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When you open a forecasting app, you simply select a location, choose an hour and read the answer.

Behind that screen, however, lies one of the hardest prediction problems in science.

The atmosphere is a three-dimensional, constantly changing system.

Before a model can predict what it will do next, it must first answer a surprisingly difficult question: what exactly is the atmosphere doing right now?

We never see the whole atmosphere

No single instrument provides a complete picture of the weather. Weather radars detect precipitation particles. Satellites observe clouds, moisture and temperatures from space. Ground stations measure conditions at individual locations. Weather balloons and aircraft provide information from different altitudes.

Each source has its own resolution, update frequency, coverage gaps and measurement errors. Building the current state of the atmosphere is therefore like reconstructing traffic across an entire city using cameras that point in different directions, refresh at different times and leave many streets completely invisible.

Meteorologists call the process of combining observations with a previous forecast “data assimilation”. It produces an estimate of the current atmospheric state, known as an analysis, from which the next forecast begins.

As ECMWF explains, forecast quality depends crucially on the accuracy of this analysis. Even an excellent model will struggle if its starting picture is incomplete, inaccurate or already out of date.

Why apps lie

One common short-term forecasting technique is optical flow. It analyses consecutive radar images, estimates how precipitation is moving and extrapolates that motion into the future. This can work well when a rain band is moving steadily. The problem is that storms are not static shapes sliding across a map. They form, intensify, weaken, split and merge. A new convective cell can appear where no rain existed 20 minutes earlier.

Imagine a storm approaching a mountain. A simple extrapolation may predict that it will continue moving at the same speed. In reality, the terrain can alter airflow, slow the system and contribute to heavier rain or hail. The challenge is therefore not only predicting where existing precipitation will move. A useful model must also predict how the weather system itself will change.

Another issue is that large-scale models are good at describing weather fronts, pressure systems and atmospheric circulation across countries and continents. But many events that affect people and businesses happen on a much smaller scale. A thunderstorm may affect one part of a city while leaving another almost dry.

A cloud front can sharply reduce output at one solar farm but miss another facility 20 kilometers away. Wind conditions can differ substantially between the ground, a rooftop and the altitude at which a drone operates. Those they can’t predict.

Weather is also highly sensitive to its initial state. Small uncertainties in temperature, humidity or wind can grow as a forecast extends further into the future. This is the real meaning of the “butterfly effect”. It does not mean that one faulty sensor automatically destroys a global forecast. It means that we can never measure the atmosphere perfectly, and uncertainty in its initial state grows over time.

That is why modern forecasting systems increasingly produce ensembles: multiple plausible forecasts rather than one supposedly certain answer. For many decisions, knowing that there is a 30% probability of a severe storm is more useful than receiving a confident prediction that later turns out to be wrong.

Not to late

Latency is one of the least discussed sources of forecast error. Consider a model that produces an excellent forecast based on atmospheric conditions measured two hours ago. If a thunderstorm formed 20 minutes ago, the forecast may already be operationally useless, regardless of how sophisticated the model is.

The World Meteorological Organization defines nowcasting as detailed local forecasting from the present up to six hours ahead. For real-world applications, however, nowcasting is more than a forecast horizon. It requires a continuous pipeline that collects new observations, checks their quality, synchronizes them in time, runs the model and delivers an updated result within minutes.

At the same time, real-time weather forecasting does not mean literally zero delay. What system does is keeps listening to the atmosphere and updates quickly enough to influence the decision being made.

And that means a lot for some industries. A consumer deciding whether to take an umbrella may tolerate an imperfect hourly forecast. Many operational systems cannot. A delivery drone needs to know whether heavy precipitation, icing or dangerous wind will cross its route before it reaches the area. An airport may need to adjust runway operations as a thunderstorm develops nearby.

A solar operator needs to anticipate a fast-moving cloud front before generation suddenly falls. Logistics and mobility platforms can reroute vehicles before flooding or severe rain disrupts a road network.

The same principle applies to outdoor events, emergency services, agriculture and energy trading. These users do not simply need “tomorrow’s weather”. They need to know what is changing, where it is changing and whether there is still time to act.

AI makes forecasting faster, but speed alone is not enough

AI weather models can generate forecasts much faster and with less computing power than many traditional numerical models. Some already outperform physics-based systems on particular variables and forecast horizons. But AI does not eliminate the observation problem.

Most global AI forecasting models still begin with an atmospheric analysis produced by traditional numerical weather prediction infrastructure. If that analysis is several hours old, fast inference cannot make the initial state current again.

AI models can also underestimate the intensity of rare events because extreme examples are underrepresented in their training data and because some training methods favor smoother, more statistically likely outcomes. Recent research has found that leading AI models can produce larger errors than physics-based systems when forecasting record-breaking heat, cold and wind events.

This is why the future is unlikely to be a simple contest between AI and physics. ECMWF already runs its operational AI forecasting system alongside its traditional physics-based model.

The strongest architecture will combine global models, high-frequency local observations, AI-based nowcasting, physical constraints and probabilistic estimates of uncertainty.

We've reviewed, rated, and ranked the best cloud backup platforms.

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

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Corsair remains one of the premier RAM-makers in our experience, and while much of the attention this year has been on soaring DDR5 prices, but DDR4 hasn't escaped the wider memory squeeze either, making upgrades much more expensive than they were last year.

Still, for a nice saving on a top memory maker, the 32GB Corsair Vengeance RGB Pro DDR4 kit is down to $260 (was $300) at Newegg.

What you're getting for your money is a well-established Corsair kit with a good combination of capacity, speed and relatively tight timings for an existing DDR4 system.

32GB Vengeance RGB Pro RAM: was $299.99 now $259.99
The kit consists of two 16GB DDR4-3200 modules running at CL16, with 16-20-20-38 timings. Intel XMP 2.0 support lets compatible systems apply the performance profile through the BIOS. Each module also has an anodized aluminum heat spreader and ten individually addressable RGB LEDs.View Deal

Why we recommend it

DDR4-3200 CL16 remains a decent specification for many existing Intel and AMD DDR4 systems. It offers reasonably tight latency, and the two-module configuration gives you a straightforward dual-channel setup.

Corsair also uses a custom PCB and screened memory ICs with stability and overclocking in mind. XMP 2.0 makes reaching the rated settings straightforward on compatible hardware so there's no need to configure timings manually.

It looks good too. The RGB implementation gives you ten individually addressable LEDs on each module, with extensive customization available through iCUE.

Price context & historical value

$259.99 is around 13% off the usual $299.99 asking price. That's not too bad in today's expensive memory market, but 32GB DDR4 kits have sold for an awful lot less in the not-so recent past.

Memory prices have risen massively this year (thanks mainly to AI), so this is about reducing what you have to pay now, rather than getting anywhere close to when DDR4 was cheap.

For more savings, we've picked out this week's best RAM deals.

Should you buy it?

✅ Buy the Corsair Vengeance RGB Pro if...

You have an existing DDR4 desktop that needs more memory and want a 32GB dual-channel kit rather than replacing the rest of your platform just to move to DDR5. It's suitable for systems where 16GB is beginning to feel restrictive when multitasking or running memory-hungry apps.

❌ Skip the Corsair Vengeance RGB Pro if...

You're building an entirely new PC and have the option of choosing a DDR5 platform. Buying DDR4 makes much more sense as an upgrade that extends the life of an existing machine than as the foundation of a new high-end system.

Part of the appeal of Vengeance RGB Pro is its lighting and design, and if you don't need that then a less elaborate 32GB DDR4 kit may make more sense and cost less.

The Catch: What to know before you buy

The biggest issue is obvious: $259.99 is still a lot of money for 32GB of DDR4. That said, you're not going to find many bargains right now, so any saving is still worth considering.

These RGB modules also have relatively tall heat spreaders, so clearance is worth checking if you use a large CPU air cooler.

• See all desktop memory at Newegg

• Microsoft has concocted another scheme to pay people to use Edge
• It's a referral link that gives you reward points for every friend invited
• A strange Bing app has also been spotted that switches some browsers to have Microsoft's search engine by default, and it's proving controversial

Microsoft is once again pushing Edge — and also Bing — in promotional efforts that may elicit more than a few groans from Windows 11 users.

We're used to this kind of thing in Windows 11, mind, and I'll come back to Bing later, as this is an apparent plan that hasn't kicked into action yet. However, the latest Edge scheme is active, and as Windows Latest reports, it's offering financial incentives to get people to use Microsoft's web browser.

This is happening on the mobile version of Edge where users are being offered a referral scheme. If you can get a friend to switch to Edge via a referral link, you'll receive 500 Microsoft Rewards points (with the ability to accumulate up to 7,500 points per month if you're feeling ambitious).

The person you invite can't be an existing Edge user (they must never have installed the mobile browser), and they will also earn 500 points for signing up. However, your invited friend must sign into Edge and use the browser for at least two days (web searching on Bing, too) within the first two weeks of being referred.

Windows Latest observes that there's no way to access this referral scheme should you be interested — you'll just have to keep using Edge mobile and wait until it's presented to you.

As well as the promotion of Bing in that offer (in terms of the requirement to use the search engine for a couple of days), there's a more brazen initiative to push Bing usage that Windows Latest also spotted.

This was highlighted in a post on X by leaker Xeno who discovered a small app called 'Microsoft Recommended Search' which has one sole and simple purpose: to change your default search engine to Bing.

When run, it offers up a simple slider to set Bing as the default engine, and if you allow this, the app switches to Microsoft's search engine across some of your installed browsers. That means Chrome and Firefox, and also apparently Brave and possibly others, via extensions which are added to these browsers. Apparently the experience is rounded off by sending the user to the Microsoft Rewards page.

Where is this app exactly? Thankfully it isn't something that's being deployed to Windows 11, and Windows Latest notes that it's just a standalone application hosted on Microsoft's official download servers (download.microsoft.com) — for the time being, anyway.

Analysis: an ominous sign?

(Image credit: Tada Images / Shutterstock)

Does this mean that the Bing switching application is something Microsoft intends to pipe out to Windows 11 at some point? That's the obvious worry, because you've got to wonder why Microsoft built this mini app in the first place. I'm guessing that this is something for use in testing, though, and not active deployment — although it could come to Windows 11 in theory (or something similar could).

I really hope not, and given that Microsoft is doing its level best to get everyone to appreciate its desktop OS this year, it's obvious that anything along these lines would be highly counterproductive to that goal.

However, there's plenty of suspicion on Reddit about Microsoft's intentions here, and chatter from those who've already switched to Linux, pointing out that this kind of thing is exactly why they migrated. As one Redditor put it: "Every day is a Microslop news day, I'm so glad I quit Windows a while ago." There are quite a few others in that thread who see this as another reason to defect to Linux, despite the fact that nothing has happened with this Bing app yet.

