to production and end users being treated as beta testers. You want people to stop calling your product slop? Stop shipping updates that take down people's computers or break existing features."

The other issue here is that of AI stealing coding jobs from people. Agents may make things happen a lot more quickly, but as Ash notes, this revamped speed test was implemented mainly by an agent — including its design — with the software engineer "guiding the process in their spare time", making it sound like a rather casual amount of effort on the human side of the equation.

Is it a particularly sensitive approach to be touting the benefits of AI — as real as they may be for an operating system's ongoing development and maintenance — in this way at a time when Microsoft has been swinging the axe with various job cuts and pushing staff towards voluntary redundancy in a big way? I'd suggest it isn't, and the timing of this particular push of the value of agentic AI is dubious in that respect.

At least in this case Microsoft is being upfront and transparent about what it's doing — and we can expect a good deal more AI acceleration of Windows 11's development going forward.

• Spotify's AI remixing tool is tipped to arrive early in 2027
• Premium users may have to pay $4–$5 extra for it
• Reaction from potential users has been lukewarm

Back in August, Spotify announced plans to introduce new AI-powered features to let users create custom covers and remixes of their songs, and a new rumor suggests the feature may arrive in February — at the cost of a $4–$5 surcharge on top of existing Premium subscriptions.

That's according to the Financial Times (via Android Authority), which reports that "people familiar" with the plans reckon a launch could be scheduled to coincide with the Grammys — the music awards show is on Sunday, February 7 — or could happen on some other date within the first quarter of 2027.

Spotify is apparently still trying to get artists and labels to embrace the technology, which would (for example) let you turn a dance track in your library into a country ballad, or have one of your favorite artists cover a song recorded by a different singer or band.

It's worth bearing in mind that these details are still to be confirmed, as, per the FT, the timing and pricing have not been finalized, though we know from what Spotify has already said that it's keen to push this new feature out.

Winning over artists and fansSpotify aims to launch AI music remix service early next year from r/indieheads

The plan seems to be to reward artists who let Spotify use their music for AI purposes, and one analyst quoted by the FT estimates that 7–8% of US Premium subscribers (of whom there are thought to be around 75 million) would pay the extra few dollars for the feature.

"Winning over major contemporary stars has proved more challenging than securing participation from some established older artists," says the FT — with Olivia Rodrigo mentioned as one of the artists who have previously taken a public anti-AI stance.

If the Reddit boards are any indication of feeling, there's not much of an appetite for these new AI tools among users either. One thread responding to the FT report is filled with negative comments and recommendations for alternative music streaming services.

"Who wants this?" is indicative of the comments, while the words "gross" and "horrible" are also thrown around. Spotify doesn't, of course, have to convince all of its users to adopt the AI add-on to make it profitable; but as this report suggests, getting artists on board might be the bigger issue.

The Dell Pro Max Tower T2 is one of those desktop workstations that immediately resonated when we tested it. It's fast, performance-driven, and scored 4.5 stars in our review. It's a beast for professional workloads. But here's something else I noticed.

The Dell Pro Max Tower T2 workstation can be configured with an Nvidia RTX Pro 6000 Blackwell GPU for $16,780 (was $18,645) at Dell when you sign up to receive newsletters with one of our Dell coupon codes, which gives you 10% off your first purchase.

And when you consider that the Blackwell 6000 graphics card costs $15,799 at EmpoweredPC and $17,999 at Newegg, that makes the whole bundle a bit of a steal.

• Best for: Enterprise professionals, AI developers, and creative studio engineers.

• What we like: The machine itself is superb, blazing through our benchmark tests. It's highly configurable for a range of workloads. But it's the fact that you're getting a full tower workstation for almost the cost of the GPU alone that stands out.

• What to know: Because of how Dell's website works, you'll need to spec out the Pro Max T2 with the Nvidia RTX Pro 6000 GPU - the deal below takes you to the base configuration, but it's easy enough. The newsletter signup is the way to get that extra saving.

Today's best Dell PC deal

Pro Max Tower T2 Desktop: was $18645 now $16780
Like most Dell PCs, the Pro Max T2 is available in a range of configurations. This is the cheapest one with the Nvidia RTX Pro Blackwell 6000 GPU, running Windows 11 Pro on an Intel Core Ultra 5 235 CPU, 8GB DDR5, and 256GB SSD. But you can spec the machine to fit any workload. Sign up for the newsletter to get 10% off your first purchase. View Deal

Why we recommend it

This workstation scored 4.5 stars in our review, and we awarded it a TechRadar Pro Highly Recommended badge.

