Hello, dear readers!

Apple mastered the art of building beautifully made, deeply reliable devices. The question now is whether that same quality-driven playbook is enough for an era being shaped by AI. Read more below.

Also, Gallup has revealed that employee engagement has continued to slide globally, and job market optimism is particularly bad in the U.S. Why does this matter? Productivity is (or will soon be) in big trouble. Scroll down to find out more.

This issue features the usual bunch of AI Insights and recommendations for the week's podcasts, books, shows, charts, and tweets, followed by a final chuckle.

Let’s get going.

Industry Highlights: Apple’s next problem is that quality alone may no longer be enough

Apple mastered quality, but can that same DNA carry it through the AI era?

For most of Apple’s life, its strengths have looked almost timeless. Design. Simplicity. Product taste. The ability to make expensive technology feel intuitive, desirable, and somehow inevitable. But one of the most interesting points in Patrick McGee’s Financial Times Big Read on Apple at 50 is that the company’s real edge runs deeper than taste. Underneath the famous industrial design is an inherited philosophy of quality, manufacturing discipline, and systems thinking, much of it shaped by ideas that traveled from postwar America to Japan and eventually back into Apple through Steve Jobs’ long education in how great products are actually made.

That history matters because Apple now faces a very current question. If quality and execution were the foundations of its rise, are they still enough for what comes next?

The operating system beneath the products

McGee’s FT piece is compelling because it reframes Apple as the endpoint of a decades-long chain of industrial knowledge transfer. The article traces how management thinkers such as Homer Sarasohn, W. Edwards Deming, and Joseph Juran helped shape a culture of quality in postwar Japan, and how those ideas later influenced the systems and people around Steve Jobs. In this version of Apple’s history, the breakthrough is the ability to combine product ambition with repeatable excellence.

That helps explain why Apple products have so often felt more finished than everyone else’s. After coming up with the iPhone, the real achievement was making millions upon millions of iPhones at a global scale with remarkable consistency, made possible through process, coaching, and quality systems.

Tim Cook then industrialised that lesson. If Jobs made Apple magical, Cook made it durable.

Why this matters now

The reason this history feels newly relevant is that Apple is no longer being judged only by the standards that made it great in the device era. It is being judged against an AI wave that rewards speed, software capability, and boldness, areas where Apple has looked hesitant and behind.

That is where the Bloomberg profile of John Ternus becomes so useful. If Cook’s likely successor really is Ternus, then Apple may be signaling that it still believes its future will be won through hardware quality, tighter integration, and disciplined engineering execution. Ternus comes across as deeply “Apple” in the classic sense. He is an engineer, a careful operator, and someone credited with improving product quality after periods when thinness and elegance sometimes came at the expense of reliability and function.

That sounds like a strength, but it might also sound like a limit in the AI age. 

Bloomberg’s portrait suggests Ternus is respected, methodical, and increasingly central inside Apple. He has taken on broader responsibilities across hardware, design, robotics, marketing, and sustainability. He has also become more visible publicly, which feels like grooming by another name. But the profile also raises the harder question hanging over the company. Is Apple best served by a steady hand who protects its culture and sharpens its execution, or does this moment require someone more willing to disrupt the Apple playbook itself?

Quality is a moat, but maybe not the whole map

Quality still matters enormously at Apple. In fact, in a world full of rushed software, glitchy AI products, and overpromised devices, Apple’s seriousness about fit, finish, battery life, performance, and integration may become even more valuable. People still want products that work.

The problem is that quality alone may not generate the next era of growth. Apple’s AI struggles have made that plain. It can build powerful chips and polished devices, but much of the excitement in AI is happening in models, services, and cloud based systems being shaped by OpenAI, Google, Anthropic, and others. Apple’s traditional advantage was that it controlled the whole experience. In AI, control is harder to maintain and the center of gravity is shifting.

Apple’s next chapter may hinge on whether the operating philosophy that built the modern company can stretch far enough to meet a very different technological moment.