As for the referral scheme to promote Edge, this isn't the first time Microsoft has effectively offered lowkey bribes to get people to switch to the browser. Indeed, the likes of million-dollar prizes have been thrown around recently (and the same has been true of Bing in the past). Not that there's anything wrong with this idea in principle, except it does show that Microsoft's getting rather desperate in its efforts to recruit folks to use Edge and Bing.

The most baffling part of all with Edge is that it's a good web browser which stands on its own merits, and I think it would benefit from not being promoted so much (as that activity only makes people suspicious, or determined not to use Edge as a reaction to being constantly cajoled about it).

TP-Link's Roam 7, a compact Wi-Fi 7 travel router, proved to be an impressive essential when we tested real-world performance, connecting to public hotspots to create our own private Wi-Fi network. Currently, the TP-Link Roam 7 is down to $90 (was $130) at Amazon.

And you're not limited to repeating public Wi-Fi. The Roam 7 can use an Ethernet connection or USB phone tethering, operate as an access point or range extender, and connect wired devices to a wireless network, making it useful for business trips and working on the move beyond hotel rooms. In the UK, TP-Link's Wi-Fi 7 mobile router is now £100 (was £160) at Amazon.

Roam 7 BE3600 Wi-Fi 7 Portable Travel Router: was $129.99 now $89.98
A dual-band Wi-Fi 7 router offering theoretical speeds of up to 2,882Mbps over 5GHz and 688Mbps over 2.4GHz. Wired connectivity includes a 2.5Gbps WAN port and 1Gbps LAN. It can create a network for as many as 90 devices simultaneously.

In the UK: now £100 (was £160)View Deal

Why we recommend it

The Roam 7's biggest strength is its flexibility. Depending on what's available, it can get online through public Wi-Fi, Ethernet or USB phone tethering, rather than relying on one particular type of connection.

In his 4.5-star review, our expert Alastair said: "If you work in different locations with multiple devices, then an option like the TP-Link Roam 7 makes absolute sense. Connect the router to the internet, then connect all other devices to it; no need to reconnect each. It offers a balanced set of security features, including VPN support, making it a great solution at a lower price than most mobile routers."

He also called it a "very appealing as an option to use anywhere, be that traveling or in a location that you just want to set up a private network, such as in an office, studio or workshop where a separate network can be useful."

Price context & historical value

The Roam 7 usually sells for $129.99, and $89.98 is a reasonable $40 (31%) saving. We have seen it cheaper in the past though, but not massively. The price has dropped to a low of $80, but not for long. I'd saying paying around $10 more today still makes this a good deal, especially if you need a travel router now.

Should you buy it?

✅ Buy the TP-Link Roam 7 if...

You regularly travel with several connected devices or want an easier way to share hotel, Airbnb, airport or other public Wi-Fi. Once the router is connected, your devices can use the private network you've created rather than each having to connect to the public network individually.

Setup through TP-Link's Tether app is quick, and the full web interface provides extensive options for managing the network and connected devices.

❌ Skip the TP-Link Roam 7 if...

You want a completely self-contained mobile router. The Roam 7 doesn't have an internal battery or SIM slot, so you'll need to supply power over USB and provide an internet connection via Ethernet, public Wi-Fi, phone tethering or a USB modem.

I'd also skip it if you're specifically looking for tri-band Wi-Fi 7. Despite supporting Wi-Fi 7, the Roam 7 operates over the 2.4GHz and 5GHz bands and doesn't support 6GHz.

The Catch: What to know before you buy

Don't mistake the Roam 7 for a mobile hotspot that provides an internet connection by itself. There's no internal SIM or battery, so it needs both an external power source and an available internet connection.

OpenWrt isn't supported and while the router can make managing and sharing public Wi-Fi considerably easier, it can't improve a painfully slow hotel connection unless you have an alternative connection available for failover.

Also consider

Roam 6 Ax1500 Portable Wi-Fi 6 Travel Router Dual-Band Usb C 3.0: was $59.99 now $49.98
If you want to spend less, consider the Roam 6 which offers dual-band Wi-Fi 6 up to 1,501Mbps, support for 60 devices, dual Gigabit Ethernet, USB-C, phone tethering, multiple operating modes, OpenVPN and WireGuard support.View Deal

• Shop all routers at Amazon

• SickKids hospital in Canada hit by third‑party software vulnerability, exposing employee data
• Clinical systems and patient records unaffected; patient care continued without disruption
• Affected staff and applicants offered 24 months of free credit monitoring and identity protection

The Hospital for Sick Children, a major pediatric hospital in Canada, suffered a cyberattack that affected parts of its website, and resulted in the loss of some employee personal information.

In an announcement published on its website, the organization (also known as SickKids) said the unnamed attackers abused a “vulnerability in a third-party software application used by SickKids and other organizations.” The announcement did not say exactly which app was used in the attack, or what the vulnerability was, but stressed that clinical systems and patient information were not affected.

“Patient care has continued as usual”, it added.

This is not SickKids' first attack

After launching an investigation, SickKids learned that personal information of some former and current employees working at SickKids, Boomerang, and SickKids Foundation, as well as SickKids job applications, was exposed. It did not detail the nature of the exposed information, or how many people are affected.

Whatever that number is, those people have been offered 24 months of complimentary credit monitoring and identity protection services, for free.

“We remain committed to maintaining strong protections and continuously enhancing our cybersecurity measures to help protect the information entrusted to us,” the company concluded. Ironically, SickKids was also committed in late 2022 and early 2023, when it was struck by LockBit and had its systems locked down by the ransomware threat actor.

While, in that incident, LockBit apologized, gave the decryptor away for free, excommunicated the affiliate responsible, and did not mention any stolen data, by late 2022 double extortion attacks were standard practice, meaning data was likely exfiltrated then, as well.

At the time, LockBit was one of the most active and most dangerous ransomware operators. In early 2024, its operations were severely disrupted through Operation Cronos, but it seems the group is making a comeback. There are reports from late 2025 of LockBit 5.0 claims, including a purported attack on U.S Bank, but the news is yet to be confirmed.

Via The Record

Having tested out the Beelink EQi mini PC, we were delighted to find an Intel-powered machine that's "highly tuned" for the office. Built around Intel's new Wildcat Lake Core 3 304 processor, which features five cores, five threads and speeds of up to 4.3GHz, right now the Beelink EQi is down to $469 (was $549) at Amazon.

It comes with 16GB of LPDDR5 memory and 512GB of UFS 3.1 storage, with an 85W power supply built into the chassis. You get both 10GbE and 2.5GbE Ethernet alongside Wi-Fi 6E, making the EQi particularly good for fast NAS access, large file transfers, server duties and network-heavy home-office setups.

EQi Mini PC: was $549 now $469
The Intel Core 3 304 can reach 4.3GHz and is accompanied by integrated Intel graphics and 16GB of LPDDR5 memory. Thunderbolt 4 and HDMI provide support for three simultaneous 4K displays at 60Hz. You also get five USB ports, Bluetooth, and useful business features including Wake-on-LAN, PXE Boot and automatic power-on.View Deal

Why we recommend it

The Beelink EQi is very well equipped for a compact office or networked workspace.

In his 4.5-star rave review, our expert Alastair said: "The EQi is highly tuned to an office environment, and when connected to my 10GbE network, it felt right at home. When opening Microsoft Office, Lightroom, and browsing the internet, the speed was surprisingly sharp."

He went on to explain that the "strength of this machine comes in day-to-day office work, where it excels," declaring it to be "one of the more capable small machines I have tested this year."

For more top performers, we've selected the best mini PCs to undergo our tests.

Also consider

A6 mini PC: was $649 now $549
The A6 packs a Ryzen 7 6800H, Radeon 680M graphics, 16GB DDR5 RAM, a 1TB PCIe 4.0 SSD, USB4, 2.5GbE, Wi-Fi 6E, and support for four 4K displays.

Read our full 4.5-star reviewView Deal

M5 Ultra Mini PC: was $499.99 now $449.99
The GMKtec M5 Ultra packs a Ryzen 7 7730U, 16GB RAM, a 512GB SSD, Radeon graphics, dual 2.5GbE LAN, Wi-Fi 6E, and support for three 8K displays.

Read our 4-star reviewView Deal

Price context & historical value

At $469, the Beelink EQi is $80 below its usual $549 price at Amazon, around 15% off. That's not an enormous saving, and it has been cheaper in the past. It was as low as $330 around this time last year, but like a lot of devices the price went up considerably in 2026 due to increases in components. That said, this is still a very good deal. 10GbE networking and Thunderbolt 4 aren't features I'd normally expect to see in a sub-$500 productivity mini PC.

For more savings, we've also checked for this week's best mini PC deals.

Should you buy it?

✅ Buy the Beelink EQi if...

You want a mini PC with the combination of 10GbE and 2.5GbE networking. Triple 4K output gives you plenty of desktop space, and Thunderbolt 4 provides a versatile 40Gbps connection for docks, external storage and other high-speed peripherals.

❌ Skip the Beelink EQi if...

You primarily want the most CPU or graphics performance possible for $469. The Core 3 304 is designed to provide efficient everyday performance rather than compete with the more powerful Ryzen 7 and Core Ultra processors. The 16GB of LPDDR5 memory is also fixed, so unlike the storage, you can't expand it later.

The Catch: What to know before you buy

The supplied 512GB UFS 3.1 storage is the biggest compromise. It's functional for Windows, applications and everyday files, but it isn't the PCIe 4.0 NVMe SSD you might expect to find as the primary storage in a mini PC at this price.

Fortunately, the two M.2 PCIe 4.0 slots give you a straightforward upgrade path. The bigger limitation is the soldered 16GB LPDDR5 memory. You'll need to consider whether that will be enough RAM for your long-term needs.

• See all mini PCs at Amazon

The challenge for marketers has quickly shifted from not having enough data to make informed decisions to having so much data that it becomes nearly impossible to organize, present, and act on it in any meaningful way.

I had the opportunity to talk to Tara Robertson, Chief Marketing Officer at Bitly, to get her insight into how modern businesses can better understand what data really matters, how to collect it, and how to move away from making 'gut-feel' decisions that could be costing your business.

How is AI changing how potential customers interact with marketing content?

The clicks that do happen mean so much more.

