Technology

Commentary: I can’t figure out if the Duo would replace my iPad, or if it’s just a portable alternative.

If you've worked in cybersecurity for as long as I have, then you'll know there are a couple of things you can count on. First, the threats that are out there never stop evolving. And second, sooner or later, you're going to be in the bullseye.

What makes life so much harder today is that AI and other automated tools have dramatically narrowed the gap between vulnerability discovery and the time it takes to exploit them.

And when this can now be measured in minutes – seconds, even – you know you have a problem. This fundamental change in the way adversaries operate means we no longer have the luxury of time to understand an attack, assess the risk and decide what to do next.

Which means we have to be better prepared and have resiliency for whatever is thrown at us.

Visibility is key

For me, that starts with accepting a simple reality: you cannot defend what you cannot see. And it’s why visibility is one of the most important capabilities an organization can develop.

After all, if you understand what exists within your environment – how those systems interact and what normal looks like – then you're in a much stronger position to identify unusual behavior before it develops into something more serious.

Observability, on the other hand, takes that visibility to the next level. It provides the context security teams need to make informed decisions quickly, especially when time is working against them.

In other words, visibility tells you what is happening, while observability helps you understand why it's happening.

And that’s crucial. Today's organizations operate across on-premises infrastructure, cloud environments, networks, and an increasing number of connected technologies.

As those environments become more distributed, understanding what's happening across them becomes significantly harder.

Without that visibility, it's difficult to understand where your risks are, how systems interact, or where an attacker may be able to exploit a weakness.

Think like a hacker

Which leads me neatly onto my next point. Throughout my career, including my time working in offensive cyber operations in the intelligence community, I've found that the most effective way to understand risk is to think like the adversary.

I start by asking how someone would attack an organization and then work backwards to identify and close gaps.

That’s because attackers don't see organizations in the way that you or I might do. They’re always on the hunt for a toehold in. They look for weaknesses in people, processes and technologies.

They look for the easiest route first to achieve their objective. And then they exploit that weakness.

And it’s an approach I would urge all security leaders to adopt if they want to stay one step ahead.

That means continuously asking where an attacker would start, how they would move through the organization and what controls would slow them down or stop them altogether.

But for this to work, it also requires organizations to design resilience into the way they operate. And that’s something we’ve embedded across our organization.

For instance, we have internal and external teams that conduct continuous product, enterprise, spear-phishing and physical penetration testing.

For us, it's about educating the team across the business to ensure they remain vigilant. But it’s also about inoculating people so that when they see something suspicious online, they have that instinct that something might be wrong and they report it.

We also want to make it easy for people to report events so we can analyze them quickly and better understand the targeting.

Secure by design

We’ve also invested heavily in Secure by Design to ensure that all the products we deliver to customers are as secure as humanly possible. In practice, it means being able to trace every piece of code back to its source and verify its integrity throughout the development process.

It's similar to maintaining a chain of custody for evidence. We want to know exactly where software components come from, how they're verified and how they're protected throughout the entire build process.

More broadly, Secure by Design is increasingly being adopted across our industry as organizations recognize the importance of software integrity, traceability and transparency throughout the development lifecycle.

This is important because, as I said at the beginning, there are two certainties in cybersecurity: threats will continue to evolve, and organizations will continue to be targeted. Businesses across the world must adapt quickly to the grim reality that a cybersecurity incident isn’t a matter of if, but a matter of when. And AI is supercharging the pace at which all this is happening and broadening the blast radius of any attack.

That’s why you need to understand your environment well enough to reduce unnecessary risk, detect malicious activity quickly and limit the blast radius when something does happen. Pair that with a clearly defined and tested plan for recovery and that's what robust cyber resilience looks like in practice.

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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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Apple’s and Google’s phones are both rated for dust and water resistance. Here’s how they compare when it comes to other features such as cameras, battery life and displays.

Defense is operating in an environment where the pace of change continues to increase. Adversaries are adapting quickly and technology development cycles are becoming shorter. The boundaries between physical and digital operations are also becoming harder to define, while military commanders have more information available to them than ever before.

This changes how operational advantage is achieved. The performance of an individual platform or system remains important, but so does its ability to work effectively within the wider operational environment. Information needs to move securely to where it is needed, supporting decisions and action across different domains.

As new technologies are introduced, integration will become an increasingly important part of defense capability. The challenge is making sure innovation can be put to practical use alongside the systems and infrastructure already supporting operations.

Connecting technology across defence

Conversations around defense innovation often focus on AI, autonomous systems, advanced sensors, cyber capability and space assets. Each has a significant role to play, but none operates in isolation.

Information gathered by one system may need to be shared across multiple domains before it supports an operational decision. Networks, data, command systems and people all contribute to that process. The value of any individual technology is linked to how effectively it connects with the wider operational environment.

This principle also applies to the infrastructure supporting military operations. Communications networks, operational facilities and digital systems all contribute to creating an environment where information can move securely and reliably. As these environments evolve, resilience and security must be designed from the outset though approaches such as secure-by-design and zero-trust principles.

