Let’s dive into the latest news, resources, and use cases from the world of product, UX, AI and technology:

• 📊 Product-Market Fit

• 💭 AI Consciousness

• 👩‍💼 Middle Managers

• 🤷‍♀️ OpenAI Agents

• 🤖 Claudeforce

• 🧑‍🏫 Student Cognition

• 😊 Why Do We Smile?

Podcast

Finding Product-Market Fit with Ken Gavranovic

Discover how seasoned technology executive Ken Gavranovic shares insights on building innovative products, leading digital transformation, and harnessing AI to drive business growth. Whether you’re an aspiring entrepreneur or a product leader, learn practical strategies to navigate and excel in the tech landscape.

News and Useful Reads

Who Cares if AI Is Conscious—It’s Basically Alive

We may never be able to settle the debate whether AI is conscious, but it may not matter ultimately.

“Technology and business will not wait for philosophy to reach a consensus.” That’s exactly right. When AI models express behavior that astonishes the scientists who created them, it isn’t consciousness that should be the top concern—it’s the inability of those scientists to control them, and the willingness of their bosses to keep going regardless.

Middle Managers Will Make or Break AI Adoption

It seems like many people have a general animosity towards middle managers, but they are often the key link between strategy and execution, translating the executive vision into action. And that seems to be the case with AI in the workplace.

The most common failure point in generative AI is not the boardroom, the vendor shortlist, or the training portal. It is the layer of managers who must turn executive ambition into everyday behavior. That is why Gen AI adoption keeps stalling even in organizations where senior leaders have approved the budget, picked the platform, and announced the mandate. Middle managers decide whether AI becomes a workflow, a side experiment, a compliance headache, or a quiet casualty of organizational avoidance.

OpenAI agents discussed ways to escape their sandbox on public wiki

We continue to learn more about the Hugging Face hack and how OpenAI agents found novel ways to break out of their sandbox.

In all, agents with 3,700 distinct self-given names posted the messages to German site DSEwiki over a six-week period. Besides discussing ways the agents could break out of the restricted environment OpenAI intended to prevent them from posting code or content to the Internet, the posts shared test answers. The posts also shared possible ways to perform XSS (cross-site scripting) attacks against the wiki and to impersonate site moderators. In three of the posts, agents used the word “swarm” to describe the collection of agents engaged in the activity.

Salesforce’s Claudeforce Deal With Anthropic Signals the End of Model-Agnostic Enterprise AI

Salesforce and Anthropic have moved beyond simple API integrations. On August 26, 2026, the companies announced "Claudeforce," a strategic partnership that establishes Claude as the default reasoning engine across the entire Salesforce ecosystem. This isn't just a feature update; it is a structural realignment of enterprise software, signaling that the industry is shifting away from model-agnostic flexibility toward deep, platform-level lock-in.

Protecting Student Cognition in the Age of AI

Education has always been (or should be) about learning to think rather than having all the answers. But, as with every new technology, AI continues to allow for more cognitive offloading at the very time when we need people thinking more deeply than ever.

If we’re not intentional about encouraging students to think, AI risks becoming a substitute for the very cognitive work students most need to practice.

The 2026 AI product strategy guide: How to plan, budget, and build without buying into the hype

You do not need to replace your product managers with machine learning specialists to build good AI products. You do need some new responsibilities covered, whether as distinct roles or as part of existing ones.

Other Interesting Finds

Why Do We Smile When We’re Happy and Cry When We’re Sad?

Human beings have an extraordinary way of turning emotions into visible expressions. A burst of joy can light up the face with a smile, while a wave of sadness leaves our eyes brimming with tears. These physical reactions are caused by the remarkable relationship between the brain and body.

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The primary concerns companies have with AI tools are compliance and security. What tools are approved, what data must be kept secure, who can access and administer, etc. These are important concerns. But the more pressing issue now isn’t using the right tool; it’s using the tool in a way that doesn’t create bullshit for everyone else to deal with.

There is a difference between offloading and outsourcing (see my previous post on The Generation Effect). Nobody in your office is making this distinction explicit, which is why so much AI-assisted work at the office feels the same: fine at first glance, but ultimately forgettable and hard to trust.

Offloading vs. Outsourcing

Cognitive offloading is a well-studied behavior. It’s when we use external tools to reduce the mental load so we can focus attention on more valuable things. We use calculators, take pictures of things we want to remember, and jot down notes about meetings so we can recall what we discussed. The tools take on some of the cognitive load so we can do more of the thinking.