Tara Robertson, Chief Marketing Officer at Bitly

AI has changed the early stages of the customer journey pretty significantly. People still want to make informed purchase decisions, but increasingly, they’re researching and comparing options inside AI tools and LLMs rather than exclusively clicking through a traditional search results page. That creates a much bigger “dark funnel” for marketers because more of the customer journey occurs in places we can’t easily see or measure.

At the same time, the visibility signals we’ve historically relied on are becoming less reliable. Ranking highly on a SERP, for example, doesn’t necessarily translate to the same level of traffic when AI Overviews can give someone the information they need without requiring a click.

On the other hand, since there are now fewer clicks than before AI became so intertwined in discovery, the clicks that do happen mean so much more. If someone looks at the AI summary, gets the answer they need, and still clicks, that shows real intent, not just casual browsing.

So, marketers should really strive to change their mindset from “how can I get more clicks” to “how do I make sure I know what's happening with the clicks I do get, and how do I create content good enough that a human or an AI system wants to surface it in the first place.

Your recent study found that 56% of marketers rely on gut instinct to make marketing decisions. With so much data now at marketers' fingertips, why do you think this is still the case?

This stat has stayed with me the most since we gathered the data. It’s not that marketers don’t want to be data-driven, but that the data they collect is spread across too many tools, making it difficult to make strategic decisions in real-time.

Our research revealed that teams are juggling an average of six different tools to measure performance, and more than a third are using seven or more. With this amount of data on hand, many would think that this provides clear campaign performance insights. Instead, the data is fragmented and typically focuses on only one channel. Very few are integrated with other tools, so teams are looking at pieces instead of the full picture.

So when faced with a tool and data overload, marketers lean on what has worked for them in the past, which is often going with their gut. This isn’t a bad strategy when the data fails to bring clear insights because those efforts worked for a reason, but in today’s landscape, that’s not what’s going to create success. Just because one tactic worked in a previous campaign doesn’t mean it will work again in the current one. My take is that the fix isn't "try harder to be data-driven"; it's giving people faster, cleaner signals that are easier to access so instinct becomes the backup plan instead of the default.

Your report also shows that 73% of marketers only realize a campaign is underperforming after it’s too late. What processes and tools can marketers put in place to ensure data is timely and helpful?

Locked-in budgets were the number one thing marketers told us limits their ability to act on what they're seeing.

Tara Robertson, Chief Marketing Officer at Bitly

My biggest tip is to be proactive.

Instead of looking at the data at a campaign level and analyzing it after it's complete, look at the interaction level and get granular with your insights from clicks, scans, and visits.

The overarching issue is that 86% of marketers wait until a project is complete to analyze data at the broader campaign level. By the time final reporting comes around, the budget is spent, and the window to optimize is closed. Analyzing granular interactions in the early days of a campaign gives you the agility to adjust in real time.

Other tips I usually share are to set a check-in point when campaigns are being built instead of waiting until after to see if it works. Set multiple, if needed, especially when just starting out.

Second, use AI to help with data analysis to accelerate the time-to-insight process. It’s still a good idea to always double-check your work, since AI can still make mistakes, but we found that marketers who incorporate AI into their workflows report receiving faster data insights and are more confident in their decisions, yet only 16% are actually doing this today.

Finally, build a little flexibility into your budget and your plan. Locked-in budgets were the number one thing marketers told us limits their ability to act on what they're seeing — you can have perfect visibility and still be stuck if there's no room to move.

How should small businesses use AI to better understand their data and make more informed marketing decisions?

Small businesses don't usually have a dedicated marketing team to thoroughly review, analyze, and act on the data that’s collected behind marketing activity. AI-enabled tools can help close that gap and surface insights to help direct the "what's next?" decision.

The goal isn't to get every new tool that comes to market, but to make sure the tools they already use provide clear insights quickly. Instead of exporting a spreadsheet and trying to manually figure out why last week's numbers moved, you should be able to just ask the tool.

I would start small. For example, business owners could ask AI assistants to provide weekly summaries of what changed. This way, if some of the numbers aren’t adding up, the issue can be detected sooner. When you are the one running the show, any way to save time on routine tasks is helpful. The businesses getting real value aren't the ones with the most sophisticated AI setup; they're the ones who made asking questions and getting answers often and quickly a habit.

Around 18% of marketers said they struggled to connect marketing efforts with customer retention. Beyond repeat purchases, which metrics can marketers monitor to better understand customer lifetime value?

Repeat purchases tell you a customer came back. They don't tell you why, or how close that customer might be to leaving anyway. To actually understand lifetime value, I look at three things beyond the purchase itself:

Customer research and direct feedback. NPS and CSAT are useful, but only if you're measuring them at the moments that matter, not once a year in a company-wide survey. Score it right after onboarding, right after a support ticket, right before renewal. The number tells you something moved; the open-ended verbatims tell you why. That qualitative layer is what most retention dashboards are missing.

Activation and usage depth, especially if you're product-led. Time to first value, breadth of feature adoption, whether usage is expanding or flatlining. A customer who renews but uses less of your product every month isn't retained; they're on their way out and still paying you for now. Watching usage trendlines catches that months before the churn shows up in your revenue numbers.

What happens in the white space between purchases. Are they opening your emails, engaging with your content, actually using your loyalty program? Rising support ticket volume or a drop-off in engagement is usually the earliest signal you'll get that something's wrong, well before it shows up as a lost customer.

None of this replaces repeat purchase rate as a metric. It just gives you the why behind the number, and enough runway to act on it before the customer is already gone.

Top-level metrics often give an idea of the way a campaign is going, but don’t always give the full picture. What micro-interactions and signals should people be looking for?

These analytics are what I think marketers aren’t focusing on enough. When reviewing success at the program and campaign levels, reporting gives you an overall view of how performance went, but it won’t provide the specifics.

More than half of the marketers who participated in our study said they focus on high-level strategy to inform decisions, while only 14% actually track micro-interactions such as individual clicks, scans, or page visits.

The small, seemingly inconsequential data points are often where the real story lies. Knowing which specific link or QR code is gaining the most traction, or even which channel it originated from. Whether a spike in engagement on one post actually correlates with anything downstream or is just noise. Knowing what happened before they converted could make the difference between a successful and failing campaign.

Even going as small as the time and location patterns can be helpful. Are most of the interactions coming from a QR code located in the store or one shared digitally? These small indicators reveal insights into customer intent. None of these metrics typically end up on top-line dashboards or reports, but when viewed as a whole, you can review which touchpoints are performing well and which ones aren’t.

How can businesses cut bloat when picking which marketing and analytical tools are right for them?

Fewer, better-connected tools will always beat more tools that don't talk to each other.

Tara Robertson, Chief Marketing Officer at Bitly

I suggest beginning with a thorough review of the tools you currently use and what you would be losing if you let it go. Tools are often added to the stack to solve one problem at a time, and a year later, those issues might no longer be relevant. Be mindful of what each offers and whether you truly need them, and always remember that you should be looking at your strategy BEFORE your tooling. Not the other way around.

Before adding a new tool to the stack, ask yourself what is unique about this product that nothing else you currently use provides. If features overlap, you don’t need to have both. I’d also consider whether those tools integrate well with the other programs you’re using. They are often forgotten about if they aren’t directly in your workflow. Fewer, better-connected tools will always beat more tools that don't talk to each other — that's basically the key finding of our research in one sentence.

• NordVPN found a malware campaign impersonating 65 brands
• It tricks victims into clicking on messages requesting urgent action
• If you use an Android phone, it’s worth checking your apps

Summer is still in full swing with many people out enjoying their holidays. Unfortunately, cybercriminals never stop trying to steal money by tricking people into believing they are on trustworthy websites or using legitimate apps — especially when our attention is more likely to wander.

That’s what NordVPN, the pinnacle of the best VPNs, recently investigated, issuing an alert urging caution over a widespread and sophisticated malware campaign targeting Android users through highly convincing phishing schemes.

The malware is posing as over 65 well-known brands, including Ryanair, Emirates, and Qatar Airways, as well as tax authorities, registry offices, and social security systems that lure you into downloading their apps.

The dangerous trojan tracks your messages and logins, spies on you through your camera, records your voice, and bypasses two-factor authentication before ultimately draining your bank account.

The campaign has targeted users in Southeast Asia, Latin America, and Africa.

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What the research found

NordVPN spent the last 12 months investigating the malware campaign — including its infrastructure and impersonation targets — analysing malware clusters and mapping more than 100 domains linked to the campaign.

It discovered that the campaign tricks users into installing an app that grants full access to their Android phones or computers by impersonating highly trustworthy companies — brands people are accustomed to providing their personal data without questioning it.

Victims are lured by a variety of requests via SMS, WhatsApp, or social media that look totally innocuous, like a job opening at an airline, a cheap flight, or a tax refund.

Once installed, the Trojan runs quietly in the background and stays active even if the phone is restarted, accessing your messages and call logs, capturing the screen, recording audio, and accessing the camera.

Attackers can even log into the victim's banking app and approve transactions themselves by using SMS interception to steal your money, as most banks implement two-factor authentication through one-time codes sent by text.

Marijus Briedis, chief technology officer at NordVPN, says: "One install, and the phone is no longer yours. The attacker sees your screen, reads your SMS codes, and empties your accounts from the inside."

Trusted brands are often the most spoofed brands in phishing scams, alongside other malware 'tricks' to gain trust, such as multi-platform PR campaigns promoting malware as legitimate software, or even Chrome extensions impersonating VPNs.

However, unlike many opportunistic phishing attempts, these attacks have been particularly hard to spot, featuring extremely accurate replicas of legitimate websites, meticulously copied and professionally translated.

How to stay safe

(Image credit: Shutterstock)

Briedis advises Android users to be very careful not to install apps from links received via text message. "Real airlines, banks and government bodies distribute apps through Google Play, not SMS or WhatsApp," he stresses.

As with other AI impersonating scams, users should treat any urgent request as a warning sign: whenever there is mention of a refund or an account being blocked, check the source carefully before clicking on anything or taking any action.

Checking that a website is legitimate and does not operate from domains ending in .cc, .lol, .xyz, .mom, or .pw will be a clear safety indicator.

Furthermore, do not rely on 'the padlock icon': an HTTPS connection merely indicates that the connection is encrypted, not that the site is genuine.

If you suspect that a suspicious app is already on your phone, disconnect your phone from the internet, uninstall the app, change your password from another device, and contact your bank: this will ensure you’re back in the clear.

And remember that if even the current UK Prime Minister can be a scam target, perhaps you should remain vigilant too.

• AI claims another victim: Dr. Dre admits to using it for music production
• The legendary producer doesn't detail how he uses it, though
• Certain uses could run him afoul of new streaming pushes

Another former musician has admitted to embracing artificial intelligence — Dr. Dre, formerly of N.W.A, has admitted that he uses AI when he's producing music.