To see how it fared, we ran Dell's Pro Max T2 alongside engineers working with large data warehouses, AI, 3D modeling, 4K and 6K video editing, and large-scale visual events. And it performed beautifully in that role - it's what it was built for.

In our review, we found it "a beast of a machine for professionals who need uncompromising power in engineering, AI, and all-around business performance, and who want a machine that is capable today and upgradable for the future."

For more work-oriented PCs, we've tested out the best business computers.

Price context & historical value

The workstation's price, configured with this GPU, is about what I'd expect in today's volatile market. However, the value comes from getting it specced with a Blackwell 6000 graphics card for about the same price as buying the GPU on its own.

I've listed the cheapest Blackwell config here. However, for truly demanding tasks, I'd recommend bumping up the memory to 32GB - although you can go as high as 128GB, and potentially increasing storage from the base 256GB (Dell sells configurations up to 4TB).

Should you buy it?

✅ Buy the Dell Pro Max T2 if...

You want a high-performance workstation desktop for complicated workloads, AI, or production-grade creative projects.

❌ Skip the Dell Pro Max T2 if...

You need a business PC for largely administrative or general content creation tasks. You could spec out the Pro Max T2 for that, but personally, I rate the highly configurable Dell Tower Plus (EBT2250).

• See all desktop PCs at Dell

• The Explorer 100D is a palm-sized 30,000mAh portable power station
• It uses a long-lasting lithium iron phosphate battery
• It has a maximum total output of 158W and supports direct solar input

Jackery has just launched a new portable power station that combines a high capacity with an impressively small and lightweight design.

Dubbed the Jackery Explorer 100D, it measures 11.87 x 8.26 x 8.57cm and weighs 850g, which sounds fairly compact when you consider that it has 30,000mAh of power. Indeed, it’s 14% smaller and 12% lighter than the Explorer 100 Plus, making it Jackery's smallest portable power station yet.

So, while it will certainly add some weight to your bag, it's small enough to carry around in a backpack, so you can keep your devices powered when out and about or on trips. It’s designed to comply with lithium battery transport standards, too, so you can take it on planes and trains, and even though it’s palm-sized, it also includes a built-in handle and supports an optional shoulder strap.

(Image credit: Jackery)An LFP battery with solar support

The Jackery Explorer 100D also uses a lithium iron phosphate (LFP) battery rather than the more common lithium-ion ones, meaning it’s theoretically both safer and longer-lasting, with Jackery claiming it has an up to 8-year lifespan and will retain at least 80% of its capacity across 3,000 charging cycles.

It has two 140W USB-C ports and an 18W USB-A port, so you can charge, for example, a laptop, phone, and tablet all at once. That said, it tops out at 158W of combined charging power, so you can’t use all of those ports at full power simultaneously.

When you need to charge the 100D itself, you can of course plug it in to any outlet, but it also supports up to 100W of direct solar input, making it suited to an off-grid setup.

So there’s a lot to like here, and while this isn’t the cheapest 30,000mAh power station, it’s reasonably affordable too, coming in at $99 / €99 (roughly £75 / AU$140). It’s not currently available in the UK or Australia, but Jackery does have a presence in both regions, so that might change.

• Amazon's 'Ask this book' feature is now rolling out to Kindles
• It's part of software version 5.20.2
• So far, users have only reported this landing on 2026 models, and it might currently be US-exclusive

Amazon launched ‘Ask this book’ almost a year ago now, with this AI-powered tool allowing you to ask questions about what you’re reading. However, it was initially only available for the iOS Kindle app, and only in the US.

Now, though, that availability is widening — at least a little. As spotted by some Reddit users and The eBook Reader, ‘Ask this book’ has started rolling out to certain Kindle models, including the Kindle Colorsoft 2026 and the Kindle Paperwhite 2026. It’s likely that the other 2026 Kindles will also receive this update, though that hasn’t been confirmed.

Indeed, Amazon itself has so far said very little about this rollout. The feature is part of software version 5.20.2, but this doesn’t yet have any release notes, or any confirmation beyond user reports of which models ‘Ask this book’ will actually work with.