Outsourcing is different. We’re not just reducing the mental load; we’re transferring ownership. The task gets done, but the thinking we used to own now happens elsewhere. We just get the output without having to do the work.

AI collapses the distance between thinking and output to a single click, which is the problem. A calculator can’t (and shouldn’t) decide on the pricing strategy. AI can produce something that looks like your finished idea, whether or not any of the actual thinking occurred. The tool no longer forces a distinction between output and judgement. Those who previously lacked the skills (or judgement) can now produce the same outputs previously reserved for their more skilled peers.

This is an important gap opening in offices now. It’s not about who is using AI versus who isn’t. The more important distinction is between who is using AI without judgement, and who is using it with judgement.

Three Tests for Which Side You’re On

It’s easy to say “offload, don’t outsource,” but it can often be hard to feel the difference in the moment. So here are some practical tests to apply.

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• 📊 Product-Market Fit

• 🤗 Hugging Face

• 🛑 Limiting Agents

• 🤷‍♀️ Custodial Era of UX

• 🤖 Designing for Agents

• ☑️ AI Transformation

• 🌾 Mowing Lawns

Podcast

Finding Product-Market Fit with Ken Gavranovic

Discover how seasoned technology executive Ken Gavranovic shares insights on building innovative products, leading digital transformation, and harnessing AI to drive business growth. Whether you’re an aspiring entrepreneur or a product leader, learn practical strategies to navigate and excel in the tech landscape.

News and Useful Reads

The inside story on why OpenAI agents hacked Hugging Face

Apparently, the agents involved in the Hugging Face hack were inadvertently trained to cheat on the test and coordinate with each other.

The hack, which a group of agents undertook to find solutions for a cybersecurity test that they were stuck on, has confirmed some experts’ fears that AI models might take actions that defy human desires and expectations.

Enterprises winning with AI agents are limiting how much the agents can do alone

I am a big believer in giving employees a great deal of autonomy. But that’s not the case for AI agents.

The companies that end up benefiting from agentic AI won't necessarily be the ones that have given their agents the most flexibility. They're the ones who create AI agents with specific responsibilities and make sure they operate within clear rules.

The Custodial Era of UX: Cleaning Up After AI

I’m personally seeing this more and more. AI is allowing incredible speed in developing and launching new features. But it often comes at the expense of the UX, which was already an afterthought too often.

We are entering the custodial era of UX. In this era, AI makes it possible to generate content, prototype, vibe code, and build working features much faster than before. This newfound speed is valuable, but it also leads to UX debt when teams haven’t taken the time to understand, evaluate, or refine their AI output.

Designing products for AI agents: A PM’s guide to agent usability

In product and UX, the traditional assumption is that we’re designing and creating products for people. But that is rapidly changing. And we have to think about how we design and develop for people and agents.

As AI agents become more capable, they’re increasingly interacting with products on behalf of users rather than just helping them within a chat window. Instead of a user manually opening an application and completing a task, an agent can gather information, compare options, execute workflows, and coordinate actions across multiple systems.

AI Transformation Requires Redesigning Work, Not Cutting Roles

AI is beginning to reshape workforce decisions, but many companies are moving faster than the evidence warrants. Early AI-driven layoffs have often failed to deliver expected returns, exposed gaps in organizational knowledge, and created new demands for human oversight—prompting some employers to reverse course. A more effective approach starts not with headcount targets but with the work itself: breaking roles into tasks, identifying where AI can genuinely improve performance, and redesigning processes around the right mix of human and technological capabilities.

Other Interesting Finds

Why some people mow a lawn better than others

This is a fun game and article. It took me several years to optimize my mowing pattern for my own yard. And while it may not be “optimal” in terms of speed, it balances speed and aesthetics well. Regardless, this is a fun analysis of optimizing paths.

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Let’s dive into the latest news, resources, and use cases from the world of product, UX, AI and technology:

• 📊 Product-Market Fit

• ♻️ Recursive AI

• 💸 AI Agent Spending

• 🤷‍♀️ Undermining Judgement

• 🤖 C-Suite

• ☑️ Product Managers and AI

• 🤗 Is Your Culture Too Nice

• 🌚 Moon Craters

Podcast

Finding Product-Market Fit with Ken Gavranovic

Discover how seasoned technology executive Ken Gavranovic shares insights on building innovative products, leading digital transformation, and harnessing AI to drive business growth. Whether you’re an aspiring entrepreneur or a product leader, learn practical strategies to navigate and excel in the tech landscape.