Strengthening the foundations of operational capability

AI has become one of the defining topics in defense. Its ability to process information and support decision-making has significant potential, but those capabilities depend on the quality of the data available and the resilience of the infrastructure that carries it.

Reliable communications, trusted data and secure networks remain fundamental to operational effectiveness. If those foundations are unavailable or compromised, the benefits of advanced technologies are reduced.

Therefore, creating decision advantage is not simply a technology challenge. It is an infrastructure and digital challenge and increasingly, a collaboration challenge.

For organizations supporting critical infrastructure, this has become an increasingly familiar challenge. Communications, operational technology, and digital infrastructure must work together to create environments where reliability cannot be compromised.

Keeping people at the heart of automation

Automation is attracting considerable attention across defense as organizations are looking to improve efficiency and increase operational tempo. However, automation should never be viewed as an end.

Its greatest value often comes from reducing routine activity rather than replacing people. Predictive maintenance, autonomous monitoring, automated network management and logistics optimization all help reduce the time spent on repetitive tasks, allowing highly trained personnel to focus on areas where experience and judgement remain essential.

The most effective technologies do not replace human capability - they amplify it.

The infrastructure supporting multi-domain operations

As operations become increasingly integrated across land, sea, air, cyber and space, infrastructure is taking on greater strategic importance. Communications, transport, energy, and digital systems all contribute to operational capability, showing how infrastructure and technology are becoming increasingly interdependent.

The movement of people, information, energy, and capability all contribute to operational readiness. Reliable infrastructure enables those elements to function as a single system, ensuring capability can be delivered when and where it is needed.

One example can be seen in the Falkland Islands, where runway infrastructure forms part of maintaining long-term strategic capability and readiness. It illustrates how infrastructure and operational capability are becoming increasingly interconnected.

Bringing innovation into operational use

The UK benefits from an established community of innovators, with government, industry, academia, SMEs and the Armed Forces all contributing to the development of new ideas and technologies. The opportunity now is to ensure those innovations can be adopted enough to meet operational needs.

Collaboration is still a critical part of this process. Bringing together different perspectives helps ensure technology is developed with practical application in mind and can be integrated more effectively into future capability.

Delivering the next phase of defense capability

Much of the technology required to support future defense operations already exists. The focus now needs to be on how quickly it can be integrated and put to operational use, giving the Armed Forces the advantage they need as threats and operating environments continue to change. That requires stronger connections across networks, data, platforms, people and infrastructure.

Collaboration between government, industry, academia, SMEs and the Armed Forces will remain central to moving capability from development into deployment. Technologies also need a clearer and faster route beyond demonstrations and pilots, so useful capability reaches operators when it is needed.

The organizations that succeed will be those able to bring people and technology together across the wider defense environment. Doing that securely, reliably and at pace will determine how effectively innovation translates into operational advantage.

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• Meta wants to upgrade ex-managers back to managers
• 7,000 workers were moved into the Applied AI org earlier this year
• Company's CTO admitted previous workforce changes were "atrocious"

Meta has reportedly partially reversed its decision to push for flatter, manager-light teams by asking some employees in its Applied AI business to move from individual contributor roles back into managerial positions.

New Business Insider reporting suggests Meta is asking certain workers to volunteer themselves as managers rather than forcing them into it, but without the company sharing comment on the matter, it's unclear how workers who refuse may be impacted.

As for the business itself, it's a pretty new one that was established this year, with around 7,000 employees shifted under the Applied AI umbrella.

Meta wanted fewer managers, now it wants more

Some of the workers who were previously assigned as managers were reassigned as individual contributors when they joined the Applied AI org, with Business Insider previously reporting how many workers felt they'd effectively been "drafted" into the business, highlighting ongoing friction internally.

The manager-light stance comes from CEO Mark Zuckerberg's 'Year of Efficiency' announcement in 2023, when he argued that a flatter organization could be more nimble and better poised for change.

With the company as a whole now on track to spend over $130 billion this year on AI chips and infrastructure, it's possible that a growing Applied AI organization could be behind the need for more traditional management.

Still, Zuckerberg's efficiency-driven, manager-light program seems to remain in force across other areas of the business, with this push for new managers looking to only be affecting Applied AI.

Separately, CTO Andrew Bosworth previously admitted that Meta's rollout of its new AI division was "atrocious" (via Wired), promising better communication for future changes.

"We shook up the management structure that was providing you stability while rapid changes in strategy, including the boom/bust cycle of hiring, left entire teams in the lurch," he admitted.

AI has rewritten the enterprise data playbook. Workflows no longer just create temporary operational data, but vast amounts of high-value assets, from LLM training datasets and model outputs to logs, metadata and archived knowledge that may need to be preserved for years.

As enterprise tech leaders seek to scale infrastructure to meet these demands, storage requirements are undergoing a fundamental shift. Capacity and performance remain critical, but data security has become equally important. Today, long-term data integrity and absolute cyber resilience carry equal weight.