Apple’s first 50 years were built on learning that beautiful products require deep systems behind them. The next phase may test whether even the best system can adapt when the game itself is changing.

The Future of Work: Employee engagement continues to slide

For all the talk about AI, return to office policies, and whether younger workers are “checked out,” Gallup’s latest workplace research points to a simpler and more uncomfortable truth. A lot of people around the world feel less connected to work than they did a few years ago, and that slide is still going in the wrong direction.

In Gallup’s new State of the Global Workplace findings, global employee engagement fell again in 2025, marking a second straight year of decline. That matters more than it sounds. Engagement is one of those corporate words people roll their eyes at, but in practice it gets at something real: whether people feel involved in their work, energized by it, and committed to what they’re doing. When that slips, performance tends to slip with it. Gallup estimates that low engagement cost the world economy about $10 trillion in lost productivity last year, or roughly 9% of global GDP.

One of the clearest warnings in the data is that managers are struggling the most. That is especially important because managers shape how work actually feels day to day. They set expectations, give feedback, create clarity, and often determine whether change feels manageable or chaotic. Gallup found that much of the recent engagement decline has been driven by managers, whose engagement levels are falling closer to those of the people they lead. In South Asia, manager engagement dropped eight points in 2025, the sharpest fall of any region. One possible reason is organizational flattening, with companies cutting management layers and stretching remaining managers across wider teams. That may look efficient on a spreadsheet, but it can create a miserable experience for the people stuck trying to hold everything together.

This is especially relevant now because managers are also the people most likely to determine whether AI adoption actually works. Gallup’s U.S. research from early 2026 found that, aside from technical integration, the strongest predictor of whether employees use AI is whether their direct manager actively supports it. In other words, if companies want people to adapt to new tools, they cannot burn out the very people expected to lead the change.

The mood around jobs is also more complicated than the headline labor numbers often suggest. Globally, job market sentiment improved in 2025, though not evenly. The gains came mostly from workers in fully on site roles that are not remote capable. At the same time, optimism fell among remote workers and among people in remote capable jobs who are now fully back on site. That feels like a clue about where the anxiety is concentrated: knowledge work, white collar work, and roles where automation is starting to feel less abstract.

In the U.S., the picture looks notably worse. Gallup says the U.S. and Canada saw a ten point drop in job market optimism, and the region now ranks second to last globally. Separate Gallup data on U.S. workers shows just 28% say now is a good time to find a quality job, down sharply from the highs of 2022. More than half of workers are either actively looking or watching for new opportunities, yet many also feel stuck. That combination is one of the more striking themes in the data: people are restless, but not confident enough to move.

Younger workers seem to feel that tension most acutely. They are the most likely to be job hunting or job watching, and among the most pessimistic about their options. Many want better pay, clearer growth paths, and stronger leadership. A lot of them are reacting to workplaces that feel uncertain, expensive to leave, and hard to believe in.

The broader takeaway is that this is a management issue, a productivity issue, and (increasingly) a resilience issue. Companies can talk endlessly about transformation, but if managers are depleted and employees are detached, those plans start to wobble. The workplaces that handle the next few years best probably will not be the ones with the flashiest AI strategy. They will be the ones that remember people still need clarity, support, and a reason to care.

AI Insights

• An AI store owner hired humans: Andon Labs says an AI named Luna ran the hiring for a San Francisco retail shop, posting job ads, interviewing candidates, and choosing two full-time workers to help operate the store. The experiment offers a striking glimpse of a future where AI may manage human labor before it can fully replace it, raising immediate questions about transparency, power, and what workers should expect from a nonhuman boss.

• Stanford releases 2026 AI Index:  The index found AI adoption has surged to new speeds globally, but public trust remains at record lows and many entry-level workers are already losing jobs as firms plan further cuts. It also highlights a major gap between optimistic AI experts and skeptical public opinion, along with low U.S. adoption compared to several countries and rising concerns amid an increasingly anti-AI climate.

