Strands is the NYT’s latest word game after the likes of Wordle, Spelling Bee and Connections – and it’s great fun. It can be difficult, though, so read on for my Strands hints.

Want more word-based fun? Then check out my NYT Connections today and Quordle today pages for hints and answers for those games, and Marc’s Wordle today page for the original viral word game.

I want to share a story of struggle. Actually, two kinds of struggle.

My father completed his doctorate at the University of Utah in the early 1970s. For his dissertation, he ran a statistical analysis on genealogical records to determine the impact of certain economic conditions on family size.

He accomplished this on one of the most advanced computers of the time. His method? Literally punching out little rectangles in dozens of stiff paper cards, and feeding the stack into the computer.

My father was a lowly graduate student, and because the demand for computing time at the university was sky high, he had to run his analysis in the middle of the night. He spent many nights punching cards and running them through the machine. Even a single mispunch would cause the entire program to stop running and require painstaking troubleshooting, re-punching, and another night at the computer lab.

Unproductive vs. Productive Struggle

The soul-sapping sleep deprivation and endless paper punching that stood between my father and his goals represents the first kind of struggle in my story: unproductive struggle — the challenging, unavoidable tasks we must perform toward a learning goal, but which add no value to the intellectual outcome.

The real intellectual challenge in my father’s work was in deciding which variables belonged in the model, determining how to represent economic conditions over time, and interpreting the data. This is the second kind of struggle: productive struggle. That is, the effort a learner expends to make sense of concepts, to figure something out that is not immediately apparent. This struggle leads to growth and insight. It builds judgment, expertise and understanding.

What is frustrating about my father’s story in hindsight is that so much of his time and cognitive energy were consumed by the unproductive struggle of punching cards and managing the computer. Without those barriers, he would have had more capacity for the productive struggle that leads to meaningful learning.

Thinking About What Matters

When it comes to AI in schools, some educators fear that it will lead to learning becoming too easy. This is referred to as “cognitive laziness.” The assumption is that we will offload our thinking to AI and eventually lose our ability to think critically. This is a risk with any technology that makes our mental work more efficient, and AI is uniquely adept at taking on cognitively demanding tasks. But ceding our reasoning power to AI isn’t a foregone conclusion. And simply not using AI in learning settings doesn’t have to be our solution for preserving our mental capacities.

Just as better computing tools would have freed my father from punching cards without removing the intellectual rigor of his work, today’s tools, including AI, have the potential to offload unproductive struggle, while preserving, and even amplifying, the productive struggle that is central to learning.

Here’s an example: When reading comprehension is not the goal of a lesson but a necessary prerequisite — a student having to read an article to understand the causes of the French Revolution, for example — AI tools can adjust reading levels on the fly to assist learners who are below grade level or for whom English is not their first language. This allows them to focus on the history rather than on decoding the text.

Refining Rigor

So what does this mean for educators who are grappling with how to help students use AI effectively?

First, we need to remind ourselves and help our students understand that the goal of learning has never been to make learning easy. It is to make it meaningful. We must ensure that learners are spending their time wrestling with big ideas, not battling logistics or bogged down by rote tasks.

Second, educators need to face a hard truth about the assignments we give students. Many assignments contain a mix of productive and unproductive struggle, and we are not always very intentional about which is which. Under crushing time and resource pressure, we can become unreflective about the distinction between productive and unproductive work. We inherit assignments, reuse problem sets, and value rigor without always asking where the rigor actually lies.

If AI forces us to confront that, it may be one of the most useful disruptions education has experienced in decades.

For instance, requiring students to write citations according to a set format may feel rigorous, but the cognitive work of formatting has little to do with the intellectual work of evaluating sources and integrating evidence into an argument. This shift requires us to redesign tasks, rethink assessments and, if necessary, let go of practices that feel rigorous but don’t meaningfully deepen understanding.

Sharpening Learning

If we do this well, AI won’t hollow out learning; it will sharpen it. It will give students more space to wrestle with ideas instead of mechanics, more time to interpret instead of transcribe, and more opportunity to make active sense of the world. It will give us a chance to be far more intentional about the kind of struggle we ask students to engage in.