Protecting this data, however, is no longer just about defeating today’s threat vectors. It requires preparing storage infrastructure for a significant shift: the arrival of quantum computing.

Data is a long-term strategic asset, not a short-lived trend

AI is accelerating data growth, but it can also extend the useful life of information. Data recorded today will be harvested for compliance, advanced analytics and model retraining for years to come.

To manage this economically, enterprise architectures rely heavily on high-capacity HDDs. While flash technologies dominate performance-critical hot tiers, HDDs remain the undisputed backbone of large-scale storage, providing the capacity, economics and longevity needed to archive data at scale.

As a result, organizations must consider how to protect not only today's data, but also its future value. After all, if the underlying infrastructure is compromised down the road, the very assets driving future AI innovations become the biggest operational and regulatory liability.

Harvest now, decrypt later

Current encryption technologies remain effective against conventional threats. However, quantum computing is expected to challenge some of the cryptographic methods used for authentication and key exchange.

This has led to concerns around “harvest now, decrypt later” attacks, where encrypted data is collected today with the expectation that future quantum capabilities could potentially decrypt it later.

For organizations storing sensitive intellectual property, research data or AI training datasets, this means security decisions made today could have implications for years to come.

Preparing for that future requires action from security leaders and IT directors now.

Security must be built into the infrastructure

Security is often viewed through the lens of data encryption, and with good reason. Self-encrypting drives (SEDs) provide always-on, hardware-based AES-256 encryption that helps protect data at rest without impacting performance.

But protecting data alone is no longer enough.

Storage devices themselves must be trusted. Firmware, authentication mechanisms, provisioning processes and diagnostic tools all play a role in ensuring a drive operates securely throughout its lifecycle.

If attackers compromise a device's firmware or trust architecture, broader security controls can be undermined regardless of how data is encrypted elsewhere in the system. This makes storage security a critical component of overall cyber resilience.

Implementing quantum-resistant defenses in storage

To counter these emerging attack vectors, the storage industry is actively embedding post-quantum cryptography into hardware architecture of enterprise hard drives. Rather than focusing solely on protecting data, the objective is to protect the trust architecture that underpins the drive itself.

Post quantum cryptography (PQC) technologies are being incorporated into areas such as secure key establishment, firmware authentication, secure provisioning, and trusted diagnostics. These capabilities are designed in alignment with established NIST post-quantum standards and are implemented using hybrid approaches that combine classical cryptography with quantum-resistant algorithms.

In practical terms, this means that the mechanisms responsible for establishing trust, validating firmware integrity and protecting administrative functions can remain resilient against both conventional and future quantum-enabled attacks. With the operational service life of HDDs often spanning 5 years (or more), implementing PQC today helps protect against quantum-based threats that may not materialize for several years, but that we know are coming.

Importantly, HDDs have long incorporated security controls to defend against today's threats. PQC does not replace these protections; it enhances them by adding an additional layer of resilience against emerging attack vectors.

Trust in the AI era

For many years, storage innovation was primarily defined by increases in capacity. Today, the expectations placed on infrastructure are much broader.

Organizations seek storage platforms that can scale with AI-driven data growth, deliver reliable performance, preserve integrity over long retention periods and withstand an increasingly complex threat environment.

PQC represents an important step in that evolution. By extending protection beyond data encryption and into the trust mechanisms that underpin storage devices themselves, PQC-enabled HDDs help organizations prepare for the security challenges of tomorrow while protecting the data they manage today.

As AI continues to elevate the strategic value of enterprise data, security can no longer be a short-term, reactive consideration. Trust must be engineered directly into the hardware layer and built to outlast the threats of today, tomorrow and the quantum era ahead of us.

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• Qobuz wants you to make a memory-filled playlist, and explain it
• You can win an iFi iDSD GR 2 for your efforts
• World Alzheimer's Month runs through September

Alongside 'Fast songs for the gym' and 'Band 101 for introducing a partner to a band on the eve of going to their gig', remembering moments or periods of your life is one of the most important reasons we make playlists. I still listen to "mix-tapes" (in digital format, mostly) I made while living abroad, road tripping around the outback or preparing for big university parties.

Now, streaming service Qobuz has taken time off its war on AI slop to acknowledge the link between music and memory for World Alzheimer's Month, teaming up with hi-fi tech brand iFi Audio to do so.

World Alzheimer's Month runs through September, and during that time, Qobuz and iFi are running a competition to submit a memory-laden playlist, and perhaps win an iFi iDSD GR 2 for your efforts.

Wait, what's the link? Well, it has been shown that musical memory remains well-preserved in Alzheimer's sufferers, and so a song may help with memory recall.

I'm getting this from a study published in the National Library of Medicine, which suggests that music interventions can "delay and decelerate the neurodegeneration in individuals at risk". But my colleague and Audio Editor tells me she has seen music's profound effect on memory recall in a fellow dancer who (even in advanced stages of this progressive disease) could still perform decades-old choreography, if the music were played.

Many non-profits, including Music & Memory or Playlist for Life, exist to help people by providing training, awareness or music-based care, to aid those suffering with various degenerative illnesses.