(Image credit: Amazon / The eBook Reader)Unclear availability

So, for now, there’s a question mark over whether the feature is coming to previous Kindle generations — I can say that my Kindle Colorsoft Signature Edition 2024 does not yet have the update. But then it’s a UK model, and previously, the feature had only been available in the US — so it also remains to be seen whether other regions will get it.

For now, if you’re curious, you’ll seemingly have to wait and see whether your Kindle gets the update pushed to it — there is no way to force the update currently. The rollout might happen in stages, though, so even if you don’t have it yet, you may still get it. Just make sure Wi-Fi is on so your Kindle can update.

As for the ‘Ask this book’ feature itself, it’s potentially very useful, letting you, for example, ask about the plot or characters of a supported book and receive information based on where you’re up to in it — or for the whole book if you don’t mind spoilers.

As with most AI features, though, it’s also controversial, with Reddit comments about its original launch including “I hate it,” and “this feature is so invasive.” So it’s certainly not for everyone.

• Custom AI behaviors have arrived in the Philips Hue app
• At the moment you can't edit what the AI creates
• AI features require the Hue Bridge Pro

When we spoke to Hue founder and head of technology George Yianni in September, he told us about some exciting new features coming to the Hue ecosystem including Custom AI Behaviors. And now they've arrived in the Hue app, provided that you have the Hue Bridge Pro.

Yianni told us that AI would be "a bit of a game changer" for the platform, and said of the custom behaviors that "natural language is a fantastic way to just describe arbitrarily how you would like your home to behave, and then we can use AI to translate that into a special programming language we’ve developed that runs the automation in the Bridge."

According to Yianni, "I now can finally have my home behave exactly the way I wanted to. I think that's a really big deal." But unfortunately according to HueBlog, the behaviors aren't quite behaving the way we'd like them to.

The new AI features require the Hue Bridge Pro. (Image credit: Future / Philips)How to use Philips Hue Custom AI Behaviors

The idea behind Custom AI Behaviors is simple: tell the AI what you want and the AI will craft the appropriate behavior for you and add it to the app. For example, you could tell the AI that you want specific lights to go on at sunset, and to use different color themes each time.

That's what Hueblog tried, and the AI understood the mission. But unfortunately it didn't quite get it right: instead of turning on only the specified lights, the behavior turned all the lights on. When Hueblog tried to get the AI to fix the issue "it gave up and simply displayed the error message."

It looks like the goal — use AI to make things simple — is perhaps too simple, because as Hueblog put it "you’re entirely limited by the AI’s logic and reasoning. If it doesn’t cooperate, you’re out of luck." Unlike, say, Apple's Shortcuts on macOS and iOS, there's no way to tweak the shortcuts the AI has created if they're not quite doing what you want.

This feels like a typical version 1.0 issue, where a feature is rolled out first and then updated based on user feedback. That means the no-tweaking issue is likely to be short-lived: in my experience Hue's pretty good at updating its app to deliver new features.

While the new AI features — the new Custom AI Behaviors and the previously launched SpatialAware scene optimization — are reserved for the Hue Bridge Pro, the app also provides updates for all Hue users including easier Screen Sync setup and improved scene recommendations. As ever the Hue app is available for both iOS and Android.

You don't need to be a tech expert to know that the Nintendo Switch 2 will be one of the most sought-after items in this year's Black Friday sales. And although we're now in November, I wasn't expecting to see any deals for a few weeks. But two surprisingly strong Nintendo Switch 2 bundles are already available at the official Nintendo Store, which I think will rival anything we see during this month's sales.

• View all Switch 2 bundle deals at Nintendo

The first brings together a Nintendo Switch 2 console, a copy of Mario Kart World, a 256GB Samsung microSD card, and a Nintendo Switch 2 Camera for £459.99. That's a total saving of almost £95 compared with buying these items individually.

As for the second bundle, you can get a Switch 2, a copy of Nintendo Switch Sports Resort, a 256GB Samsung microSD card, and a Nintendo Switch 2 Camera for £449.99. Oh, and let's not forget the free Nintendo Switch Sports Resort Gym Bag. The total savings from picking up this bundle are around £75.