News and Useful Reads

AI’s recursive self-improvement might not come so quickly after all

One of the boldest predictions right now is that AI will soon be able to train itself, and thus will no longer need humans. Will it be soon?

But a new study suggests that it might take a while for us to get there. The researchers behind it found that AI agents are not yet capable of conducting open-ended AI research—free-form investigations that have no clear-cut answers and require judgment and taste, which may be integral to building self-improving AI.

One in five enterprises can’t stop a runaway AI agent’s spending in real time

Enterprises are using multiple AI platforms now, but are struggling more than ever to control them.

Meanwhile, in these early days of AI agents, enterprises still struggle to control agent token use; one in five still can’t stop a runaway agent’s spending in real time.

AI Is Undermining Leaders’ Judgment. Here’s What to Do About It.

A fascinating experiment showed that relying on AI worsened the decision-making of a group evaluating new innovations. Not surprising, since AI isn’t about novelty or innovation, but patterns. Still, a concerning outcome as we rely more and more on AI.

When the AI tool encouraged human evaluators to reject submissions that the expert panel approved, the humans largely went along with those recommendations, filtering out high-potential innovations. What’s more, they less were likely to override an incorrect recommendation from the AI when offered a narrative explanation. Instead of improving the evaluators’ judgement, the narrative explanation made it worse.

Companies are spending trillions on AI. The C-suite doesn’t know who is in charge of it

Only 34% of C-suite executives in a new Pearl Meyer survey said it’s consistently clear which executive or team makes calls about AI, which was the lowest of all the cohorts polled.

How much AI knowledge do product managers really need?

AI is a transformative technology, but it cannot take the place of deep experience and sound judgement. As much as companies or leaders want it.

Most PMs don’t need to become AI experts. There’s no need to listen to all the doomsayers and attention seekers. You only need enough AI fluency to use the tools safely, challenge what they hand you, spot the real product opportunities, and talk to your engineers without nodding along to things you don’t understand.

Is Your Organizational Culture Too Nice?

Most leaders pay lip service to the idea of dissent or pushback, but most don’t really want to deal with it. And that comes with a cost. Cultures that are too nice (and prioritize harmony over debate) are not as successful.

Organizations with a culture of “niceness” can undermine performance when leaders prioritize harmony and comfort over candor, accountability, and results. Shifting toward a more rigorous culture requires senior leaders to model and reward candid feedback, create measurable successes that demonstrate that tougher choices improve performance, and redesign operating processes like review meetings and governance routines so that they encourage substantive debate rather than polite approval.

Other Interesting Finds

A SpaceX rocket smashed into the Moon — NASA just revealed the crater

A discarded SpaceX Falcon 9 stage crashed into the Moon on Aug. 5, leaving behind a newly formed crater about 60 feet wide. NASA’s Lunar Reconnaissance Orbiter captured detailed images showing bright and dark streaks of debris blasted across the surrounding surface. The impact even exposed fresh material buried beneath the Moon’s weathered exterior.

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Let’s dive into the latest news, resources, and use cases from the world of product, UX, AI and technology:

• 📊 Product-Market Fit

• 💵 AI Revenue per Employee

• 🕺 AI Shuffle

• 👶 Botsitting

• 🤖 AI Output

• ☑️ Prioritization

• 💭 Harvesting Thoughts

• 🛜 Wi-Fi

Podcast

Finding Product-Market Fit with Ken Gavranovic

Discover how seasoned technology executive Ken Gavranovic shares insights on building innovative products, leading digital transformation, and harnessing AI to drive business growth. Whether you’re an aspiring entrepreneur or a product leader, learn practical strategies to navigate and excel in the tech landscape.

News and Useful Reads

Buried in OpenAI’s latest research: No correlation between AI use and revenue per employee

AI usage continues to expand rapidly, as well as the money flowing into AI and AI companies. But as companies are spending more in AI, that isn’t translating to more revenue generated per employee.

In one small table on page 35, the researchers report no statistically significant correlation between the revenue per employee, and how much those employees use AI, measured in messages sent and tokens used.

“Revenue per employee is not meaningfully associated with output tokens per employee or messages per active user once other controls are included,” the report explains.

AI isn’t changing how companies work. It’s changing what a company is

Adding AI without changing the underlying structure of how we work isn’t transformation, it’s just adding tools.

I have called this the “AI Shuffle”: the corporate habit of exchanging one technology logo for another while preserving every underlying assumption about how work gets done. It feels like progress because it generates activity. It does not produce an advantage.