In the end, AI won’t decide whether our students experience cognitive laziness or cognitive growth. We will decide that by how we design assignments and assessments, and by the choices we make about which AI tools to adopt and how we choose to use them.

This is our chance to weed out the punch cards and open up more time for students to struggle over things that truly matter.

Amazon CEO Andy Jassy may have been the source of security concerns that led Anthropic to cut off worldwide access to two models on Friday.

The Wall Street Journal reports that Jassy told Treasury Secretary Scott Bessent and other government officials that Amazon researchers used Anthropic’s Claude Fable 5 to obtain information that could be used in cyberattacks. The government subsequently imposed an export control ban on the Fable 5 and Mythos 5 models.

An Amazon spokesperson said in a statement that while it’s “not uncommon for governments to seek our counsel on potential security risks,” the company does not “share the details of those discussions.”

The spokesperson also pointed to an update stating that AWS has been affected by the model cut off.

The Information and Reuters similarly reported that Amazon (a major Anthropic investor) had communicated concerns about the security of Anthropic’s models.

David Sacks, Trump’s former AI czar who now co-chairs the President’s Council of Advisors on Science and Technology, offered his own account of the discussions, claiming that “a highly credible trusted partner of both Anthropic and the USG […] came forward with a jailbreak.”

Sacks added, “The Admin asked [Anthropic CEO Dario Amodei] to fix the jailbreak or de-deploy the model. Dario refused.”

Anthropic said in a blog post that the capabilities apparently causing government concern are already available in other publicly accessible models.

This post has been updated with a statement from an Amazon spokesperson.

It was published by KPMG, one of the world’s ‘Big Four’ accounting firms.

Professional services firm KPMG has pulled a report titled, “Redefining excellence in the age of agentic AI,” after numerous organizations said the report’s claims about their AI usage were untrue.

Research group GPTZero identified a number of inaccuracies in the report, which was published in October 2025. GPTZero told the FT that the inaccuracies stemmed from AI hallucinations. In other words, the professional services firm appears to have used AI to help write a report about AI. 

UBS, the UK’s National Health Service, Swiss Federal Railways, and Transport for London all told the FT that the report’s claims about their AI usage were either untrue or misleading. A KPMG spokesperson said the firm removed the report from its websites while conducting its own investigation.

“We expect all our people to follow our guidelines on the responsible use of AI, including human oversight to validate content and verify independent sources,” the spokesperson said.

Last month, EY withdrew a report on loyalty rewards programs that appeared to include fake footnotes and AI hallucinations.

While Hollywood has fake cities for filming movies, the FBI apparently has one for getting hacked. The agency has pulled back the curtain on its Kinetic Cyber Range, a 22,000-square-foot replica small town hidden inside its Huntsville, Alabama campus. But instead of training officers for shootouts or hostage rescues, the facility is designed to simulate realistic cyberattacks on homes, businesses, and critical infrastructure so investigators can practice responding to them in a controlled environment.

The FBI built an entire town just to simulate cybercrime

The indoor complex includes buildings such as homes, a hotel, a gas station, a courthouse, and even a fully functional data center packed with around 200 servers. Each location is wired with operating systems, connected devices, and live networks to mirror the kinds of digital environments agents encounter during real investigations.

According to the FBI, trainees can investigate simulated ransomware attacks, recover evidence from hacked vehicles, and trace digital footprints across multiple interconnected systems. Since opening last year, the facility has reportedly trained more than 1,400 FBI personnel and members of other government agencies. The goal is simple: replace classroom theory with realistic, hands-on scenarios where mistakes can be made safely before agents face similar incidents in the real world.

Cybercrime has become too real to train with PowerPoint slides

The idea might sound unusual, but it reflects how modern cyberattacks increasingly spill into the physical world. Ransomware can shut down hospitals, compromised industrial systems can disrupt utilities, and hacked vehicles or IoT devices often require investigators to understand both hardware and software simultaneously.