In an interview with the New York Times the rapper, who's actually called Andre Romell Young, joined the likes of David Guetta, Timbaland and Grimes in admitting to using AI in their works.

"It's a new tool for creativity," Dre said, "I'm embracing it. I can't wait to see what's going to happen with this." He also repeated a common AI-user talking point, comparing it to drum machines or synthesizers and describing how much of a backlash there was against those now-common tools when they were first introduced.

In the interview, Dr. Dre didn't open up about how he actually uses AI. So it's not clear whether he uses it to artificially create entire tracks or stems, like Boy George infamously did with his We Will Dance Again, or simply to isolate elements of existing tracks, as Paul McCartney famously did to remaster a Beatles song.

Given how many simple tech tools are labelled as AI, he could simply be using it to organize files.

Dre runs afoul of the streaming war

(Image credit: Deezer / TechRadar)

Streaming services are currently waging a war against the deluge of AI music which gets dumped on their platforms daily. According to Deezer, half of its uploads are AI-generated, and the issue has pushed the major platforms to lay down the law with AI slop.

Deezer has been busy releasing non-AI features and unveiling AI removal filters, while Qobuz recently spoke to us about its own plans to tackle AI, and Tidal doesn't give royalties to AI music. Spotify has been much slower on the draw than its rivals, but even it recently unveiled an AI Persona tag to identify 'artists' who aren't real people.

It was done best by Bandcamp, which simply and easily banned music which was "generated wholly or in substantial part by AI". Now that's how you stick up for your users.

Given that he's a known entity in the music world, with a large back catalog that predates AI, it's very unlikely that Dr. Dre would fall afoul of these existing anti-AI rules. You're not going to see an AI tag on California Love, or find Straight Outta Compton has been demonetized.

But the goalposts are constantly changing, as music streaming services cotton onto just how much listeners hate AI slop, and discover new ways of identifying and quashing artificial music. While Dre's ambiguous AI use won't break streaming service rules now, that could change as these services redefine what they allow.

The current narrative around enterprise AI is rapidly shifting from the excitement of the pilot phase to the sobering reality of production. As organizations race to integrate generative AI into their workflows, they are hitting a wall that has less to do with technology capability and everything to do with how those models are deployed.

Increasingly, companies are discovering that the problem isn't AI itself, but the assumption that every task requires the most powerful model available. This has led to widespread "tokenmaxxing" - the tendency to default to the largest and most expensive models even when a smaller, cheaper alternative could complete a task.

Rather than matching the right model to the right job, many organizations assume every workflow requires frontier-level reasoning power.

This over-engineering of automation creates a structural drag on profitability. When companies treat every problem as if it requires a frontier model, infrastructure costs inevitably outpace the value of output.

The market is witnessing the consequences of this approach, with reports of major enterprises burning through entire AI budgets in months and canceling internal licenses as costs spiral.

As enterprises experience AI sticker shock, it is becoming clear that AI spending is often outpacing the tangible value it delivers.

Moving beyond the pilot trap

The core issue is that the success of isolated, controlled pilots often serves as the benchmark for current enterprise AI initiatives. In a pilot, the variables are limited, and the cost per process looks manageable. But the moment those floodgates open to enterprise-wide usage, the messy reality of production, edge cases, multistep retries, and high-volume variability, takes hold.

Because probabilistic AI generates a different cost for every run, it creates an unpredictable expense that finance departments cannot forecast. With traditional software, a fixed budget aligns with a predictable cost per task. With AI, that stability is missing. When the same process costs one dollar one day and a hundred dollars the next, it cannot be safely moved onto an operating budget.

This is why 80% of enterprises admit they miss AI cost forecasts by more than 25%, and over 95% of GenAI pilots fail to reach meaningful production. Enterprises are not currently optimizing a cost-to-value ratio; they are discovering that ratio the hard way, often after the financial damage is already done. For many leaders, the only perceived lever left is to "use less", throttling usage or restricting access.

But this response is flawed. The real shock is not the size of the bill itself, but the realization that the only lever management has left is to restrict consumption. By rationing access, the organization is effectively admitting that its AI implementation is too costly to run at scale, turning a potential competitive advantage into a defensive retreat.

Rethinking the economics of automation

Today, most organizations focus on optimizing model selection, essentially deciding which model should handle a task, but the bigger opportunity lies in optimizing the work itself. Because costs reset every time a request starts from scratch inside a large model, assuming every task requires a frontier-level LLM quickly becomes an expensive mistake.

Standard routing tools operate at the request level: they look at an incoming task and forward it to whichever model seems adequate, but that model still performs the entire task as a single, opaque generation. The only thing being optimized is which model answers, and nothing produced makes the next run any cheaper. True scalability requires going one level deeper.

This requires shifting toward an architecture that owns the business process rather than relying entirely on the underlying model. Rather than simply routing work to an endpoint, this architectural approach manages the process itself. It sits above individual models, breaking a workflow into discrete, code-backed steps to generate an auditable trace at every stage.

This single architectural choice is what separates structural optimization from surface-level cost management, offering a depth of efficiency that conventional routing tools cannot reach. This shift leads to a more efficient cost structure. Rather than relying on a single model to perform every task, computation is distributed across specialized, code-backed steps, improving resource utilization and changing how the workflow is executed.

In a high-volume loan- processing workflow, for example, this approach improves overall economics by reducing reliance on expensive model inference where it is not required. Moving toward this modular, process-driven architecture provides a sustainable path for managing the costs of high-volume operations.

Because the process is decoupled from any specific provider, organizations retain full flexibility. They can freely apply optimization strategies, rotating between frontier LLMs, open-source weights, and smaller specialized models as performance and cost needs evolve, without having to rebuild their core infrastructure.

And because every execution produces a deterministic, auditable trace of reasoning steps, tool calls, and outcomes, those records become valuable data assets, improving specialized alternatives that already know how to handle predictable tasks without defaulting to general-purpose calls.

Elevating human capacity through precision

The goal of this new approach is to transition from AI as a capped experiment to AI as the standard means of performing work. When repetitive cognitive tasks, such as verifying data or confirming disclosures, are handled by automated digital workers, the human role changes entirely. Analysts are no longer forced to spend their day manually opening files and keying in data; instead, they shift their focus to high-judgment exceptions, complex strategy, and creative problem-solving.

This is the promise of sustainable AI adoption. By converting unpredictable expenses into a known cost base and focusing on re-architecting workflows rather than just swapping models, companies can finally open the floodgates. This gives organizations a path toward sustainable and measurable ROI as adoption scales, empowering their workforce to focus on the high- value, evaluative work that technology cannot replicate.

The future of enterprise AI will not be determined by model capability alone, but by the ability to deploy integral AI systems that finally make the technology economically viable at scale. It is time to leave behind the era of unsustainable experimentation and embrace a disciplined, architectural approach to AI adoption. For organizations ready to move beyond the pilot stage, the challenge is no longer proving that AI works. It's making it economical enough to scale.

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• The 2026 World Humanoid Robot Games are happening this week
• Robots are performing better than ever across 51 events
• Stopping a sprinting robot remains a major engineering challenge

The World Humanoid Robot Games are underway in Beijing, China, and records set by flesh and blood humans are tumbling: these bots have now beaten our best efforts at the 100-meter sprint and the high jump.

As the Associated Press reports, the robot record for the 100 meters now stands at 9.39 seconds (beating Usain Bolt's 9.58 seconds), while a humanoid bot has reached 2.88 meters on the high jump (above Javier Sotomayor's 2.45 meters).

This is only the second year of the Robot Games, but the progress from 2025 is noticeable — these robots were only reaching 0.95 meters on the high jump last year, for example. One engineer told the South China Morning Post that improved networking capabilities, meaning better access to cloud AI processing, is one reason for the advances in the tech.

These humanoid robots will be put to the test across 51 different disciplines over the course of the five-day event, with sports like tennis, table tennis, and kickboxing newly added for 2026. More practical trials are also included, covering tasks across industrial production, logistics, and hospitality.

Stop right there

Unitree humanoid robot achieving a top speed of 28.3 mph failed to brake in time, veered off the track, and crashed into trackside pic.twitter.com/1JRxoELl2kAugust 20, 2026

As impressive as a lot of these robot athletes are, we're still seeing plenty of fails — such as sprinting robots smashing into safety barriers to stop. Getting these machines to slow down is actually a harder engineering challenge than you might think: we're talking about high-speed, complex movement that needs to be managed with exact precision.

There's a lot of energy that needs dissipating, a lot of rebalancing that's required, and a lot of transitioning from one state to another to be done. Researchers have managed it in simulations, but not yet in actual sprinting robots — right now the speeds and movement mechanisms are too much for the robot AIs to cope with.

It comes back to a perennial problem for robots: avoiding falling over. We take staying upright for granted, but it involves a lot of split-second calculations. When a robot is running, the problem gets exponentially more difficult.

Those watching don't seem too concerned by the abrupt stopping mechanisms. "These sports are perfectly normal for humans, but now robots can do them. I find it amazing," spectator Yang Shangzheng told the Associated Press.

• Apollo confirms July 2026 cyberattack via social engineering exposed PII in its cloud environment
• Data included names, DOB, contact info, addresses, and Social Security numbers
• Firm offers two years of identity protection; no evidence of dark web leaks yet

Apollo, one of the biggest private equity firms in the world, has confirmed it suffered a cyberattack which compromised some people’s personally identifiable information.

The company notified California’s Attorney General’s Office about the breach and shared a copy of the letter it is now sending out to affected individuals. It is impossible to discern from the letter if the victims are Apollo employees, customers, or someone else entirely, but the company did clearly explain what happened.

As per the letter, an unidentified threat actor tricked an Apollo employee into granting them access to the company’s cloud environment. The attackers used social engineering (usually phishing), which means the victim either tried logging in using a spoofed landing page, unknowingly installed an infostealer, or was convinced to grant the attackers access via remote monitoring and management software.

Was there really a hack?

The company spotted the attack a few days later, and after activating its safety protocols (notifying the police, enhancing its security protocols, and bringing in third-party forensic experts), launched an investigation which showed that the attackers accessed its cloud platform between July 6 and 10.

“During our investigation, we learned on August 12, 2026 that the information potentially impacted by this incident included your name, date of birth, contact information, home address, and your Social Security Number (SSN),” the company said. This means that financial data such as credit card or bank account information, was not compromised.

Still, cybercriminals can make use of this type of information, as is often the case in identity theft, business email compromise, and even wire fraud.