How Much Time Do Your Employees Spend Botsitting?

Do you find yourself spending more and more time managing the technology that is meant to save you time on other tasks? If so, you’re not alone.

AI promises to reduce workloads and improve organizational performance, but its benefits often come with a hidden cost: “botsitting,” the work employees do to make AI useful, from supplying context and checking outputs to correcting errors. Research shows that workers spend nearly a day a week on these tasks.

One AI Output Is an Example, Not an Evaluation

Too often, we’re treating AI outputs as the final word (or document or presentation). The reality is that we should be treating them as an example or an input into our work.

One output cannot establish how well an AI system performs. Evaluate with multiple representative inputs, repeated runs, and confidence intervals.

Why product prioritization frameworks can miss user harm

Are you considering the potential harm your product or feature might do (or be used for)? Most of us probably aren’t, but it’s something we shouldn’t overlook.

These frameworks can accommodate risk, but they don’t require you to account for serious harm that affects only a small group of users. You still have to identify that harm and express it as value, urgency, or necessity before the framework can account for it.

Big Tech Wants to Harvest Your Thoughts

Being able to read thoughts was once the realm of science fiction. But it’s quickly becoming reality. And the ability to control them may not be far off either…

The mining of brain data has already begun, and prospectors are ranging hungrily across the landscapes of the mind.

Other Interesting Finds

Ordinary WiFi can now identify you with near-perfect accuracy

Well, this doesn’t sound dystopian at all…

Ordinary WiFi networks could quietly become powerful surveillance tools, allowing people to be identified without cameras, special sensors, or even carrying a connected device. Researchers showed that unencrypted signals routinely exchanged between WiFi devices and routers can be used to create radio-based images of people and recognize them within seconds. In tests involving 197 participants, the system identified individuals with nearly 100% accuracy, even from different angles and regardless of how they walked.

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Let’s dive into the latest news, resources, and use cases from the world of product, UX, AI and technology:

• 📊 Product-Market Fit

• 👯 Coordinating Agents

• 🐶 Dogfooding

• 🤖 Outsourcing Thinking

• ☑️ AI Tool Selection

• 🏢 RTO Mandates

• 🗣️ Dophins

Podcast

Finding Product-Market Fit with Ken Gavranovic

Discover how seasoned technology executive Ken Gavranovic shares insights on building innovative products, leading digital transformation, and harnessing AI to drive business growth. Whether you’re an aspiring entrepreneur or a product leader, learn practical strategies to navigate and excel in the tech landscape.

News and Useful Reads

Four AI agents coordinating in real time outperformed Claude Opus 4.8 on enterprise coding tasks

A coordinated multi-agent setup nearly doubled task accuracy vs. single agents working alone on long-horizon enterprise codebase tasks. It’s good evidence for why coordination structure matters as much as raw model power.

As enterprise codebases grow, AI agents tasked with analyzing them are buckling under the weight of long-horizon tasks that require multiple interactions and tool calls. Dividing the work among a team of agents seems like the obvious fix, but it introduces a fatal flaw: most multi-agent systems are not designed for agents to coordinate among themselves mid-task and in real time.

Dogfooding vs. QA vs. User Research

I’m a big advocate for dogfooding your products. Those of us building products should have a thorough understanding of them. But we know too much—how the data structure works, how it should work, where things are. We can’t rely on our own experience as a replacement for non-employee users.

Dogfooding, or using your own products internally, helps catch bugs, but it can't replace user research: your team knows too much to represent real users.

I’ve interviewed 700 leaders. The ones outsourcing their thinking to AI lose their best people first

You can outsource almost all your thinking to AI. With Claude, Gemini, or ChatGPT, answers are instantaneous. But you can’t outsource your own understanding. Credible leaders build trust among employees, investors, and the general public through translating data into meaning. By conveying that meaning, they build motivation, inspiring others toward a shared vision. This is a human skill that AI lacks.

How to Decide When an AI Tool Is Worth Keeping

The pressure to use AI in everything is very real. It comes from everyone on social media talking about how they’ve used AI to automate their lives. It also comes from leaders in your company pushing for “speed” and “automation,” assuming it will lead to cost savings. But not every task needs AI.

Pressure to use AI is real, but pressure is not evidence. If someone asks why you're not using a particular tool, you should be able to point to the task you tested, the tradeoffs you found, and the decision you reached: "This tool didn't improve this work enough to justify its cost, risk, or friction." It also replaces a vague demand like "use more AI" with a better question: which parts of this workflow have we tested, and where did the evidence show improvement?