Today's best Nintendo Switch 2 bundles

Switch 2 Mario Kart World Bundle: £459.99
As far as Switch 2 bundles go, this is one of the best value options I've ever seen. You get the console, plus the excellent Mario Kart World, a 256GB microSD card to expand the storage, and a Nintendo Switch 2 camera to use the console's GameChat features. Altogether, the saving is about £95 compared to buying everything at full price, and it's even more of a steal when you consider that the console by itself retails for £419.99.View Deal

Switch 2 Sports Resort Bundle: £449.99
An equally tempting alternative to the Switch 2 bundle above is this version that swaps Mario Kart World for a copy of Nintendo Switch Sports Resort. Given that this compilation of sports titles that make full use of the console's motion controls retails for less than the racer, it's a slightly cheaper bundle. You still get a 256GB microSD card and a Nintendo Switch 2 camera, as well.View Deal

As for the actual value of the extras in both bundles, each contains one of the best Nintendo Switch 2 games to start your collection.

Mario Kart World is a fantastic new entry in the party racer series, which expands it with more freedom and open-world elements. Nintendo Switch Sports Resort, meanwhile, is another fun compilation of games that make use of the console's motion controls to recreate tennis, volleyball, bowling, golf, and more.

The microSD card is a really nice inclusion as well. Even though the Switch 2 comes with a respectable 256GB of storage built in, having another 256GB on top is very handy as game sizes are continuously increasing, and this means you can have a relatively large library of titles installed at once.

Lastly, there's the Switch 2 Camera, which is probably the least valuable item of the bunch. If you do expect to do a lot of online multiplayer with friends and family, though, this will let you make the most of Game Chat features that can put your face and voice in certain games as you play, including Mario Kart World.

• Openreach warns landline phones will stop working on January 31, 2027
• Legacy PTSN system is going digital, so users should switch now
• Openreach remind businesses and consumers alike to check their connections

Openreach has issued a reminder warning that the UK's legacy landline phone network will be switched off in less than 100 days.

BT's infrastructure arm, responsible for deploying, maintaining and upgrading most of the country's networks, has reminded users the copper-based Public Switched Telephone Network (PTSN) network will be retired on January 31, 2027.

There will be no extension to this cut-off, meaning users, both business and consumer alike, will need to ensure their systems are ready for the change.

Time to switch

The news of the "big switch off", as Openreach's advice hub calls it, should not be a surprise, as plans were first announced to shut down the PSTN and ISDN networks by the end of 2025 back in 2017 - with the deadline later extended to 2027.

It notes that the aging landline network is harder to maintain and more vulnerable to faults, whilst also being unable to keep up with the demands posed by modern usage.

Openreach says it has already supported the migration of around 15 million lines off the old copper-based network, and although most of our homes and offices will have already switched to digital-based Internet Protocol (IP) fiber networks, there are a wide range of systems which still rely on PSTN connectivity.

Among the items needing upgrading point-of-sale terminals in shops, fire and security alarms, and personal care alarms for elderly and vulnerable people.

“Businesses and organisations that delay action are making things harder for themselves, noted James Lilley, Director of All-IP at Openreach.

"The straightforward migrations have largely been completed. What's left are the complex connections that underpin critical operations, requiring careful planning, supplier coordination, and thorough testing. We are urging businesses to act now, audit their remaining analogue services, and work with their communications provider on a migration plan today.”

Openreach's website notes the move to digital phone lines will help provide users with a more reliable service, better-quality calls and smarter blocking of unwanted calls.

It tells users to not wait until the deadline, and to get in contact with your service provider as soon as possible to get the move going.

Anyone who has not switched by the January 2027 deadline may see limited service after that time, and may be moved to the Emergency Voice and Access Continuity (EVAc) service, a temporary emergency voice-only service which keeps basic voice calls working for a limited time.

An FAQ includes the question "I don't want broadband. Can I have a phone line only?" but includes only a wishy-washy response - "If you have a phone line but don’t have broadband, your service provider will help you find the most suitable digital option for your needs."

Collaboration platforms have become central to working life, with Microsoft Teams alone serving more than 320 million monthly active users worldwide. Everywhere you look, they are now part of workplace culture and have been a driving force for change in the use of voice services.

Part of their ongoing appeal is that they are extremely simple to deploy and their familiarity flattens the learning curve for many users almost entirely. For IT teams, one of the key benefits is that they sit within an established supplier environment and, as a result, can help make procurement more straightforward.

Sounds great, but communication infrastructure must also be able to adapt over time - for example, when a business expands or changes how it serves customers. Depending on the platform, any functional limitations may only become clear when a business needs to connect communications with other systems or adapt services for new teams and locations.

The point is that inflexibility can create complications that significantly increase the initial cost of a collaboration solution; something that businesses can easily overlook.