Apollo is now offering two years of free identity theft protection and monitoring for affected individuals through Cyberscout.

At press time, no threat actors claimed responsibility for the attack, and the data has not yet surfaced anywhere on the dark web.

Via TechCrunch

Oppo Reno 16 5G: two-minute review

The Oppo Reno 16 5G is a stunning mid-range phone with a lush display, fantastic camera and strong performance. If you’re looking for a phone with “summer looks” and “star vibes,” that’s exactly how Oppo is describing its new mid-range handset, which is aiming to be among the most trendy, flashy looking models on the market.

But it’s not all marketing hype — I really do think that the Oppo Reno 16 5G is a gorgeous phone. It's slim, comes in some beautiful color options, and has a striking 3D holographic design on the reverse side, making it the ideal option for those seeking an aesthetically pleasing and stylish digital companion. It's also lightweight and compact for those who prefer a smaller device.

Don’t be fooled, though, this thing isn’t just a pretty face. Like all of the best phones, the Oppo Reno 16 5G offers solid performance (thanks to its Qualcomm Snapdragon 7 Gen 4 processor), a clean and easy-to-use UI, and a 6,000mAh battery for seamless everyday use.

Another highlight for me, though, was the camera quality on the Reno 16 5G. It has a highly capable system of cameras, featuring a 50MP wide, ultra-wide, and selfie camera, as well as a 50MP telephoto lens. And for a mid-range phone, this thing produces really impressive results. The telephoto lens — which in itself isn’t always a guarantee to get at this price-point — can capture detailed, rich photos with surprisingly little compromise, and the phone is also able to capture 4K 60fps footage with its main or front camera — not bad, eh?

The display, though small, is also vibrant and punchy, and finer intricacies come through nicely when watching movies or YouTube videos in full HD. You won’t get the perfect contrast and detailing that the priciest flagships plate up, sure, but compared to rivals, the Reno 16 5G’s display is very decent indeed.

On the software side, things are pretty good — albeit slightly flawed. ColorOS, which runs on Android 16, runs like a dream the vast majority of the time, and is both well-laid out and easy to customize. Bloatware is relatively limited too, which was a relief for me, even if a handful of the usual offenders (like Temu and AliExpress) are pre-installed.

There are some small oddities, and the default AI-generated background carousel is truly awful, though it can be deactivated if you prefer (and yes, I do indeed prefer). Other AI features are more palatable, and all centralized in the Mind Pilot app, which is fine enough.

In fact, most of my gripes with the Oppo Reno 16 5G are relatively minor. I would’ve liked to have seen wireless charging onboard, and the device can get a little toasty when the processor is hard at work. But overall, this is an excellent phone.

The one thing that I consider a sticking point is the device’s price. At £649 (about $880), it’s more expensive than its recently released predecessor, and is certainly towards the top-end of that mid-range bracket. When rivals like the Nothing Phone (4a) Pro offer similar performance across the board (as well as a stunning design), the high cost could prove to be a turn off for a lot of consumers. Still, the Oppo Reno 16 5G is certainly a highly capable mid-range phone with the substance to back up its style, and I’d recommend it — especially if you spot it on sale!

(Image credit: Future)Oppo Reno 16 5G review: price and availability

• Priced at £649 (about $880)
• Released in July 2026
• Not sold directly in the US, but could conceivably be imported

The Oppo Reno 16 5G was released in July 2026, just half a year after its predecessor. In the UK, the Oppo Reno 16 5G is priced at £649 (about $880), and comes with 512GB of storage and 8GB of RAM. However, some different storage options are available in other markets, such as India. The Reno 16 5G is quite expensive for a mid-range phone, and costs about £50 more than its predecessor did at launch.

The standard Reno 16 5G is not sold in Australia, but a similar model is available called the Oppo Reno 16F 5G. Although Oppo’s phones aren’t directly sold in the US, you could potentially import it. The Reno 16 5G is available in a range of colors across different markets, but in the UK there are two options: Pop White and Purple Black.

Oppo Reno 16 5G review: specs

Dimensions

6 x 2.9 x 0.3 inches / 151.2 x 72.4 x 8.4mm

Weight

6.6oz / 188g

Screen

6.32-inch AMOLED

Resolution

2640 x 1216

Refresh rate

120Hz

Chipset

Qualcomm Snapdragon 7 Gen 4

RAM

8GB

Storage

512GB

OS

ColorOS 16.0 (based on Android 16)

Rear cameras

50MP f/1.8 wide; 50MP f/2.0 ultra-wide; 50MP f/2.8 telephoto

Front camera

50MP f/2.0

Battery

6,000mAh

Charging

80W wired, no wireless charging

(Image credit: Future)Oppo Reno 16 5G review: design

• Impressive build quality
• Attractive look with 3D pattern
• Ultimate IP69K dust and waterproof rating

It really feels like a lot of the Oppo Reno 16 5G’s appeal is in its design. Even on Oppo’s website, a substantial amount of attention is placed on its aesthetic, which is meant to radiate “summer looks” and “star vibes”. And I have to say, this is a really great-looking phone.

The Pop White variant I tested is slim, lightweight, and has an excellent standard of build — it's constructed from aerospace-grade aluminum, according to Oppo. The Reno 16 5G is a fairly compact device, with a 6.32-inch display, and it feels incredibly comfortable in-hand. It's worth noting that it's very similar form-wise to my Xiaomi 17, so moving across to the Reno 16 5G felt natural for me, but if you’re accustomed to a larger phone, like the iPhone 17 Pro Max, say, then it may feel a little undersized to you.

Something that’s unique about this device is its use of ‘Holoverse 3D technology’. On the glass back cover of the phone, you’ll see a visual of a floating planet that actually pops out at you, much like graphics on a 3D display but without having to wear the glasses. It looks fantastic, I’ve never seen this on a phone before, and it adds some nice flair to the Reno 16 5G’s aesthetic.

Right, we’ve ascertained that this is an excellent-looking phone, but does the Oppo Reno 16 5G have the practical elements to make it a true design marvel? Well, yes.

It has well-sized buttons, the camera module is pretty low-profile, and perhaps best of all, the device has an IP69K rating. IP69K is the pinnacle of the dust and waterproof rating tree, and means that the phone is fully protected against dust ingress and can survive high-pressure, high-temperature water jets from close range. It will even survive being submerged underwater, meaning it's pretty accident-proof — though I still wouldn’t recommend scrolling in the shower or anything.

• Design score: 5/5

(Image credit: Future)Oppo Reno 16 5G review: display

• 6.32-inch AMOLED display
• 120Hz refresh rate
• Solid peak brightness of 3,600 nits

The Oppo Reno 16 5G has the sort of screen you’d expect from a mid-range device. It has a 6.32-inch AMOLED display, with a 2640 x 1216 — sometimes known as Full HD+ — resolution.

But what does this mean in-use? Well, I found that the Reno 16 5G produced vibrant, punchy colors, solid contrast, and decent detailing. When watching a wildlife video on YouTube in 1080p HDR, I was struck by rich green tones, intense reds, and azure blues that helped every part of the environment pop. When tuning into The Dark Knight Rises on Netflix, black levels weren’t the best I’ve seen, but the picture was still relatively detailed, and finer elements, like lines on faces were still perfectly visible.

As you’d expect from a mid-range model, the Reno 16 5G’s display has a 120Hz refresh rate. That means that keen mobile gamers can enjoy 120fps gameplay, if software supports it that is. More generally, this meant that scrolling and typical use was incredibly smooth and fluid.

In addition, the Reno 16 5G has a commendable peak brightness of 3,600 nits. This meant that I had no issues using the phone outdoors during an incredibly bright (and sweltering) summer in the UK.

All in all, you’re getting good performance for a phone in the mid-range category. Don’t expect flagship quality in terms of detailing and resolution, but when comparing it against rivals, you’ll likely be satisfied with the Reno 16 5G’s display.

• Display score: 4/5

(Image credit: Future)Oppo Reno 16 5G review: software

• Runs ColorOS 16.0, with five years of OS and six years of security updates
• Lots of AI functionality — but some parts are more welcome than others
• Relatively light on bloatware

The software experience on the Oppo Reno 16 5G is pretty good overall, but it isn’t without its flaws.

This phone runs ColorOS 16.0 out of the box, which is running on Android 16. You’ll get five years of OS updates, and six years worth of security updates. This is pretty good for a phone in this price-range, and will likely serve most users across their time with the device.

ColorOS 16.0 provides the kind of user experience that those familiar with Android would expect. The UI is clear and looks pretty stylish, accessing apps and settings is quick and easy, and you can customize the home screen swiftly.

But let’s take a deeper look at what the Reno 16 5G has to offer. Like a lot of rivals, Oppo is going pretty hard on AI functionality. To be honest, I don’t ever use AI functions on my usual phone, but there are a few options worth highlighting.

Most functions sit in the Mind Pilot app, which lets you make use of Gemini, Perplexity, or ChatGPT, or as I like to call them, the three horsemen of the apocalypse. You can insert basic prompts, ask it to remember vocal prompts and store them as memories, or manage your transactions. Essentially, it’s able to record and collect content on-screen, and help you organize it all in one central hub. Does it work? Sure. But I’d rather handle these sorts of tasks manually

The Reno 16 5G also uses AI to generate some wallpaper options for you — at least that’s what it did for me by default. The results are often ugly and unlikable. The prompts are also left on the wallpaper, a decision I find baffling decision. A lowlight was ‘Farmer saves kittens using a broom handle’, which literally just displayed a ginger cat swimming underwater. This is the sort of AI use that leaves a sour taste, and almost no one actually wants it. Thankfully, you can disable this, but Oppo, please just get rid of this feature.

Something that I did appreciate, however, was that the Reno 16 5G was pretty light on bloatware. You’ll see a few unwanted apps — AliExpress, Temu, and Block Blast to name a few. But I wasn’t subjected to a swathe of shoddy mobile games or unwanted AI chatbots — something I got on the Xiaomi Redmi Note 15 Pro 5G — and most of the pre-installed stuff was things you’d expect, like Google and Meta apps, for instance.

And to finish on a high, I want to shout-out the Snap Key. This is a button on the left side of the phone that enables you to instantly trigger one of many functions. Options include: taking a screenshot, turning on the torch, opening the camera, and more. It's fully customizable and works like a dream, and I wish my flagship Xiaomi phone had this.

• Software score: 3.5/5

(Image credit: Future)Oppo Reno 16 5G review: cameras

• Very solid 50MP main camera
• But the telephoto lens is a real highlight
• Solid selfie camera and video performance

I used the Oppo Reno 16 5G to take photos in a wide variety of lighting conditions, both inside and outside — testing all of its cameras and video performance in the process. And after checking the final results, I have to say that the Reno 16 5G is a pretty nifty phone for photography.