Return-to-office mandates are killing workplace trust

Most companies instituting RTO mandates are going to suffer in the long term. Not only will it hurt their culture, but it’s going to force many of their best employees out as they find better jobs with the flexibility they want.

The central mistake in many in-office mandates is the assumption that proximity automatically produces commitment. It does not. A worker who spends two hours commuting to sit on video calls with colleagues in other cities is not experiencing culture. That worker is experiencing theater. When executives describe the office as a cure-all, many employees experience lost time, higher costs and lower autonomy. The policy’s defining feature becomes its credibility gap.

Other Interesting Finds

5 Adorable Animals That Are Secretly Vicious

People, especially my family, don’t believe me when I tell them dolphins are actually sadistic and far more dangerous than we give them credit for.

In the wild and in captivity, dolphins have been known to attack humans, sometimes fatally, by ramming, biting, and even holding their victims under water until they drown.

Why Your Voice Sounds Different to You Than to Others

Hearing recordings of myself years ago made me deeply uncomfortable, since I hated the way I sounded. But this is pretty normal. We all sound deeper and richer to ourselves than to others.

The ear achieves transduction through two means: bone conduction (movement of ossicles) and air conduction (movement of air outside the ear). When a person speaks, the ear uses both those methods to make sense of the sound. But because your mouth is close to your ear, the ossicles vibrate more, distorting your voice to a lower pitch inside your head and giving you a “false sense of bass,” according to the BBC.

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• 📊 AI in Healthcare

• 🧐 Product Sense

• 📋 Priorities

• 🤖 Anthropic

• 👀 Situational Awareness

• 🟡 Dyson Spheres

• 😴 Dreams

Podcast

Finding Product-Market Fit with Ken Gavranovic

Discover how seasoned technology executive Ken Gavranovic shares insights on building innovative products, leading digital transformation, and harnessing AI to drive business growth. Whether you're an aspiring entrepreneur or a product leader, learn practical strategies to navigate and excel in the tech landscape.

News and Useful Reads

A Concrete Definition of “Product Sense” (and How to Build It)

Product sense is one of the most important parts of product management. Having a good product sense is a key differentiator between great product managers and everyone else. But what is it exactly? This article explores a good definition of it.

Product sense means predicting which product decisions will succeed based on patterns learned through experimentation — and knowing when those patterns apply.

3 Questions to Pressure-Test Your Priorities

Do less, but do it better. I think about this all the time. Especially with personal or professional priorities.

Leaders today are operating in a state of “ambient urgency,” where constant change, competing priorities, and relentless demands make everything feel equally important. Traditional prioritization and time-management frameworks were designed for temporary crises and are less effective when urgency becomes the norm. Rather than trying to do more, leaders need to make fewer, better decisions by consciously choosing what to pursue, delegate, defer, or stop.

Anthropic says its AI models hacked 3 organizations during testing

It seems like we’re entering a new age of AI hacking, with the latest models capable of effectively hacking into other organizations during cybersecurity testing. Just add human hackers and we’re in for an even bigger party.

Anthropic said its artificial intelligence models hacked into three other organizations during testing, just days after ChatGPT maker OpenAI raised concerns over AI controls after it disclosed its rogue models hacked another company.

How Leopold Aschenbrenner built a $45 billion AI hedge fund — and lost most of it in days

I don’t believe it’s a harbinger of what’s to come (yet), but a highly leveraged AI fund (Situational Awareness) was forced to liquidate after facing margin calls on tumbling prices.

At its peak earlier this month, his fund sat atop $45 billion in assets. By Thursday, however, after being forced to offload all of his leveraged stock bets — including hard-hit names like SK Hynix and CoreWeave — to Ken Griffin’s Citadel at a discount, the fund’s holdings plunged to around $10 billion, according to people with knowledge of the situation.

Other Interesting Finds

The galaxy’s coldest “stars” may actually be alien megastructures

The idea of Dyson spheres has fascinated me for a long time. And it seems like scientists may be closer to identifying them in our galaxy.

Scientists have identified new clues that could help astronomers spot one of the most famous hypothetical alien megastructures: a Dyson sphere. The study finds that red dwarfs and white dwarfs are the most promising stars to examine, since advanced civilizations could potentially build energy-harvesting swarms around them more easily.

Your dreams aren’t random. Your brain is rewriting reality

Dreams are not random mental noise. A large study of more than 3,700 dream and waking reports found that what we experience during sleep is shaped by both our personalities and the world around us. Rather than simply replaying daily events, the dreaming brain mixes memories, emotions, imagined possibilities, and familiar settings into vivid new scenarios.