In many ways, the Kinetic Cyber Range is the cyber equivalent of the FBI’s famous Hogan’s Alley training town in Quantico, except the bullets have been replaced by malware and forensic tools. As digital attacks continue targeting everything from power grids to city infrastructure, having an entire fake town where agents can safely break and rebuild systems before responding to the real thing suddenly feels less like science fiction and more like a necessity.

Over two years after the Apple Car program was declared dead, Apple has offloaded its 5,500-acre Arizona proving ground to Waymo. It’s a sale that recoups $220M from the $10B Apple spent on the failed project.

The Apple Car project is a program believed to have been cancelled by Apple after about a decade of research and development. In what is the surest sign of it being dead, Apple has sold off a massive parcel of land used for self-driving vehicle testing.

In a filing reported by TechCrunch dated June 5, the property at Wittman, Arizona, has been acquired by Waymo. The sale, which was confirmed by Waymo, sees a payment of $220 million being handed over to Route 14 Investment Partners LLC.

Route 14 is a Delaware shell company believed to be connected to Apple. After renting the facility for a number of years, it Route 14 acquired it for $125 million in 2021.

The purchase gives Waymo yet another place to test out its vehicles. It already has locations in California and Ohio, but the Arizona lot will give it a massive amount of land for testing its fleet.

A Waymo spokesperson said the Arizona facility would be used to simulate driving scenarios in a controlled environment. This is to test its self-driving system, including rider-only testing, motion control, operational training workflows, and its future testing needs.

A self-driving playground

Apple’s renting and later purchase of the facility made sense at the time. It is a location that has a lot to offer companies in the automotive business.

The 5,458-acre site was previously used by Chrysler, again as a vehicle proving ground. It was then sold to a housing developer in 2005, but was later annexed by the City of Surprise and left alone.

A view of the facility – Image credit: Google Earth

In 2016, the city signed a development agreement with the then-owner SFI Grand Vista LLC, under the intention that it would be used by Route 14.

Despite being over 5,000 acres in size, only a small part of the facility has been set up for testing purposes. There is a 115-acre city course, as well as a freeway course geared towards autonomous vehicle testing.

It also has a 35-acre vehicle dynamics area and a four-mile oval track.

The sheer size of the facility provides ample opportunity for occupiers to build out the area for extended testing. All while still maintaining a safe distance from the edge of the lot, which also helps keep the testing private.

Cash back from an expensive project

The sale of $220 million in now-unused land sounds like a lot, and so does the $95 million in value the site earned in just five years. That is, until you remember that this involves Apple.

At Apple’s scale, the proceeds of the property sale will help fund other projects, but it’s pocket change compared to its other investments.

Indeed, compared to the $10 billion Apple has been estimated to have shelled out over a decade for Project Titan, it’s barely 2% of the outlay.

It is, however, an attempt by Apple to shed the last vestiges of the extremely expensive failure.

It’s no longer testing its self-driving system on roads, after cancelling the Autonomous Vehicles Program Manufacturer’s Testing Permit in September 2024. Holding onto private grounds for testing doesn’t make sense if there aren’t any planned for the future.

The work wasn’t entirely a bust for Apple, as the teams and research that went into it will have been absorbed by other parts of the company. It’s not hard to imagine some of the computer vision elements being incorporated into Apple Intelligence, or elements being used to push forward its robotics efforts.

The sale, two years after a very public funeral for a very secretive project, is merely Apple getting rid of a massive site that it has no use for anymore.

It’s a reminder of the costly mistake that hurt its wallet and with little to prove for it.

The Leadership Effectiveness Analysis best practices report explores the qualities that differentiate high-performing tech leadership professionals from their less effective counterparts.

Leadership skills in 2026 are a critical capability that enable professionals in all industries to navigate the highs and lows of the ever-changing global working environment. Whether a job announcement, acquisition, or restructuring, there is always a challenge to be overcome, and positive leadership is often the driving force towards success or a favourable outcome in a difficult situation.  