The main 50MP camera is really solid, delivering the exact kind of quality I’d expect from a mid-range device. In bright outdoor conditions, the camera is at its best, producing vibrant colors and plenty of detail. I snapped some trees by my office, and the richness of the greens and gorgeous blue sky were captured fantastically well. Taking photos also feels incredibly easy, with image stabilization on board.

On a more overcast day, the main camera maintained impressive color accuracy and delivered great contrast. Some finer details could’ve looked clearer, but the final results were strong overall. The main camera also did great indoors with, or without, artificial lighting. It replicated the striking emerald green color of my strange yet beloved frog ornament, for instance.

Something that truly exceeded my expectations, though, was the Reno 16 5G’s telephoto lens. Usually, budget or mid-range phones struggle to provide clear and detailed images when zooming in too far, but the Reno 16 5G is an exception. Even when taking a photo at 7x zoom, the intricacies of a building in the distance were surprisingly clear, and details of surrounding foliage were captured with relative ease.

You also get a good quality, 50MP selfie camera, which can zoom out to easily fit you and all of your friends in frame. No more weird arm craning needed.

Video is also great on the Reno 16 5G. You can capture footage in 4K at 60fps — either with the main or selfie camera. Advanced stabilization tech and tilt correction help you to get smooth, fluid, and quality footage at all times.

There are a number of editing and processing tools that also help you get impressive results on the Reno 16 5G. These include ProXDR, which shows your photos with enhanced dynamic range, and AI Remix Collage, which includes options like an AI eraser, and Perfect Shot (which detects stuff like closed eyes).

• Camera score: 4.5/5

A church hidden among trees, taken in natural light outdoorsFutureThe same photo, but using 7x zoomFuturePhoto of trees by my officeFutureFrog ornament, taken in low-light indoorsFutureA photo of buildings taken in the eveningFutureA street in Bath, England, taken in the morningFutureOppo Reno 16 5G review: performance

• Smooth everyday performance with Qualcomm Snapdragon 7 Gen 4 processor
• Really good built-in speakers, good codec support
• 8GB of RAM enough for multi-tasking, but gets a little hot with higher-demand stuff

Like a lot of its recently released fellow mid-rangers, the Oppo Reno 16 5G makes use of the Snapdragon 7 Gen 4 chipset. This is a pretty solid option shared by other models we’ve rated highly, like the Nothing Phone (4a) Pro. But how does it perform in practice?

Well, I found the Reno 16 5G to run nicely, and experienced very few performance blips during my intensive testing. Of course, it handles the standard stuff like social media scrolling, menu navigation, and surfing the web with ease. But I also found it up-to-the-task for gaming. I hopped onto Genshin Impact — a relatively demanding, 3D game — and the Reno 16 5G handled it without a hitch. Whether I was dashing around sprawling areas, doing battle with mysterious creatures, or watching cinematics, the phone held its own with frame drops kept pretty minimal.

Even when multi-tasking between a lot of apps at once, then Reno 16 5G seemed to keep things under control. I had one occasion where there was a bit of slow-down on the home screen, but this only lasted for a very brief moment. The model I used has 8GB of RAM, which is the standard for a mid-range handset.

One thing I will say is that when the processor is put to work, the device can get pretty hot to the touch. It’s something I’ve also experienced with my Xiaomi 17, and after I left the phone to cool off for a few minutes, it was fine to use again, but this is an issue that some more powerful phones may not pose.

An area of the phone’s performance that impressed me was its audio capabilities. I review a lot of audio gear here at TechRadar, so it's fair to say that I have high standards. But I found this to be a great lil’ device sound-wise, right across the board. The built-in speakers provide surprisingly clean, articulate sound, and although there’s little in the way of bass, I’d never expect impactful low-end from phone speakers.

There’s also excellent Bluetooth codec support, with both LDAC and aptx (thanks to the Snapdragon chip). That means you can enjoy higher-res wireless streaming on the go, if you have compatible headphones or speakers, like the Sony WH-1000XM6 or Bose SoundLink Max.

• Performance score: 4/5

(Image credit: Future)Oppo Reno 16 5G review: battery life

• 6,000mAh battery is good for a day’s use
• Supports 80W wired charging
• No wireless charging

The Oppo Reno 16 5G has a 6,000mAh battery, and while I’ve tested phones with more than this, that’s still quite large. I found it to be good for a day’s worth of mixed usage — gaming, watching videos, scrolling the web, and general use. Your mileage will vary depending on the applications you use and how intensive they are, but Oppo says you get over 60 hours worth of calling time with the Reno 16 5G. Not bad, is it?

When your phone does run dry, it doesn’t take all too long to bring it back to life, either. It supports very fast 80W wired charging, and I found it could charge to full in around an hour.

Something that I found slightly disappointing, though, is that the Reno 16 5G does not support wireless charging. At this price, it would’ve been a nice feature to have, especially as my wireless charger stand is a staple of my office desk setup.

It’s also worth noting you get the standard battery preservation options, battery saving settings, and a hub where you can view battery use by app.

• Battery life score: 4/5

(Image credit: Future)Should I buy the Oppo Reno 16 5G?

Attribute

Notes

Score

Design

Gorgeous looks, great standard of build, top-tier IP69K dust and waterproofing.

5/5

Display

Solid display at this price-point with 120Hz refresh rate.

4/5

Software

Neat OS with easy-to-use UI, relatively light on bloat, but some small quirks and odd AI functionality.

3.5/5

Cameras

Great quality for a mid-range phone with an especially admirable telephoto lens.

4.5/5

Performance

Steady performance across the board with impressive audio.

4/5

Battery life

Large battery for all-day use, speedy charging, but wired only.

4/5

Buy it if…

You want a super-stylish handset
If there’s one thing Oppo wants you to know about the Reno 16 5G, it's how stylish and trendy it looks. And I’d have to agree, whether it’s the pretty color options, slim build, or 3D holographic design, this phone is very easy on the eye.

You want great camera quality
I was really impressed by the Oppo Reno 16 5G’s camera quality. Its telephoto lens is the real highlight, and even at 7x zoom, my photos had great levels of detail and color accuracy.

Don’t buy it if…

You need wireless charging
Given that the Reno 16 5G is on the pricer side for a mid-ranger, I was hoping that it would have wireless charging. If this is a deal-breaker for you, then I’d recommend the Google Pixel 10, which is often on sale now that its successor has arrived.

You’re on a budget
The Reno 16 5G is pretty pricey, and it faces some red-hot competition from more affordable mid-rangers like the Nothing Phone (4a) Pro, for instance, which you can read about down below. If you’re on a budget, then that might be the better pick.

Oppo Reno 16 5G review: also consider

Oppo Reno 16 5G

Nothing Phone (4a) Pro

iPhone 17

Price

£649 (about $880)

$499 / £499

$799 / £799

Dimensions

6 x 2.9 x 0.3 inches / 151.2 x 72.4 x 8.4mm

6.4 x 3 x 0.3 inches / 163.7 x 76.6 x 8mm

5.9 x 2.8 x 0.3 inches / 149.6 × 71.5 × 8mm

Weight

6.6oz / 188g

7.41oz / 210g

6.2oz / 177g

Cameras

50MP wide, 50MP ultra-wide, 50MP telephoto

50MP wide, 8MP ultra-wide, 50MP periscope

48MP wide, 48MP ultra-wide

Battery

6,000mAh

5,080mAh

3,692mAh

Nothing Phone (4a) Pro
The Nothing Phone (4a) Pro is easily one of our favorite mid-rangers on the market. It’s oozing in style, has a gorgeous 6.8-inch display, offers solid performance, and has a clean software experience too. It's a bit cheaper than the Reno 16 5G, although Oppo’s phone arguably boasts better cameras. Read our full Nothing Phone (4a) Pro review.

iPhone 17
It’s a slight step-up in price from the Oppo Reno 16 5G, but the iPhone 17 is a great phone worth considering if you want a mixture of great design, performance, and a seamless user experience. Though its battery life is nothing special, and it lacks a telephoto lens, it still offers a stylish and simple user experience backed up by the powerful A19 chip. Read our full iPhone 17 review.

How I tested the Oppo Reno 16 5G

• Tested over the course of a week
• Used for gaming, photography, and general productivity
• Made full use of various features and camera settings

I spent a week testing the Oppo Reno 16 5G, during which time I tested out its various features, put it through its paces with mobile games, and snapped a whole lot of photos.

When taking photos, I stuck mainly to the 16:9 aspect ratio, and tried snapping buildings, foliage, household objects and more in a range of lighting conditions. These included: artificial light, low-light indoors, natural light outdoors and indoors, and nighttime outdoors. I also made sure to assess the phone’s battery life across a full day of mixed usage, compare its software to that of my Xiaomi and Nothing phones, and test its display side by side with some rivals.

More generally, I’ve spent years testing gadgets here at TechRadar, where I serve as a Senior Reviews Writer. I’ve reviewed a number of phones including the budget-friendly Xiaomi Redmi Note 15 Pro 5G and the flashy Nothing Phone (4a).

• Read more about how we test
• First reviewed: August 2026

• Android Pulse has appeared on the Google Play Store
• It's available as an update for some users, showing that it's already on their phones
• The description suggests this runs in the background to check for misbehaving apps

Android Pulse is an app that you probably don’t know you have — but if you’ve got an Android phone then there’s a chance it’s already running in the background, and there’s an easy way to find out.

As spotted by 9to5Google, just such an app has appeared on the Google Play Store, and more tellingly, you might find it in your list of available Google Play Store app updates — meaning it’s already on your phone, even though you won’t have knowingly downloaded it.

This isn’t actually a completely new app, with versions of it dating back to March appearing on APK Mirror, but it has seemingly only now got itself a Google Play listing — and with the listing mentioning over ten million downloads, a lot of people must already have it.

Keeping your Android's pulse healthy

(Image credit: Google / 9to5Google)

So what is this mystery app? Well, the listing says “this app facilitates rule distribution for anomaly detection in critical system resource consumption by the Android operating system and installed applications.” That’s a bit unclear, but 9to5Google’s interpretation — and we’re inclined to agree — is that this runs in the background, performing software diagnostics on the operating system and your installed apps.

It’s likely — based on the “anomaly detection” part of the description — that it’s looking for any apps or services that are misbehaving, by for example using more battery or CPU than they should. Though whether it then does anything about them or just alerts Google to it is less clear.

Either way though, the ultimate goal is presumably to keep Android running smoothly, so that’s no bad thing.