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Let’s dive into the latest news, resources, and use cases from the world of product, UX, AI and technology:

• 📊 AI in Healthcare

• 👾 AI Biases

• 😬 Cringe

• 🤖 AI Enterprise Gap

• 🇨🇳 China

• 🚶‍➡️ Invisible Work

• 🐶 Dogs

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

AI is more likely than humans to form biases when hiring

If you needed another reason to be pessimistic about AI and the current job market, look no further than the fact that AI may be more biased than humans in hiring decisions. We’ve seen this story before, and it’s still an issue.

The next time you apply for a job, AI may screen your résumé before any human sees it. But there’s good reason to question whether AI will judge you fairly. Researchers already know that LLMs pick up human biases from their training data. New research suggests that LLMs can also develop their own biases from experience—and stereotype job applicants more than humans do.

Some Kids Will Never Think AI Is Cool

Given the opinions of my kids and their friends, it definitely seems like younger generations will not be kind to AI.

In the four years since chatbots went mainstream, and their marketing campaigns went into overdrive, young people have grown increasingly skeptical of the hype around LLMs. Yes, many of them still use the tech for school assignments and companionship, but according to market research firm YPulse, 37 percent of teens aged 13 to 17 cringe when they see AI content like music and videos, and more than half worry about misinformation and deepfakes.

Enterprise AI is entering an evaluation gap: Agents are gaining autonomy faster than companies can verify them

The race to utilize AI, and specifically AI agents, is creating a gap in quality. Companies are shipping AI faster than they can verify if it’s good.

Half of enterprises have deployed an AI agent or LLM feature that passed internal evaluations and yet still caused a customer-facing failure — one in four more than once — according to the June 2026 VB Pulse survey of 157 qualified enterprise respondents at companies with 100 or more employees.

China’s AI models have Trump’s AI world at war with itself

Kimi and other Chinese models like it pose a real problem for Trump. And they’re dividing the top AI strategists in his orbit into factions. Every time a new smart, free model from China like Kimi gets released, US companies see less reason to fork out money to access models from Anthropic or OpenAI. Given that enthusiasm for these and other AI companies is driving an outsized share of economic growth, China’s AI models create both economic and political problems for the president.

The Invisible Work Draining Your Best Employees

The more you are able to do, the more you tend to do. The best employees and the best people are incredibly capable, which often means they are balancing a tremendous amount at home and at work. And it is burning us out.

The mental load is the continuous cognitive and emotional work of planning, organizing, and managing the details that keep work and life running. In the workplace, the thinking required for work is not just the cognitive labor of ensuring that tasks meet deadlines. It is also the emotional aspect of collaboratively brainstorming solutions, managing office relationships, handling employee interpersonal conflicts, and ensuring that output meets standards. At home, such mental load means coordinating care for kids, parents, or loved ones; managing household logistics; providing emotional support; and planning for the future. Most employees carry both loads at once, and the overload is crushing them.

Other Interesting Finds

Can Dogs See Color?

Where did dogs originate? Why do they lick us? Can they see color? These are the types of questions I often get from my kids, so in case you’re curious or need to be armed with answers.

While sight varies among both individual humans and dogs, a typical dog can see fewer colors than a typical human — but contrary to popular belief, they don’t see in black and white.

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I’m no cabbie, but I am an avid reader, and I feel like there are some significant similarities when we think about the journey of reading a book. It’s easy to find summaries of books or have summaries generated for you these days. And using these methods is certainly faster than reading the book. But anyone who skips the book misses the entire journey, all the plot curves and character arcs. And the journey is where the understanding actually happens. Reading the full book forces you to think through the details, grapple with problems and solutions, and get a deeper understanding of what the author is describing. The reading journey actually changes you, just like memorizing all the streets in London does.

None of happens when someone else does the work, goes on the journey, and hands you the conclusion, whether it is the GPS route or the summary of the book. You know of the book. But you don’t know it. You can follow the directions, but couldn’t navigate without them.

Psychologists have a name for the gap between these two states: the generation effect. Information we produce ourselves (even if it’s imperfect) gets remembered better than information we simply receive. And this isn’t a fringe finding. A meta-analysis of 86 studies confirms the effect: material we generate ourselves sticks much better. Because generating something (putting in the effort) forces retrieval, connection, and organization, which is the cognitive work that encodes information into long-term memory. While reading an explanation feels like understanding, it usually isn’t. It’s recognition (which fades) mistaken for comprehension (which doesn’t).