Touchstone Executive Assessment recently published the results of its Leadership Effectiveness Analysis best practices report. The company collected data from 142 senior professionals in advanced technology roles, across multiple European organisations, between March 2023 and March 2026. The aim was to determine the specific leadership attributes that differentiate highly effective and less effective leaders. 

The report said: “Many years of research and practice assert a direct connection between leadership effectiveness and organisational performance.

“Organisations, however, differ widely in terms of their culture, history, business strategy and people. Because organisations present unique cultural signatures, there is no one best model or profile of effective leadership behaviour.”

Leading in tech has undoubtedly become more complicated as professionals are working in a landscape that is being heavily impacted by political and social instability, threats to global supply chains and mass layoffs at major organisations. With that in mind, now more than ever, it is critical that tech leaders motivate and drive positive action in the workplace. To do that, a hefty arsenal of diverse skills is necessary. 

Steady skills

Among those identified by Touchstone Executive Assessment (TEA) as the most critical skills for a modern-day tech leader was significant cognitive ability. TEA’s research found that leaders depend on the ability to learn quickly, think strategically, see the bigger picture and embrace ambiguity. 

The report said: “Technical knowledge and domain expertise, while important in themselves, are not the factors that differentiate the best in class from the average. It is the ability of the individual to reason under uncertainty, in real time and in a very expansive manner.”

In blending domain expertise with the ability to view one’s industry through a strategic lens, TEA’s report found, professionals can take into account the long-term implications of decision-making, improve business aptitude and create that big picture perspective.

The data also suggested that operational and interpersonal skills are key areas to work on for professionals in demanding technology roles.

“This is where the worlds of technology and people really come together,” the research noted.

“While execution focus and a production mindset are important, leaders in advanced technology must also be able to manage stakeholder relationships, to communicate and influence effectively, and to drive accountability and engagement across their entire landscape. 

“This goes well beyond project management; there is a real sophistication in understanding the organisational environment, knowing the rules of the game and rallying people behind the mission as well as the person.” 

Strong leaders, it said, will have the ability to understand organisational dynamics, effectively lead organisational change and deliver results.

Long-term stability

Perhaps unsurprisingly, given the current state of global instability and disruption, TEA’s report also indicated that professionals who show the ability to thrive under pressure and scrutiny perform better in leadership roles. 

“This talks to the characteristics of the person, not just the person in their role. Our research indicates that personal and professional resilience are increasingly important factors, bringing an ability to sustain performance when the going gets tough and to bounce back quickly from setbacks.”

People in this position are, according to TEA, tenacious, determined and better able to sustain their performance in landscapes impacted by uncertainty and pressure. It found that they are unlikely to take issues personally or emotionally, as they demonstrate resilience, effective decision-making and a tolerance for ambiguity. 

Commenting on the results of the study, David Ringwood, the head of assessment and executive coaching at TEA, said: “There is no single right or wrong way to lead – context is king. Technology and AI today are very different than they were 10 years ago, and leadership accordingly needs to recalibrate in line with that shifting context and the changing expectations of employees. The best technology experts don’t always make the best leaders.

“Hiring, developing and building a book of talent that includes those who have the headroom to grow is critical, not least in technology and AI where there is always competition for top talent. This is a ‘how do we’ question – how do we objectively know what predicts the greatest future potential, how do we measure what is exactly relevant and how do we know we’re being as objective as possible?

“Putting the wrong person in the wrong role or career path is an expensive way for everyone to find out. This research may contribute to the definition of what high potential looks like in the tech sector and gives organisations a much clearer sense of where to build performance for today and leadership for tomorrow.”

Notably, in May of this year, technology and consulting company Expleo released the results of its AI sentiment tracker, AI Pulse, for Ireland, a report which found that business leaders in Ireland, ahead of their contributing European counterparts, are far more likely to value empathy as a fundamental skill for managers in the age of AI.

Among Irish business leaders, human-centric skills were identified as the most critical abilities a manager can wield, particularly in the context of increased AI adoption. 

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