But this isn’t an app you can directly interact with or run scans from — if it’s on your phone, you just have to hope and assume it’s doing some good, and not simply wasting resources.

• The first teaser trailer for The Pitt season 3 has been released by HBO Max
• It picks up on Dr. Robby's first day back after his four-month sabbatical
• A release window of January 2027 has been confirmed for the season

The Pitt season 3 first trailer has dropped, and I'm incredibly surprised that we're getting a first look this early. We can expect new episodes to arrive at some point in January 2027 — meaning we've got a five month wait until we find out what's really going on.

But HBO Max is a streaming service that likes to keep us on our toes, simultaneously giving away everything and nothing in the first season 3 teaser trailer (which you can catch up with below).

We already know that season 3 is set in early November, corresponding with the three- or four-month sabbatical Dr. Robby (Noah Wyle) is due to take at the end of season 2.

While creators said in a statement that season 3 is “just before the holidays, ushering in a whole new set of emergencies and confrontations and complications,” Wyle added at PaleyFest, "The thesis of season 1 is the doctor is the patient. Season 2, doctors don’t make very good patients. Season 3, doctors benefit from being patients.”

He also told Deadline, "Well, I think we’ll find out what that rock bottom [for Dr. Robby] looks like next year.”

Is this the impression I get from watching the first few glimpses of footage? No. But instead, I think that another medic is finally about to have their moment in the spotlight.

Opinion: The Pitt season 3 teaser trailer hints that Dr. Javadi will finally step up

With such a truly ensemble cast, there were never going to be any losers in The Pitt season 3... but if I were you I'd keep your eye on Dr. Javadi (Shabana Azeez) in new episodes.

Meek, mild-mannered and constantly second-guessing herself, as the 'baby' of the ER team Javadi has striven to prove herself both to her colleagues and to her disapproving parents, who work in general surgery and endocrinology upstairs.

But in the above clip, she's finally stepping up to take charge... and it suits her. In a split-second clip, we see her working with two other medics to try and resuscitate a patient, asking for help without feeling self-conscious in the process.

It's rare that The Pitt produces positive stories of growth for our team, but as the ER storm whips back up, I've got a good feeling about Javadi.

From what Dr. Robby tells us, though, nothing else is going to be straightforward. How the screaming casualties rolling into the day shift are going to differentiate from seasons 1 and 2 is yet to be established, but put it this way — nobody's looking well-rested.

• Amazon has increased the prices for its best-selling devices, including popular Kindle models
• This is due to the increasing memory and storage component costs
• Users online have found ways to score Kindles for cheaper

Amazon is the latest tech giant to increase prices across its lineup of smart home devices — and this also includes popular Kindle models.

In addition to devices such as the newer Echo Dot Max, Echo Show 21, and some Fire TV sticks, Amazon’s basic Kindle and mid-range Kindle Paperwhite e-readers have shot up by up to 60%. The only Kindle model that hasn’t seen a price hike is the premium Kindle Scribe.

Amazon’s price increases quietly landed over the weekend without an official statement from the retailer, but luckily the online outlet Fortune spotted the new price tags when conducting a review — who also shared that Ring doorbells are the only Amazon devices that haven’t been hit with a price adjustment.

The outlet also provided a full breakdown of the devices affected by the price hike, which you can view below:

Device

Old price

New price

Echo Dot (5th Gen)

$49.99

$79.99

Echo Spot

$79.99

$109.99

Echo Show 21

$399.99

$499.99

Echo Dot Max

$99.99

$119.99

Echo Show 15

$299.99

$349.99

Echo Show 11

$219.99

$249.99

Echo Show 8

$179.99

$199.99

Fire TV Stick 4K Max

$59.99

$84.99

Fire TV Stick HD

$34.99

$39.99

Kindle (16GB)

$109.99

$149.99

Kindle Paperwhite (16GB)

$159.99

$199.99

eero 7 (3-pack)

$349.99

$399.99

eero Pro 7 (3-pack)

$699.99

$799.99

Though Amazon didn’t issue any form of official explanation for this, a spokesperson released a statement to Fortune to offer more insight, sharing that consumer tech is “facing significant increases in memory and storage component costs. After absorbing these increases for as long as we could, we recently adjusted pricing across our product lines”.

2026 really has been the year of the price hike for the tech world, and it’s not just Amazon that’s been affected. Apple raised its Mac, iPad, and HomePod prices in June, while services like Spotify hiked subscription plans earlier this year and the same goes for YouTube Premium.

Price hikes are regular as clockwork at this rate, however some users don’t seem to mind as much if the product in question is of value and has a lot to offer. But take devices such as the standard Echo Dot and basic Kindle for example, two entry-level models in their respective areas, a $30-$40 increase seems a little unfair.

Though the Echo Dot is a basic speaker that gets the job done, its audio output and smart features aren’t worth over $50 in my opinion. The same goes for the basic Kindle, an e-reader with basic functions, which you also have to pay more for if you want an ad-free experience.

As you can imagine, Amazon’s latest price increase hasn’t settled well with Kindle users, especially since Amazon’s e-readers are one of the company’s best sellers. Redditors have been posting non-stop about this, one user replied to a post saying ‘I hope nobody buys these and prices go down’ — however, bookworms are sharing ways to score these devices for cheaper in the wake of the price hike.

Comment from r/ereader

Now, users are reverting to third-party discount sites to get their hands on Kindle e-readers for a fraction of the new prices. Many users replied under the same Reddit post recommending Unclaimed Baggage, a site that sells on devices found in lost luggage from airlines.

For example, Amazon’s premium Kindle Scribe Colorsoft e-reader is the best part of $680, while Unclaimed Baggage has offers for half of that. This isn’t the only third-party retailer however, Redditors have also recommended Woot, an online deals site run by Amazon where you can access hundreds of deals across electronics.

One of the better sides to these third-party options is that they’re not limited to Kindles, they also have a number of listings for other devices in Amazon’s latest price increase. That said, Redditors aren’t ruling out Facebook Marketplace for finding offers on gadgets — you never know what the person around the corner from you wants to get rid of.

• HoverAir launched its new Versa drone on Indiegogo, saying it had FCC approval
• FCC has since stated that certification was granted 'erroneously'
• The Versa is the world's first 2-in-1 pocket gimbal camera and drone

HoverAir launched the Versa drone on Indiegogo last week, and a few words in the promotional material suggested that the world's first 2-in-1 pocket gimbal camera and drone had a distinct advantage over DJI: "FCC (Federal Communications Commission) certification."

The claim of FFC approval implied that the Versa would be permitted to be sold in the US, a market which new DJI drones have been fully locked out of since 2025. World-first features, plus US availability — those were two big leg-ups for the Versa.

However, HoverAir's hopes of having that key advantage in terms of market access have quickly been dashed. The FCC contacted TechRadar to tell us that "certification for this device was granted erroneously and has been set aside by the FCC and removed from our public database".

Furthermore, it said the "FCC is considering further action against HoverAir for apparently willfully violating the FCC’s Covered List rules."

It's quite the turnaround for HoverAir. The company must have been licking its lips at the prospect of its innovative innovative 4K drone and pocket gimbal camera having unchallenged access to the US market. Turns out, it's in the same position as DJI after all.

Here's the FCC statement in full:

“Importing, marketing, or selling this [HoverAir Versa] device in the United States is a violation of U.S. law, and the FCC has directed HoverAir to cease any such activity immediately.

"The device in question is on the FCC’s Covered List: the Versa camera alone is a prohibited UAS critical component produced in a foreign country and, when the Flight Kit is included, the device falls under the ban on UAS produced in a foreign country.

"The certification for this device was granted erroneously and has been set aside by the FCC and removed from our public database. The FCC is considering further action against HoverAir for apparently willfully violating the FCC’s Covered List rules.

"Finally, the FCC is sending guidance to all Telecommunications Certification Bodies to strengthen their due diligence of applications to ensure they comply with their legal obligation not to certify equipment on the FCC’s Covered List."

HoverAirHoverAirHoverAirHoverAirMore bad news for drone fans in the US

Following the self-flying X1 and the waterproof Aqua, HoverAir notched up a trio of world-first drones with the Versa, a 2-in-1 pocket gimbal camera and drone.

According to its Indiegogo page, the Versa is tipped for a worldwide launch and for October 2026 delivery to backers. However, despite US pricing (starting at $499) remaining on the crowdfunding page, it looks like the Versa won't be taking to the skies in the US any time soon.

That's a shame for drone fans in the US. Versa's modular design means that its wings (guard-protected propellors) can be removed in a simple motion, switching the device from a 230g self-flying 4K camera to a 163g pocket gimbal camera.

Its key features include 4K video up to 60fps, 4K HDR video up to 30fps with 10-bit color depth, 12MP photos (there's no mention of RAW format) and a 1/1.3-inch sensor.

Controller-free aerial selfies are a breeze, thanks to palm take-off and landing, AI subject tracking, auto framing, plus voice and gesture commands.

Furthermore, the Versa is compatible with HoverAir's Beacon device, which debuted with the Aqua, meaning it can pair with a phone for clear audio. It's said to reach speeds up to 36km/h with a Level 5 wind resistance, and have 14-minute flight times, though realistically battery life will be less than that.

As a gimbal camera, the Versa features a rotating OLED haptic screen, which measures 1.64 inches on the diagonal and hits 800 nits of brightness.

We haven't tested the Versa yet, but we'll share our in-depth review soon. The innovative drone will make its public debut at the IFA consumer electronics show, which takes place in Berlin, Germany, from September 4-8, and you can learn more about it in the YouTube video below.

The first salvo of the war against AI slop on LinkedIn looks to be going the right way for those of us who can actually use our imaginations, the company has said.

LinkedIn Chief Product Officer Hari Srinivasan has revealed over a million people have clicked the ‘seems like AI slop’ report option in the two weeks since its launch - and I've definitely clicked it a few times.

Srinivasan says that these reports, along with changes to LinkedIn's detection systems, have cut views of content classified as AI slop by 40% - although sadly my feed is still pretty full of it.

"Low-quality content" crackdown

In his post, Srinivasan noted the feedback was, "helping us better understand how our community experiences low-quality content" across LinkedIn, suggesting stricter clampdowns to come.

The first stage of this is launching now, so if one of your posts receives enough community feedback (aka is reported as AI slop), you may see a message in your Post Analytics, "to help you understand how your content is being received".

"We approached this assuming good intent; I know I'm increasingly conscious on how to not sound like AI & the goal is to provide helpful feedback," Srinivasan says.