What about that competition?

(Image credit: iFi / Qobuz)

Oh yes, the competition.

During September, Qobuz and iFi want you to make a playlist (on the former's hi-res download and streaming platform, of course) full of songs which bring you back to a certain time or important memory.

Then, you need to head over to iFi Audio's competition landing page, which will give you a few steps to complete and fields to fill in.

This page also lets you provide a 'short story' or description of what the playlist means to you. There's no stated word count, but this whole news story could be pasted into the field with without a problem.

Once you've submitted your playlist, you'll be in with a chance to win the iFi iDSD GR 2 DAC (or digital-analog-converter, to level up your music using, say, the USB-C port on your phone, and on to your wired headphones or earbuds), worth $529 / £529 / AU$849. And that's a great prize. We gave the iFi IDSD GR 2 a perfect, 5-star review, praising its sound quality and easy-to-use touch-screen. So good luck!

There's no indication of how the brands will choose a winner; if it'll be based on the description, or tracks, or at random. It's also not clear what will happen to the rest of the playlists; maybe Qobuz will publish some of its favorites for all to see, but perhaps the submission is just for the purposes of the competition. Either way, delving back into old albums and tracks that really take you back to a specific moment will be a cathartic — and sometimes profound — experience. Music's great, isn't it?

Spoilers for The Paper season 2 ending ahead.

Regardless of whether you love or loathe Esmeralda (Sabrina Impacciatore), you can't deny that she's made The Paper season 2 ending incredibly memorable.

While Ned (Domhnall Gleeson) comes to Mare's (Chelsea Frei) rescue at The Cincinnati Chronicle, Esmeralda is on a mission of her own. Distraught by the news that her son has got C on his latest school exam, she undertakes an undercover investigation to get to the bottom of the "injustice."

As Oscar (Oscar Nuñez) tells us, these Esmeralda specials tend to be a regular occurrence. She's donned a fat suit to protest weight restrictions at a local playground, and disguised herself as a balding, older man to work out why those who "aren't attractive" are having problems dating.

This time, Esmeralda's transformation comes in the form of a teenage boy, dressing up in a short brown wig, baggy football jerseys and a backwards cap — much like a member of N*SYNC — to infiltrate Matteo's (Zak Messinger) class, though she's immediately detected.

While Matteo is willing to indulge her ridiculousness (albeit for a short time), the sheer stupidity of it all makes it the best moment in the entire season. But which disguise did Impacciatore find the most uncomfortable?

'I was shocked when I looked in the mirror'

"I had so much fun with that," Impacciatore tells me. "The most uncomfortable was the woman.... but the older man was horrible.

"I felt so shocked looking at myself in the mirror, and that shock remained for a good few days. I didn't recognize myself... just a very shocking experience. It's literally just for a few seconds in the show, but the experience of it lasted."

Personally, I'd enjoy an entire episode dedicated solely to Impacciatore's old man, who tells a group of attractive younger women at a bar that just because he doesn't look like Marlon Brando — already an outdated reference — doesn't mean that he should be ruled out.

While Esmeralda is probably the least predictable character of the bunch, these episode 10 transformations do set her up for future undercover investigations if The Paper season 3 is greenlit.

If her more direct exposé has almost cost Esmeralda her job and status at the Toledo Truth Teller, then why not try alternative methods to do exactly what she wants to? Watch this space, is all I'm saying.

• Marvel has seemingly cast a Gen V alumnus as Angel in its new X-Men movie
• Asa Germann is said to have signed on to play the winged mutant
• For the most part, MCU fans have reacted positively to the news

Marvel has reportedly tapped Asa Germann to play Angel in its new X-Men movie.

The Hollywood Reporter (THR) first broke the news, with the trade publication's sources claiming that the former Gen V star has signed on to play the winged mutant in the Marvel Cinematic Universe (MCU).

Interestingly, THR suggests that Germann was a major contender to portray Scott Summer/Cyclops in the forthcoming flick. However, while Marvel decided to hire Kit Connors to play Cyclops in its X-Men reboot, the comic giant's top brass were so impressed by Germann's audition, they offered him the role of Angel instead.

After appearing in The Boys spin-off Gen V, Germann has some superhuman experience under his belt (Image credit: Prime Video)

At 28 years old, Germann is on the older side of the Marvel Phase 7 movie's cast, with many of his fellow stars in the 20 to 25 bracket. Nonetheless, Germann fits the bill as an actor under the age of 30 who, as long as he's signed a multi-picture deal, could feature in numerous X-Men and MCU movies over the next decade.

Real name Warren Worthington III, Angel is a founding member of the X-Men in Marvel Comics. As his mutant alias implies, he's defined by a pair of giant, white feathered wings that protrude from his upper back. Unsurprisingly, these allow him to fly, but Angel also boasts the usual superhuman abilities — super-strength, reflexes, stamina, and durability — that keep him in the fight for longer than ordinary people.