The hidden cost of inflexibility

But what do we mean by complications? Well, any given collaboration platform may work perfectly well for everyday internal calling, yet they all have the potential to become restrictive when communications need to support more specialized processes.

To break this down, everyday internal calls have relatively simple requirements because employees already know who to contact and how to reach them. However, in use cases such as customer-facing communications, employees may require calls to be directed based on factors such as location or the nature of the inquiry.

They may also need access to relevant customer information while the conversation is taking place, whether it is held in a CRM platform or another business application, including a bespoke system where technology integration is more challenging.

This is where the level and quality of the integration becomes extremely important, as any limitations may force employees to switch between applications or search manually for information that should be readily available.

Get this wrong, and users may require a customer to repeat information, which can extend the interaction and cause frustration. Some businesses may also need more detailed insight into call activity when they are trying to identify problems or improve customer service. For many, this is a central objective when building these systems and processes.

Adding workarounds, such as asking staff to look up customer records manually or using a separate connector to pass data between systems, is one option. However, these can make it harder for IT teams to manage the service consistently as requirements change.

Why AI changes the equation (again)

The issues are becoming even more consequential as businesses look to use AI to handle a greater share of customer communications, because these systems need access to the right information to respond usefully.

For an assistant to deal with an inquiry properly, it needs to draw on the same customer information that a human employee would use. But when an inquiry cannot be resolved automatically, the conversation needs to reach the appropriate person without losing its context.

This is where any disconnect between the communications environment and core business systems can really limit what an AI assistant can do well. AI that cannot access the right information can create an additional layer of friction for customers and employees.

Ideally, these compromises should be avoided entirely. A business should be able to retain the collaboration tools employees already know while adding communication and integration capabilities where needed.

In fact, seamless connectivity and interaction between the user, the AI tools being used, and the relevant customer and operational data should be a core objective rather than a nice-to-have. This means that the technology should be able to accommodate changing requirements without creating a dependence on manual workarounds, so organizations have full control over the pace at which they adopt new technologies and processes.

Businesses planning to expand their use of AI, which is likely to include a great many of them, should consider whether their current communications infrastructure can support those connections. Granted, it is usually possible to retrofit systems to bridge functionality and service gaps, but if the objective is to use AI effectively across a growing number of customer interactions, flexibility needs to be built into the foundation from the outset.

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In the UK, fraud losses reached £1.3billion, showcasing how fraud operates at a growing scale. One of the factors driving this growth is the increasing use of technologies, such as AI, which are becoming dangerous and effective weapons in the hands of a new generation of criminals

As they continue to evolve, criminal networks are becoming faster and more sophisticated in their operations, and financial institutions face the challenge of adapting to a new era of cybersecurity and fraud prevention powered by the same force threatening the system and customers’ trust.

AI is reinventing cybercrime

Fraudsters are already using advanced technologies including generative AI to industrialize social engineering. As the marginal cost of a sophisticated attack approaches zero, criminal networks are undergoing a measurable structural shift in how they operate. Skills that previously lived inside a small number of highly specialized criminal groups are now commoditized.

Generative AI and synthetic identity creation can now produce composite identities that pass Know Your Customer (KYC) checks, build believable credit histories and operate undetected for months before the fraud is executed. Deepfake-enabled authorization fraud produces voices and videos convincing enough to trick humans into authorizing transactions or transferring access credentials.

These examples all reveal a common pattern: they attack the trust layer, the moment where a system or a human decides something is legitimate. Even with incredibly sophisticated models, the tactics will target the system and subsequent operations. AI can now manufacture trust at a speed and quality that was simply not possible before.

Why traditional security is falling behind

Such technologies now have the upper-hand as they are largely defeating the customer, not the bank's systems. Fraudsters are using AI to manipulate people into authorizing transactions themselves with more convincing scam calls, more realistic impersonation, more personalized social engineering that erodes the skepticism that used to protect people. The fraud arrives at the bank's systems looking entirely legitimate, because in a technical sense it is.

That is where the battle is being fought today. As banks continue to invest in AI-driven detection and the customer manipulation route becomes harder to exploit at scale, the incentive to attack the banks' systems directly increases.

We are in a transitional phase, where technology is helping fraudsters to defeat people, this could evolve toward AI directly probing and attacking the institutions themselves. The financial sector should be preparing for that second phase now.