"Importantly, no single piece of feedback determines how content is distributed," he added. "We look at many signals together, and we've built safeguards to help prevent individual feedback from being used to unfairly target other members."

"Despite the progress, we know we have more to do to ensure LinkedIn remains a place where you can find real people & real perspectives... this all remains very top of mind," Srinivasan concluded, suggesting further actions may come soon.

(Image credit: LinkedIn)

The company announced it was cracking down on AI slop in early August 2026, when Srinivasan declared it was, "a top priority for all of us. We really care about this...people come to LinkedIn to connect with real people and share their real perspectives, ideas and expertise."

To report a post, users just need to click on the three dots at the top-right of any LinkedIn post, and among the usual options to save, share or embed, you'll see a new option - "Seems like AI slop".

Srinivasan added that Microsoft-owned LinkedIn will, "continue to improve and invest in our automation defences..on comments alone, everyday we are now catching hundreds of thousands of automated comment attempts, and have blocked billions of other automation attempts (posting at scale, slop) in the last couple months alone."

At 2 a.m., an automated remediation agent detects a problem on the network, traces it to a misconfigured policy, validates through the harness that the proposed fix operates within the given policy boundaries and fixes it. The network stabilizes. Nobody’s notified.

In the morning, a human reviews the agent's daily insights: a summary of all the changes executed, with links to the logs, audit trails, reasoning and root cause behind them, confirms everything has been properly resolved and moves on. That is what Human-on-the-Loop looks like.

At another organization, at 4 a.m., a DIY-built, vibe-coded remediation agent detects a problem on the network, traces it to a misconfigured policy, and fixes it. The network stabilizes. Nobody’s notified. In the morning, a human reviews the logs, assumes the issue has been resolved, and moves on.

Where's the difference?

The difference is that, in the DIY scenario, the logs only tell part of the story. They don't show that the agent made three other changes to get there, which were broader than intended, and the decisions behind those changes weren’t flagged because nothing in its constraints required them to be.

This is what the move toward Human-on-the-Loop can look like without the right controls in place. No dramatic handover. Just a series of small, reasonable delegations that gradually build into something nobody explicitly signed off on.

And it's happening faster than most leaders realize. According to recent research, 57% of IT leaders expect to remove humans from the loop within a year or less, and 79% already treat AI agents as "users" who require their own identity management and governance controls.

The shift to agentic AI is happening faster than most organizations are prepared for, both in terms of governance and the ability to evaluate autonomous systems.

The illusion of "I approve"

The answer to autonomous AI has long been quite simple: keep a human in the loop. Somebody who reviews the output, hits approve, preserving accountability. Except it isn't, not really. Reviewing every action doesn't automatically create accountability, and it also prevents organizations from realizing the full benefits of autonomy.

Rather than reviewing every individual action, humans should be focused on evaluating outcomes, ensuring the system operated within its intended boundaries, and providing feedback that improves its performance over time.

Approval can become a ritual without meaning. As systems prove reliable and the number of alerts multiply, humans sometimes start to treat intervention as something that isn’t often needed.

The approval can become more of a click than a considered choice. And when something goes wrong (for example, a misconfigured policy, an automated remediation that turns into an outage), the question of who was responsible is difficult to answer.

It also reinforces a broader shift: one of the most important human capabilities becomes critical thinking and the validation of hypotheses, rather than the execution of tasks.

And something else is happening. Humans are transitioning from doing to reading before approving – a fundamental change in the day-to-day work of most of us.

Also, attribution isn't the same as provenance. A log that records what an agent did tells you almost nothing about why, or what shaped that decision. When things go wrong, those are the things you need to know.

Non-human identities and the new network population

When AI agents act on your network, querying systems or making configuration changes or routing traffic, they are effectively users. They need credentials, policies, guardrails, explainability, and audit trails just like human operators.

Most organizations haven't caught up with this. Identity frameworks were built for people, and applying AI agents to them as a kind of afterthought creates exactly the sort of shadow access that security teams spend their lives trying to eliminate.

The near-80% of leaders who already treat agents as governed identities are ahead of the curve. The rest are collecting risk they can't quantify, until it crystallizes into an incident.

To get this right you have to treat each agent as a principal with bounded permissions, time-limited access and a clear revocation path, along with a complete record; not just of what it did, but of what it was allowed to do and why.

Autonomy isn't given, it's earned

Network and security teams already know how to do this. Every enterprise has access control frameworks that govern what humans can reach and when. A junior engineer doesn't walk in on their first day with total production access. They gradually earn it, and this same logic needs to apply to AI agents.

We're not quite there yet. Too often, autonomy is treated as all-or-nothing. That isn’t the right model. Trust when it comes to humans doesn’t work like that, and it shouldn’t with AI either. Start agents in suggestion mode and let them prove themselves within clearly defined limits before expanding what they can do. And make sure every decision leaves a trail that explains not just what happened but the reasoning behind it.

As the use of autonomous AI grows, organizations will need to balance human oversight with systemic governance. People remain responsible for reviewing not only the outcomes AI produces, but, where necessary, the actions it takes and the reasoning behind them.

However, as the volume and complexity of autonomous decisions increase, this oversight should be complemented by infrastructure that embeds identity, policy enforcement, observability and accountability. Together, these controls help ensure AI actions remain transparent, traceable and aligned with organizational intent.

Building multi-agent systems that hold up under pressure

The more capable these systems become, the more organizations will move toward multi-agent architectures. This is where specialized agents each own a piece of a workflow and hand off context as they go. That's where things get complicated.

A single agent misbehaving is traceable. A chain of agents, each acting on the outputs of the last, is much harder to untangle when something goes wrong unless the right architecture and governance are in place. You need to know what each agent knew, not just what it did.

Do the boring part

Two organisations deploy the same AI-powered networking agent. One of them has done the unglamorous work: setting up tight permissions, proper identity controls and audit trails that actually answer questions. The other one hasn't.

You won't know the difference until something breaks.

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There’s a pattern starting to emerge with AI.

At first glance, everything looks like progress. AI is being adopted quickly, embedded into products, talked about in boardrooms, and pushed into real-world use faster than anything we’ve seen before. But as businesses become more accustomed to AI and increasingly find new ways to use it, there is a greater problem brewing that has the potential to be detrimental to a company’s cybersecurity posture.

Organizations are moving quickly to use AI, but far fewer are making the right decisions about how it’s actually being delivered and secured. And the gap between those two things is widening, with security teams left scrambling to fix vulnerabilities like whack-a-mole.

The speed is understandable. AI hasn’t followed the usual enterprise lifecycle. It hasn’t patiently moved from concept to pilot to controlled rollout. In many cases, it’s gone straight from experimentation into something business-critical, stitched together from APIs, models, agents, and data sources that weren’t originally designed to work together in this way.

That creates something fundamentally different. Not just another application, but something more fluid, a tool that behaves dynamically to make decisions and interact across multiple layers of the stack in real time.

And this is where the problem begins.

Where AI security currently breaks down

While the architecture that needs to be secure has changed, the thinking around security largely hasn’t, meaning traditional security measures are still being applied to situations they aren’t built for. Most organizations believe they have this covered. They’ve extended their existing controls, added new tools and invested in visibility. On paper, it looks like a sensible evolution of what they already had that keeps up with AI.

But in reality, much of that security still sits around AI rather than within it.

These traditional methods are protecting edges, monitoring outcomes and analyzing behavior after the fact. What they’re not consistently doing is sitting in the path of execution, where decisions are actually being made, and where things can go wrong in real time. It’s this distinction that matters more than most people realize.

AI doesn’t behave like anything we’ve secured before. A single interaction isn’t just a request and a response. It’s a chain of events where a prompt is interpreted, a model responds, an agent may take action, data is retrieved, decisions are made, and outputs are generated. This all happens in one continuous flow.

The risk doesn’t exist at a single point. It exists throughout that chain. This is where prompt injection happens. It’s where models can be manipulated, where sensitive data can leak through inference and where unintended behaviors and outcomes emerge.

The cause of this isn’t always an incorrect configuration; it can also be the result of the system responding exactly as designed, just not in the way anyone expected.

The industry is starting to acknowledge this. There’s a growing recognition that runtime is where the real battle is being fought, and that securing AI means understanding how it behaves under pressure, not just how it’s built.

Moving beyond bolt-on security

But if that’s becoming clearer, why are so many organizations still getting it wrong? Well, in most cases, it comes down to how decisions are being made. AI is often being driven by innovation teams or developers, those who are closest to the opportunity and implementation of AI tools.

But that also means infrastructure and security decisions are following behind rather than shaping the architecture from the start. At the same time, there’s a tendency to default to adding more tools to plug the security gaps. Faced with a new risk, the natural instinct is to look for something new and shiny to buy that addresses it.

AI doesn’t fit neatly into that model. It doesn’t live in one place. It cuts across applications, APIs, data, and user interaction all at once. Treating AI as something you can secure with a standalone tool misses the point entirely.

What is actually needed is a different way of thinking, one that starts with looking at where control actually needs to exist. There are only so many places security can be meaningfully enforced, and for AI, one of the places that consistently matters is the flow of traffic itself.

This is the point at which requests are made, decisions are processed, and responses are returned - where behavior can be influenced the most and where policy can be enforced. Everything else, to some degree, is reactive.

This is also where the conversation around security platforms becomes more interesting. Not because AI capabilities have simply been added to existing portfolios, but because the role these platforms play is changing.

Sitting in front of applications and APIs, they have long been responsible for managing traffic, applying policy and enforcing decisions. What’s changed is that these same control layers are now being extended into AI interactions themselves.

That shift is subtle, but important, as it moves AI security away from being something that happens in isolation and closer to something that is embedded directly into how systems operate. Not bolted on, not observed from the outside, but enforced as part of the execution path.

This isn’t really about one vendor. It’s about recognizing that AI has changed the shape of the problem.

Control will define the next era of AI security

The market is still catching up. The tooling is still evolving. And most organizations are understandably feeling their way through it.

But the decisions being made now - where to place control, how to integrate security, what assumptions to carry forward from the past - will define how manageable this becomes over the next few years.

We’ve seen this before, just in a slightly different form. APIs went through a similar phase not long ago - rapid growth, fragmented control, and then a long period of retrofitting security once the risks became clear.

AI is moving faster than that ever did. The attack surface is broader, the behavior less predictable, and the consequences potentially more significant.

Which means there’s less room for getting it wrong.

The organizations that navigate cybersecurity well in the age of AI won’t necessarily be the ones that adopt AI the fastest. They’ll be the ones that understand where control needs to sit and make deliberate decisions about how it’s enforced. With AI, more than anything else, it’s not just about what you can see. It’s about where you can act.

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