Germann won't be the first actor to embody Angel on the big screen. Indeed, Ben Foster portrayed the Marvel character in 2006's X-Men: The Last Stand, while Ben Hardy played the same individual 10 years later in 2016 movie X-Men: Apocalypse. For more on those films and other mutant-led flicks, find out how to watch the X-Men movies in order.

What have Marvel fans said about Asa Germann's casting as Angel in the MCU's first X-Men film?Comment from r/marvelstudios

In the main, MCU fans have lauded Germann's casting. Indeed, threads on r/MarvelStudios, r/MarvelStudiosSpoilers, and the ResetEra forums are filled with comments from people excited to see what Germann will bring to the table as part of his portrayal.

Funnily enough, as one eagle-eyed fan pointed out, Germann's first name actually means 'wing' in Portuguese, too. It's almost as if this was planned, isn't it!

While the vast majority are pleased with this hiring — shout out to long-time MCU casting director Sarah Halley Finn for yet another great pick, by the way — a couple of fans are giving themselves a well-earned pat on the back for previously suggesting that Germann would be their top choice for Angel. Not exactly the proven leaks we're used to, but I'll allow it.

Anyway, what do you think of Germann's casting? Let me know in the comments, and if you want to read more on the first MCU movie he'll star in, find out everything else we know so far about Marvel's new X-Men movie.

The newest Apple smartwatches have premium features — and prices to match.

• OpenAI for Financial Services comes with built-in premium datasets
• Third-party subscription sharing is also in the works
• GPT-6 promises 100% on the 256-512K Long Context benchmark

OpenAI has lifted the wraps off ChatGPT for Financial Services, its latest industry-specific version of ChatGPT Work designed to give sector professionals access to relevant reasoning and models.

The company warned that analysts regularly spend too much time finding data, checking figures, building models and turning complex analysis into presentation-friendly reports – all things it hopes to be able to tackle with this iteration of ChatGPT Work.

Core to this new product is, of course, GPT-6 Astra, but OpenAI also worked with investment experts from Morgan Stanley and Evercore to guide its development.

ChatGPT for Financial Services

With the launch of ChatGPT for Financial Services, OpenAI has built premium datasets from the likes of Daloopa, PitchBook and LSEG News directly into the tool, so users won't need to negotiate their own external datasets. By hosting and indexing that data itself, OpenAI can ultimately improve performance and latency for end users.

OpenAI also promises to be working with S&P Capital IQ, LSEG, MSCI, Dow Jones Factiva and Moody’s so that users can access their subscription benefits directly through their ChatGPT login to reduce the friction further.

All of this with the benefits of OpenAI's latest frontier model, Astra, which sees marked improvements across the board. The jumps from 91.5% to 100% at 256K-512K and from 73.8% to 96.3% at 512K-1M are especially noteworthy on the Long Context MRCR benchmarks when compared with GPT-5.6 Sol, because finance work often requires handling long documents like annual reports and filings.

The company also advertises a 100% score for the ExploitBench cybersecurity benchmark, which should come as welcome news to this highly-regulated industry.

Only eligible financial institutions will gain access to the tool for now, and they must contact OpenAI for options.

"ChatGPT for Financial Services is one way we serve customers across the industry, but we recognize that it will require a range of solutions to address the needs of the finance industry," the company said in its launch blog post.

"OpenAI has a long history of collaborating with innovators to unlock novel AI solutions. Financial services firms and developers can use our API to build specialized applications for the needs they understand best. OpenAI brings frontier models and the capabilities to put them to work. Financial institutions, data providers, and software partners bring specialized expertise, trusted information, and customer relationships."

Hunting for an iPhone 18 Pro case to go with your shiny new handset? I'm here to help. I've rounded up my favorite cases and covers from some of our favourite brands. Sure, you can get cheaper options if you go for a weird, no-name brand on Amazon, but with a phone this pricey, it really is worth paying a bit more for a case that's going to provide proper protection.

If you want a case with personality, head to CASETiFY — here you can choose your level of impact protection, as well as picking from a massive range of fun designs. Mous is brilliant for premium feeling, streamlined cases, and OtterBox shines when it comes to covers with built-in extras like finger grips and stands. Spigen is great for ultra-rugged protection, and if you want a leather wallet, Snakehive is the brand to look for. Of course, Apple makes a few official options, too. You'll find all these below.

Not bought your phone yet? Here are our iPhone 19 Pro first impressions, and a guide to Apple iPhone 18 Pro preorders.

In the US? Head to my US iPhone 18 Pro case roundup instead

iPhone 19 Pro cases

Apple Silicone Case — Magenta

Spigen Rugged Armor Case, Matte Black

Apple Clear Case With Magsafe

CASETiFY Cloud Case

CASETiFY Ultra Impact Case — Floating People #2

CASETiFY Ultra Impact Case —EttaVee Watercolor Fleurs

Mous Limitless Black Leather Cover

OtterBox Commuter Series Case — Green

Mous Limitless Speckled Black Cover

Spigen Liquid Air Case — Matte Black

Snakehive Leather Wallet Case — teal

Mous Clear Case

OtterBox Defender Pro Series Case - Green Intrigue

CASETiFY Ripple Case — White

OtterBox Defender Pro Case, Black

OtterBox Figura Case, Blue

Spigen Tough Armor T Case, Black

Spigen Ultra Hybrid Case, Clear

Snakehive Leather Wallet Case — navy

Apple Techwoven Case With Magsafe – Burgundy

Spigen Ultra Hybrid Case

The vast majority of enterprise leaders are bullish about how ready their organizations are for AI-generated code. However, once that code reaches production, this confidence wavers as incidents arise. This pattern shows up across multiple independent studies in this year alone.