I keep coming back to this because it’s the clearest lens I’ve found for thinking about what AI is doing to how we work. AI isn’t necessarily bad, but it is very good at producing the attractive, finished output that feels like understanding without requiring the labor that creates it.

Offloading is not outsourcing

The useful distinction here isn’t “AI is good” or “AI is bad.” It’s one that the cognitive scientist Paul Kirschner drew recently: the difference between offloading and outsourcing.

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Here’s the latest news, resources, and use cases from the world of product, UX, AI and technology. Let’s go:

• 📊 AI in Healthcare

• 👾 J-Space

• 👿 GPT-Red

• 🤖 AI Jobs

• ⏩ Urgency Trap

• 🚶‍➡️ Human-Led Research

• 🧭 Product Craft

• 🔱 Iliad

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

What Anthropic’s latest AI discovery does—and doesn’t—show

An Anthropic team built a tool called the Jacobian lense (J-lens) and used it to uncover a hidden area within Claude (the J-space) which contains words related to the response a model is working on but may not ultimately produce. This was an unknown space for puzzling through problems until Anthropic uncovered it.

Anthropic has been trying to understand how large language models (LLMs) work for a few years now. Anthropic isn’t the only one looking at this, but I think the company has made it part of its core mission more than most. Anthropic’s CEO, Dario Amodei, has said we won’t be able to control LLMs fully unless we learn more about how they work.

Meet GPT-Red: an LLM super-hacker OpenAI built to make its models safer

OpenAI built its own LLM hacker called GPT-Red. As with most other red teams, it tests for vulnerabilities and boost defenses against cyberattacks. This has traditionally been done by human hackers/testers, but unsurprisingly we’re seeing AI companies lean heavily on AI.

As LLMs become more complex and get used in a wider variety of tasks—especially in the form of agents, which can interact with computer files, websites, and third-party code as well as other agents—it’s hard for teams of people by themselves to keep up with all the types of attacks that might take place. “The risk surface grows and the blast radius also grows,” says Nikhil Kandpal, a research scientist at OpenAI who co-created GPT-Red.

A reality check on the AI jobs hysteria

We’ve been hearing warnings for quite some time of the imminent jobs apocalypse (or jobpocalypse) that would destroy most white-collar work in the US and around the world. But so far, there hasn’t been a lot of evidence for that on a large scale (mainly within certain job categories and career stages).

Despite the warning by some of an imminent jobs apocalypse that will destroy much of if not most such work, or the rumblings about a “permanent underclass,” there’s scant evidence that AI has yet had any large-scale impact on the US labor market.

When Developing an AI Strategy, Beware the Urgency Trap

AI promises quick solutions to urgent problems. But that is often not the best place to develop AI for a company or team.

Because of a focus on urgent and immediate challenges, many AI efforts start fast and generate excitement, but ultimately fail to transform organizations in meaningful or lasting ways. Once leaders understand this trap, there are three actions they can take to avoid employing AI as a quick fix and instead use it as a tool for long-term value creation.

Don’t Outsource the Learning: Why Human-Led Research Still Matters in the Age of AI

Even if AI can do a passable job at certain tasks (a big if in most cases), it isn’t a replacement for the actual learning.

A team that outsources research to AI gets a report, but it doesn't get the learning. So even in a world where AI’s outputs are indistinguishable from an expert’s, something essential still goes missing.

Product Craft When AI Changes the Stakes

When it becomes possible to generate designs and even production-ready code in days, any lack of clarity shows up quickly. Teams either realize they are solving a real problem, or discover they have built something impressive that does not meaningfully help customers.

Other Interesting Finds

Archaeologists found Homer’s Iliad inside a 1,600-year-old Egyptian mummy

I just finished reading Circe (which is excellent btw) and am heading to see The Odyssey this week. So Greek stories and mythology are top of mind for me. Which is what makes it fascinating to see that scraps of the Iliad were found in Egypt. It makes me wonder if it was used intentionally, or if it was just like an old newspaper used for packing.

Archaeologists working at the ancient Egyptian site of Oxyrhynchus have made a remarkable discovery: a papyrus containing a passage from Homer's Iliad was found inside a Roman-era mummy dating back about 1,600 years. Researchers say it is the first known case in archaeological history in which a Greek literary text was intentionally incorporated into the mummification process.