• Apple AI glasses details leaked: Apple’s upcoming smart glasses are being developed with an “instantly recognizable” design across at least four styles, using premium acetate materials and exploring multiple finishes, with a distinctive vertically oriented camera setup. Smart glasses seem to be a natural extension of Apple’s track record with iconic wearables like AirPods and Apple Watch.

The Supply Aside

📕 Read - Sam Altman may control our future - can he be trusted?

Ronan Farrow and Andrew Marantz’s New Yorker piece is a deeply reported look at why doubts about Sam Altman have endured inside and around OpenAI. Drawing on memos, depositions, and interviews with former insiders, including Ilya Sutskever, Dario Amodei, Mira Murati, and Helen Toner, it argues that concerns about Altman came from a broader pattern of alleged evasions, contradictions, and power plays, especially as OpenAI’s stated commitments to safety and accountability came under pressure from scale and competition.

What makes this such an interesting (albeit very long) read is what it reveals about the AI industry itself. The real issue is whether any governance structure can meaningfully restrain a leader who is highly persuasive, ambitious, and operating at the center of a technology with enormous consequences.

What Else I’m Reading

• Why women are winning most new jobs: NPR reports that women filled nearly all net new jobs over the past year, largely because hiring has been strongest in health care, a sector dominated by women. While women still face pay and promotion gaps, men are increasingly being left behind by job growth concentrated in caregiving and service roles they have been slower to enter.

• What an Ivy League education really gets you: The biggest advantage of elite colleges may not be prestige or classroom instruction, but immersion in a dense concentration of ambitious, high-performing peers. Students who attend an Ivy Plus school are 50% more likely to reach the top 1% of earnings by age 33 and earn about $101,000 more on average a decade after graduation than similar students who attend flagship public universities.

• The workers opting to retire instead of taking on AI: The WSJ reports that some older professionals are choosing to retire early rather than adapt to the disruption, retraining, and uncertainty tied to AI at work. The share of Americans over 55 in the workforce has fallen to 37.2%. The question is: are companies worried by the exodus of older workers, or are they happy to see the headcount reduced?

📺 Watch - Apple: The House That Tim Cook Built

Apple: The House That Tim Cook Built (2024) is a full-length documentary available free on YouTube. It tells the story of how Tim Cook went from operations roles at IBM and Compaq to becoming one of the key architects of Apple’s rise. What makes it worth watching is its focus on the part of Apple’s success people often overlook: the supply chain, manufacturing discipline, and operational decisions that helped transform the company from struggling to dominant. It’s especially good if you’re interested in how operational excellence (not just product vision) can build one of the world’s most valuable companies.

👂 Listen - The Knowledge Project: Connor Teskey

Representing the new generation of investment leaders, Teskey breaks down the 90% rule, the buildout of AI infrastructure, and what he sees ahead for the future of investing. As the CEO of one of the world’s largest investment firms, Teskey’s especially worth listening to on minimizing losses, making decisions without perfect information, and balancing downside protection with upside potential. He also shares lessons from his work with Bruce Flatt and discusses how Brookfield approaches risk, long-term growth, culture, mentorship, talent, and positioning.

🧠 Think: Get Ready for Y2Q

Everyone is panicking about AI tools finding software flaws. Fair enough. But Richard Clarke, America’s first cyber czar, argues that the bigger threat is something else entirely. Google quietly signaled that quantum computing capable of cracking much of today’s encryption may arrive far sooner than expected. Not decades away. More like two to three years. 

That is the real problem. Encryption is not some niche tool for spies and Signal addicts. It sits underneath digital certificates, browsers, emails, databases, sensors, and a huge share of the modern economy. If encryption fails, trust in the system fails with it. The fix is post-quantum encryption. The catch is scale. Replacing it everywhere will be a project at least as daunting as Y2K, and most organizations have not even started to scope it out yet.

The flashy AI story got the headlines. The quantum one may be the one that actually matters.

Charts of the Week

Quote of the Week

Tweet of the Week

The Final Chuckle

Thanks so much for reading. I’d love to know what you think about this issue and how I can make it more useful to you. If you have suggestions or topics you want to see me address, email me at [email protected]!

-- Naseem