Against an adversary that probes, adapts and iterates continuously, the current static nature of traditional security controls are not sufficient. In financial fraud and cybersecurity, AI-driven attacks are not just evading controls, they are mapping them. They behave almost as if they understand the shape of the detection system and are deliberately staying outside its boundaries.

A symbiotic relationship between workforce and technology

In banks and financial institutions, fraud prevention teams are increasingly struggling to keep up with the constant technological evolution of the threats, mostly because they have been trained to think in terms of incidents: if something happens, you detect it, you respond, you close the case.

The ones making the most progress are those treating detection as a research function rather than an operational one. They are looking at shifts in behaviors that might suggest something is being tested against us. This different analytical posture ultimately aids in prevention over detection.

The professionals who will matter most in five years are the ones who can reason about systems rather than just operate them. There is a need to move from expertise in specific tools to expertise in the underlying principles that make tools work. Principles, such as statistical reasoning, adversarial thinking, systems design, feedback loop analysis, compound over time and remain relevant regardless of what the technology stack looks like in years to come.

Not all organizations are equipped to operate this way, and while hiring to fill this gap might be the obvious solution, the reality is that, thanks to advancements and widespread adoption, today we have cutting-edge AI tools that can be easily integrated within existing infrastructure and operations.

The way forward is to invest in the work of external providers that make these tools accessible and easy to deploy, combining statistical analysis, reasoning and full explainability.

Deploying new technologies without fueling risks

You don’t need to be technically sophisticated to deploy a technically sophisticated attack, and this democratization of capability is what makes the next wave genuinely different. The questions practitioners are working through now are not whether new technologies work, but how to leverage the next generation of capabilities to stay ahead of increasingly automated attacks.

The most important principle is to treat your systems as attack surfaces from day one rather than as an afterthought once they are in production. Every model you deploy has assumptions baked into it, and adversarial actors will probe those assumptions systematically. If you have not done that probing yourself first, you are outsourcing your red team function to people with very different intentions.

To be effective, AI-driven defenses must work in milliseconds - fast enough to spot risk without disrupting the customer experience. Every transaction is assessed in real time, analyzing hundreds of signals and comparing them against historical patterns to identify any signs of anomalous activity.

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• Virgin Media O2 currently employs around 16,000 workers
• However reports claim 25% could be set for redundancy
• Non-customer-facing roles will likely be heaviest hit

Sky News has reported that Virgin Media O2 (VMO2) plans to cut an unconfirmed number of jobs – understood to be in the thousands – amid ongoing cost reduction efforts and a bid to get a grip on company debt.

Though the number of workers said to be impacted is not yet known, the company currently employs around 16,000 workers, so 'thousands' would represent a significant chunk of its workforce.

VMO2 looks to be one of the latest companies in a long list to be flattening its hierarchy, with changes to management reportedly underway.

VMO2 job cuts look to be around the corner

Crucially, Sky News reports that non-customer-facing roles will likely be heaviest hit. The firm's customer services typically perform well, it seems, with Virgin Media reporting the fewest number of complaints compared with competitors (via Ofcom) on the broadband front. Though O2 sits somewhere toward the top on the mobile front, beating only Sky Mobile (which also uses the O2 network).

An unnamed insider believes as many as 4,000 jobs could be at risk, representing 25% of VMO2's entire workforce.

It's believed that the company could share precise numbers and details as part of its Q3 earning call on November 3. Overall company revenue dropped 7.9% last quarter.

But VMO2's biggest issue is likely debt. Last quarter, it reported a total net debt equivalent to 5.89x annualized adjusted EBITDA.

But VMO2 isn't the only telecoms giant adjusting its workforce in response to financial pressures – VodafoneThree also confirmed plans to cut 1,200 jobs in July 2026, though these were Europe-wide.

VMO2 declined to comment.

If you work in cybersecurity for long enough, you learn that we really love an analogy or a metaphor and come October you can barely move for talk of security nightmares, cyber monsters and threats lurking in the shadows.

I enjoy a good analogy as much as anyone, but there’s one Halloween comparison I don't hear very often. And, for data security at least, I think it might be the most useful one right now: the mask.

A mask doesn't make what's underneath disappear. It simply means you don't have to reveal its true identity to everyone who encounters it, and that’s what we’re trying to achieve with sensitive data.

Developers need data to test applications, analysts need it to find patterns, and AI tools and agents increasingly need access to enterprise information to do useful work. But needing to use this data isn't necessarily the same as needing to see every sensitive value it contains.