For instance, data published in April 2026 found that monthly production incidents climbed by almost 58% as AI coding tools scaled across engineering teams. A similar study from June found that the same volume of code changes is now producing more than three times the production incidents it did before AI coding tools were introduced en masse.

These findings are echoed in the 2026 State of Code Abundance Report, which surveyed more than 200 enterprise technology leaders and found that 92% expressed confidence in the production readiness of AI-generated code and rated their own AI-code readiness at an average of 84 out of 100.

Yet, the same study found that 81% reported an increase in production issues tied to AI-generated code - indicating a significant gap between confidence and control. While 93% say they have a formal process for reviewing and releasing AI-generated code into production, only 56% report that those processes are always enforced.

Furthermore, 86% of the same respondents report full or high visibility into AI-generated code, signaling a major contradiction - high visibility and rising incidents cannot both be describing the same pipeline.

Understanding the visibility gap

This is a familiar phenomenon in business, where confidence tends to be highest in areas where organizations have the least ability to measure their own performance. These enterprises aren't lying about their trust in AI-generated code, they believe it is production ready. The issue is that belief has out-grown the instrumentation needed to verify it.

We need to remember that AI coding tools are, by most measures, doing exactly what they were built to do: allowing more code to be produced faster and shifting engineering effort from writing code to deciding what should ship. Prior to this, the amount of code an organization could produce was largely tied to the size of its development team, incurring significant constraints for many.

In the agentic era, this barrier has effectively disappeared. What hasn't been adjusted is understanding what that code does once it's live, who wrote it, why it changed, and what broke when it did. Most organizations could stay on top of this governance while code was being written at human speed, but the challenge now is keeping up with the pace of agentic coding.

AI has widened a visibility gap that already existed, at a pace most governance structures were never designed to keep up with. For enterprise leaders right now, the natural instinct is to estimate how much faster AI can make their teams. This thinking leads many organizations to fall into the trap of prioritizing speed over quality, which leads to more errors when code is deployed - causing the process to slow dramatically.

The importance of code governance

Before investing heavily in AI coding tools, the best thing to establish is an idea of how much of your current pipeline you can actually see, measure and attribute. As only 12% of organizations have a dedicated team for governing AI-generated code, the vast majority of enterprises adopting these tools are doing so without a designated owner for the risk they're taking on.

This means that when something goes wrong, there's frequently no clean way to trace it back to a decision, model, or person accountable for the outcome.

This is the part of the pipeline that doesn't get enough attention, because it's less exciting than the productivity headlines. However, it's the part that will determine which organizations actually reap the benefits of agentic coding and which ones spend their time and resources cleaning up after it.

There’s a temptation, which is understandable given the competitive pressure, to treat AI-driven code generation as a race: whoever ships the most, fastest, wins. This is the wrong way to think about it, and the winners will actually be the ones that pause and strengthen their governance before they accelerate.

Control vs playing catch-up

The organizations that will benefit from this shift are the ones building measurement, attribution and oversight into their pipelines ahead of time. That means treating governance as infrastructure rather than paperwork and being able to answer, at any point, which parts of their codebase were AI-generated, who reviewed them, and what production behavior they're responsible for.

Furthermore, budget owners must be able to say what they're actually spending on AI-assisted development, rather than estimating.

None of this slows delivery down in the long term, and if anything, it's what allows delivery to keep accelerating without the incident curve growing alongside it. The gap between how confident enterprises feel about AI-generated code and how much of it they can actually see isn't going to close on its own. It will close because leadership teams decide to build the visibility first.

The organizations that do that now, while the rest of the industry is still counting lines of code shipped, are the ones that will still be standing when the next wave of AI-driven development arrives.

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Here are hints and the answers for today’s Connections: Sports Edition puzzle No. 718 for Friday, Sept. 11, 2026.

Trump Mobile’s T1 phone now costs $749, echoing price hikes across other phone retailers.

• Boeing receives $12.68 million investment to update the MQ-25's RF blanker, encrypted storage, and mission computer security, running through November 2029
• The change is a recent one: the Navy's April 2026 acquisition report lists refueling as the MQ-25's primary mission and intelligence, surveillance, and reconnaissance (ISR) as secondary, with no electronic warfare requirement and only two key performance parameters
• An RF blanker is electromagnetic compatibility hardware that stops an aircraft's own transmitters from deafening its receivers, allowing it to conduct EW more effectively

A single line buried in a recent US Department of War contract announcement is being read across multiple channels as the Navy's first carrier-based drone acquiring multiple electronic warfare upgrades.

The details, however, seem to focus on the defensive side of the spectrum and include a Radio Frequency Blanker Unit and an updated Encrypted Mass Storage System carrying an embedded Data Transfer System.

The modification also provides an option for deficiency analysis and corrections, supporting security assessments of the aircraft's Mission Management System Computer.

Why do these upgrades matter?

The most important upgrade for the MQ-25 Stingray, arguably, is its RF Blanker. An RF blanker is electromagnetic compatibility equipment. When an aircraft carries several transmitters and sensitive receivers within a few meters of each other, a transmitter firing at full power can deafen or damage a nearby receiver operating in an overlapping band.

A blanker fixes that by taking a blanking request from each transmitter and issuing a suppression pulse to the affected receivers for the duration of the transmission, as GE Aerospace describes. For a drone that could also house sophisticated EW capabilities in the future, this is essentially a prerequisite.

The Navy's Modernized Selected Acquisition Report dated April 21, 2026, offers a relatively narrow scope for the drone for now; however, it states that the MQ-25 conducts aerial refueling as its primary mission and provides Intelligence, Surveillance, and Reconnaissance capability as a secondary mission.

It is fairly possible that the upgrades are purely defensive, to prevent rogue players from accessing the drone or knocking it offline with relative ease. In its current capacity, the MQ-25 serves as an unmanned aerial refueling drone for the US Navy, offering capabilities including the ability to carry roughly 14,000 to 16,000 pounds of fuel at a combat radius of 500 nautical miles.

This could change even as the US continues hardening its EW offerings and prepares for potential hostile actors to have the same capabilities it currently harbors. For now, the $12 million invested in what is a $19 billion program is essentially a rounding error at the end of the day.

This sudden investment may signal more to come: Boeing has already pitched a land-based MQ-25 variant with external pylons and marketing language about ISR, electronic warfare, and airborne early warning roles, though the aircraft has no customer yet.

• The US Army has moved TITAN from prototypes into production
• Palantir received $127 million under the latest TITAN contract award
• Anduril secured $65 million for TITAN hardware and integration work

The US Army has shifted its Tactical Intelligence Targeting Access Node (TITAN) program from prototype status into full production this week.

Palantir Technologies and Anduril Industries together received a combined $192 million award covering the next production phase.

The Army first selected Palantir back in 2024 to serve as lead contractor for developing this next-generation targeting system for ground forces.

Contract splits work between two defense firms

TITAN was built to streamline how soldiers collect and process data when locating and striking distant targets on the battlefield.

Palantir secured $127 million of the total award and will oversee TITAN's production alongside several supporting partners in the effort.

Those partners include L3 Harris Technologies, Sierra Nevada Corporation, Strategic Technology Consulting and World Wide Technology, each contributing specialized capabilities to the program.

Anduril received the remaining $65 million and will build the hardened, vehicle-mounted units required for field deployment.

Anduril's portion also covers integrating power systems and thermal management components, so TITAN functions reliably in harsh operating conditions.

The program includes two distinct configurations built for different vehicle platforms and mission requirements across Army units.

An advanced version will mount on tactical trucks and can pull data directly from orbital sensor networks overhead.

A simpler basic version is intended for the Joint Light Tactical Vehicle, giving smaller units similar targeting capability.

Under the current award, contractors must deliver four advanced units and four basic units within eighteen months.

Production ramp builds on existing prototype fleet

These newly ordered units will supplement nine prototype systems the Army already operates and uses in current exercises.

Army officials have indicated they plan to issue further production contracts for TITAN sometime during fiscal year 2027.

The move from prototype to production status marks a milestone for a program meant to modernize how ground troops gather targeting information.

TITAN forms a central piece of the Army's broader push to overhaul aging ground systems across its combat formations.

By linking space-based sensors with vehicle-mounted terminals, the system aims to shorten the time between spotting a target and engaging it.

Whether that translates into a meaningfully faster targeting cycle in real combat conditions remains to be tested at scale.

The involvement of five separate companies alongside Palantir and Anduril suggests the Army is spreading technical risk across multiple vendors.

That approach could either strengthen the program's resilience or complicate coordination as production accelerates toward the 2027 follow-on orders.

For now, the contract signals steady progress rather than a dramatic leap forward for the broader modernization effort.

The scale of future procurement will depend on Army requirements, funding decisions, and how the systems perform during operational evaluation.

Via Defense News

• The US Navy approved Rolls Royce engines for autonomous surface vessels
• The certified engines can support missions lasting up to 30 days
• Series 4000 engines completed two separate 720-hour durability trials

The US Navy has approved Rolls-Royce marine engines for unmanned vessels capable of operating for periods reaching 30 days without crews onboard.

The certification covers mtu Series 4000 and Series 2000 engines following tests examining their suitability for extended autonomous naval missions.

The approval comes as the Navy expands its use of unmanned surface vessels for missions where keeping sailors away from danger remains important.