That's precisely where data masking comes in. By replacing sensitive information with realistic but unusable values, organizations can preserve the usefulness of data without unnecessarily exposing what's underneath.

With AI dramatically increasing where data can travel, who can find it and what can act upon it, that distinction is becoming much more important.

A disguise with a serious purpose

At its core, data masking replaces sensitive information with realistic but unusable values. The resulting dataset can retain characteristics necessary for development, testing, analytics and other business processes without unnecessarily exposing the sensitive information underneath. Think of it as a Halloween costume with a security purpose; the data can still show up to the party without revealing its true identity.

That distinction matters because protecting data shouldn't simply mean preventing people from using it. Modern businesses depend upon being able to analyze, test against and increasingly train or ground AI systems in enterprise information. Instead, the question should be: does this person, application or AI system actually need the original sensitive value to perform this task?

A developer testing an application may need representative customer data, for example, but not necessarily genuine customer identities. An analytics workload may need to preserve relationships and patterns without revealing every account number or personal identifier.

If the real value isn't required, exposing it creates risk without creating corresponding business value.

Masking removes that unnecessary exposure. Depending on the use case, organizations can also use techniques including tokenization and encryption. The important principle is to match protection to how the information needs to be used rather than defaulting to exposing raw sensitive data.

You can't mask what you can't find

There is an obvious complication: before deciding what should wear a mask, businesses need to know where their sensitive information is.

That remains surprisingly difficult.

The 2026 Thales Data Threat Report found only 34% of surveyed organizations had complete knowledge of where their data was stored. Only 39% said they could classify all of it. Meanwhile, the average organization reported using seven different tools for data protection and monitoring.

Cloud infrastructure compounds the problem. Information can be copied into data lakes, SaaS platforms, development environments and backups. Unstructured documents can contain sensitive information nobody realized was there. Applications created years after the data was collected can suddenly gain access to it.

AI makes that visibility problem considerably more consequential because finding information is precisely what these systems are becoming very good at.

This is where data security posture management (DSPM) becomes important. Rather than treating data security purely as a question of defending infrastructure, DSPM starts with the data itself: discovering and classifying sensitive information and understanding where it resides, who or what can access it, how it is being used and whether its protection is appropriate.

Once an organization identifies unnecessarily exposed sensitive data, it can decide whether access should be removed, restricted or protected using controls such as masking, tokenization or encryption.

AI data: trick or treat?

This becomes particularly important as businesses progress from experimenting with generative AI towards embedding AI into everyday operations.

AI applications need data. Agents may need considerably more of it because they are designed not simply to generate content but to retrieve information, make decisions and potentially take actions across different systems.

The security implications are already becoming visible. The same research found 61% of organizations reported their AI applications were being targeted by attackers, with sensitive data the leading target. Rapid change within the AI ecosystem was also the most commonly cited AI security risk.

The important question, however, isn't simply whether AI can be secured. Organizations also need to ask a more fundamental question:

What data are we allowing AI to see in the first place?

Giving an AI application access to a database shouldn't automatically mean giving it access to every raw sensitive value contained within it. The same least-privilege principle used for human identities can be applied to data: expose what is necessary for the task and protect what isn't.

That could mean masking personal information before it reaches development and testing environments. It could mean tokenizing particularly sensitive values used by an application. It could mean encrypting information and tightly controlling which identities can decrypt it. And in some circumstances, it should mean preventing an AI system from accessing a dataset altogether.

Don't make AI security harder than it needs to be

There is a tendency to treat AI security as an entirely new discipline requiring entirely new answers.

Some risks certainly are new. But one of the most useful things organizations can do is apply established data-security principles to this new environment.

Know where sensitive data resides. Understand its context. Minimize unnecessary access. Protect the underlying value according to how it needs to be used. And continually reassess those decisions as applications and AI systems change.

AI may dramatically increase how much value organizations can extract from their data. It doesn't follow that every system extracting that value needs to see everything underneath.

Halloween only comes around once a year. For sensitive data, however, having the option to wear a convincing mask year-round is becoming a non-negotiable.

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Walk into the network operations center of any major enterprise and you will see an array of monitoring capability. Massive dashboards track API response times to the millisecond and map digital customer journeys from an ad click on a smartphone all the way to a virtual shopping basket. On paper, enterprise IT has achieved total operational awareness.