Rolls Royce engines clear tests for autonomous vessels

The Series 4000 completed two separate 720-hour durability assessments before receiving approval for propulsion and onboard electricity generation duties.

That engine can deliver as much as 4,300 kilowatts for propulsion while providing up to 3,000 kilowatts through its electrical generation system.

The smaller Series 2000 gained approval after component checks and operational trials, allowing it to provide propulsion output reaching 1,939 kilowatts.

Both engine families can now support Navy vessels designed for lengthy missions without requiring people aboard for routine maintenance or repairs.

The certification followed requirements established through the National Defense Authorization Act, which sets conditions governing equipment used within autonomous military platforms.

The Navy has already begun deploying unmanned boats, including Sea Hunter vessels fitted with twin mtu 12V 2000 engines supplied by Rolls Royce.

That deployment gives the newly approved engines a direct connection with the Navy's growing fleet of vessels designed for remote operations.

The company says its propulsion systems have supported naval operations for decades, while newer autonomous missions create different demands for endurance.

“For decades, mtu engines have been trusted to provide reliable, mission ready power for our crews at sea,” said Scott Hanson, vice president of governmental sales at Rolls Royce Power Systems North America.

Longer missions create new demands for naval engines

The ability to keep a vessel operating for 30 days without onboard personnel changes how the Navy can use unmanned surface craft.

Such vessels can remain at sea for extended periods while avoiding the accommodation, support, and immediate safety requirements associated with crewed naval platforms.

Rolls-Royce said the certification gives the Navy additional options as unmanned vessels become part of its wider fleet plans.

The company also supplies propulsion equipment for several unmanned aircraft, including the MQ 4C Triton and MQ 25A Stingray platforms.

Its portfolio also includes engines used by the United States Air Force's RQ 4 Global Hawk unmanned aircraft.

The latest approval therefore extends an existing relationship between Rolls Royce and American military programmes into autonomous maritime operations.

The certification does not mean every unmanned vessel using these engines will automatically achieve 30-day endurance during actual missions.

Actual operating duration can vary according to vessel design, speed, weather, payload, fuel capacity, mission demands, and maintenance requirements.

For the Navy, the immediate significance lies in having certified propulsion options for vessels expected to spend longer periods operating without crews.

As more unmanned boats enter service, engine reliability will remain important because failures far from support facilities can impede mission success.

Via The Drone Front

• Ukraine has started European production of its BARS jet-powered strike drone
• The latest BARS configuration reportedly has a 1,000 kilometers range
• BARS can now carry warheads weighing up to 60 kilograms

Ukraine has begun production of its BARS jet-powered strike drone in Europe, and the latest version has a range of 1,000 kilometers.

Production commenced in early September, intending to support higher output as developers continue to modify the drone for different mission needs.

This is a joint effort between Ukraine and Germany, with the first completed drones expected to reach Ukraine's Defense Forces from October 10 2026.

BARS enters European production with longer reach

The arrangement followed an agreement signed July 8 by Ukrainian Foreign Minister Andrii Sybiha and German Defense Minister Boris Pistorius.

Germany is financing the first production stage, while completed systems are intended for use by Ukraine's armed forces.

Engine availability remains a key limitation, since turbojet deliveries currently determine how quickly additional aircraft can leave production.

The BARS jet-powered strike drone can travel above 700 kilometers per hour while carrying a substantial warhead.

However, with several modifications and upgrades, the newest configuration can reportedly travel 1,000 kilometers.

Its maximum warhead weight has also increased substantially, rising from 22.5 kilograms on earlier models to 60 kilograms.

Its design allows developers to alter fuel storage and payload capacity based on the distance required for a particular mission.

Longer missions can use additional internal space for fuel, while shorter flights can devote more room to carrying additional weight.

Developers keep changing the drone and its guidance

BARS has reportedly gone through more than 40 design changes and upgrades since the prototype was developed.

The platform is divided into DeepStrike, MiddleStrike and FrontStrike configurations, covering different mission ranges and operational requirements.

The developer says artificial intelligence now contributes to several stages of the program, including engineering work and the drone's final guidance system.

“We use the tools that AI technologies provide us today, and we do not shy away from them at any level—from development and solving engineering problems to implementing machine vision in our target-guidance systems,” said the BARS developer.

During the final part of its flight, the operator can continue controlling the drone or transfer control to optical guidance.

This expansion of BARS production is a strategically sound move for Ukraine because German financing and supply chain ease pressure on Kyiv's defense budget.

Producing BARS in Europe also shields manufacturing from Russian strikes that have repeatedly targeted Ukrainian defense facilities.

For Germany, this partnership signals a deepening commitment to Ukraine's long-term defense industrial base rather than merely short-term arms transfers.

It strengthens bilateral ties and proves that European backing can translate into real, sustained battlefield capability.

Such a longer-range, heavier-payload drone with AI-assisted guidance raises Moscow's defensive costs by threatening targets deeper behind the front line.

This forces Russian air defenses to stretch across a wider geography, while the joint-production model may set a template for future allied co-production deals.

Via United24media