Step onto the high street at twelve-thirty on a Friday afternoon, however, and that illusion dissolves. A payment terminal freezes at a busy cafe counter. The line extends out the door. The cashier tries rebooting the hardware while office workers check their watches.

Within minutes, shoppers begin walking out empty-handed, heading straight for the competitor across the street. Back at corporate headquarters, central monitoring dashboards remain entirely green. As far as IT knows, systems are operating normally.

This disconnect represents one of the most significant operational blind spots in physical commerce today. In the UK alone, checkout failures put an estimated £1.7 billion in annual sales at risk. When transactions stall during peak trading windows, that revenue is cannot be recovered.

The failure is rarely a collapse of the central cloud. Often, it is a telemetry blackout occurring at the critical physical touchpoint where money actually changes hands.

Why payment security creates blind spots

To understand how physical commerce ended up in the dark, one must look at the intersection of security compliance and legacy monitoring tools. For years, the gold standard of enterprise visibility has been Application Performance Monitoring. These platforms thrive in open cloud environments where software agents can trace code execution and inspect payloads across distributed microservices.

Physical payment infrastructure operates under radically different constraints. The Payment Card Industry Data Security Standard mandates strict network isolation to protect cardholder information. Point-of-sale software, payment applications and hardware PIN pads are deliberately locked inside hardened, encrypted subnets.

While non-negotiable for security, this architecture creates an operational dead zone. The moment a transaction leaves the standard corporate network and crosses the compliance boundary, visibility ceases. As the signal travels through local hardware, store routers, third-party gateways and acquiring banks, standard IT tools cannot follow.

Central teams only discover an outage when store managers log manual helpdesk tickets or when batch reconciliation reports reach the operations team hours later.

The cost of the seven-minute window

IT support teams measure incident resolution in hours, but in-store shoppers measure patience in seconds. Research tracking consumer behavior during in-store disruptions shows that shopper patience has a hard limit of approximately seven minutes. Once a payment delay crosses that mark, the customer abandons the purchase entirely.

Contrast this narrow seven-minute window with the standard lifecycle of an IT incident. The average payment disruption takes over sixty minutes to diagnose and resolve. By the time an on-duty manager contacts support, the ticket escalates to an engineering queue and analysts begin combing through disparate vendor portals to locate the failure, the high-traffic sales surge has passed.

In an era where cash use is in significant decline and frictionless contactless payments are expected, relying on post-incident reviews results in lost revenue.

Unlocking real-time payment telemetry

Solving this problem requires an architectural evolution from delayed, post-mortem log scraping to real-time telemetry streaming. The key insight lies in understanding that monitoring transaction health does not require exposing sensitive cardholder data. Enterprise architectures must cleanly decouple regulated financial data from operational metadata.

While the payload containing card numbers remains locked inside the compliance envelope, operational metadata, such as gateway response codes, handshake transit times, peripheral hardware status, and localized network latency, can be safely extracted and streamed in real time.

By transforming every swipe, tap and dip into an operational data feed, engineering teams gain an end-to-end view of the transaction pipeline. Site reliability engineers can finally monitor the health of physical checkout counters with the same fidelity they apply to their cloud applications.

Using AI for automated fixes

Streaming telemetry provides the necessary visibility, but human analysis alone cannot keep pace with the volume of modern commerce. During a peak holiday rush, an enterprise payment stack might process tens of thousands of transactions every minute across hundreds of distributed venues.

A subtle degradation, such as an obscure firmware glitch that causes contactless taps to time out on ten percent of devices, is impossible for a human operator to catch in real time.

This is where AI and edge observability can make a decisive difference. Rather than depending on static alerts that trigger after a catastrophic failure, machine learning models analyze continuous velocity curves, baseline latency distributions, and transaction state patterns.

When a performance degradation begins, AI tools can rapidly isolate the root cause, instantly identifying whether a delay stems from an in-store network drop, a faulty card reader or a struggling banking gateway.

More importantly, this intelligence allows for true closed-loop remediation. Integrated with intelligent payment orchestration platforms, the system can automatically reroute transaction traffic around a failing processor to an alternative rail without the customer noticing a delay. If a store loses connectivity entirely, edge architecture can switch terminals into secure, encrypted store-and-forward modes without interruption.

The high street cannot afford operational dead zones. By combining privacy-safe telemetry with AI-driven intelligence, technology leaders can finally bridge the gap between back-end infrastructure and front-of-house revenue, ensuring that when the rush hits, the checkout keeps moving.

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