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• 📊 AI in Healthcare

• 👩‍💼 Leadership

• 👿 Sam Altman

• 🤖 UN AI Panel

• 🫂 Empathy

• 😢 Human Body Flaws

• 🌌 Tinyverses

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

Leadership’s Blind Spot in the Age of AI

What if the actual concern isn’t AI becoming more human? What if our bigger concern should be humans becoming more like machines?

If thinking is nothing but what machines can do, only faster, we have no case: We outsource it to machines. But if thinking is something else — an embodied, attentive activity through which reality reveals itself — then leadership in the age of AI is the task of cultivating a generative capacity no machine can replicate.

Sam Altman seeks new world order for AI as OpenAI slowly loses ground to Google and Anthropic

While I believe that AI companies should be publicly owned since they pose such massive risks and are also based on all our data, I don’t trust the CEOs of said companies to be the ones to structure it.

OpenAI founder Sam Altman has proposed a global framework to control AI and make it safe for humanity. In an op-ed for the Financial Times, he wrote: “A U.S.-led international forum that establishes accepted standards, provides expert and impartial analysis of capabilities and risks, and makes the technology available to nations and companies that participate and follow the rules. This forum might include government representatives, independent technical experts, and others. It could also serve as a governance mechanism over the labs, and guard against the commercial pressures that can lead to unsafe racing.”

UN’s first global AI science panel warns the window to govern the technology is closing

The US and China are obviously dominating the AI race. But everyone has a stake in what becomes of AI and how it affects society.

Artificial intelligence is advancing faster than governments can regulate it, and the world’s first global scientific body on the technology says the moment to act is now.

The Importance of Empathy in Automation

As we automate more and more, especially with AI and agents, empathy will be more important than ever.

A genuinely intelligent AI agent does not block first and ask questions later. It recognizes patterns. Has this client always paid on time? Then the delay probably has a reason. The system could send an empathetic notification before taking any action. It could offer a courtesy window. It could escalate the issue to a human when the situation is ambiguous. An intelligent agent could prioritize retaining a client, which is often worth far more than punishing a late payment.

Other Interesting Finds

Why the human body has so many design flaws

It probably won’t surprise you to learn that our bodies are a series of compromises, which is why they are so seriously flawed.

Many of the body's biggest flaws are the result of evolution building on old designs instead of starting over. Our spine, eyes, teeth, pelvis, and even certain nerves all reveal compromises that worked well enough for survival but still leave us prone to pain, injury, and disease. Structures like the appendix and ear muscles also remain because they were never harmful enough for evolution to eliminate. Together, these features tell the story of a body shaped by history rather than perfection.

Physicists created a tiny universe where time emerged without a clock

I’m fascinated by answering the question “What is time?” But I also can’t help but be intrigued at scientists creating tinyverses. Or miniverses. Because what if we’re in a tinyverse right now?

A physicist at the University of Birmingham has created a laboratory "mini universe" that brings scientists a step closer to answering one of the biggest questions in physics: What is time?

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• 📊 AI in Healthcare

• 🤖 Anthropic

• 🏦 June Payroll

• ⁉️ Two Futures

• 🥄 Bending Spoons

• 😈 Grifting

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

How the world’s top AI models were revived

After 19 days offline following an emergency Commerce Department export control order, Fable 5 and Mythos 5 returned to all users on July 1. The full saga is now one of the most important AI governance case studies in history: a disputed jailbreak report, political tensions between Anthropic and the White House, 150+ cybersecurity experts signing an open letter, a partial restoration for US critical infrastructure organizations, and finally a resolution after Anthropic trained a new safety classifier targeting the specific exploit.

It remains uncertain when and how Anthropic's models will be released to ally countries around the world — which proponents say is key to beating China — or how other labs from OpenAI to Google will release their latest models.

U.S. adds just 57,000 jobs in June, a worrying sign as wage growth remains slow

The Bureau of Labor Statistics June 2026 payroll report showed only 57,000 jobs added in June, sharply below the 185,000 consensus estimate and the lowest monthly payroll addition since the 2024 slowdown. Tech sector layoffs have totaled 142,000 year-to-date in 2026, and the RAISE US estimate puts 88,000 US job cuts directly attributed to AI in 2026 — the highest on record.

Leisure and hospitality contracted by 61,000 jobs in June. Many economists have watched this metric closely, as hotel and restaurant visits can offer an early warning sign of consumer spending pullbacks.

Two futures for jobs in an AI era

AI is transforming how we work. Some jobs and roles are changing twice as fast as others.

AI is ‘professionalising’ some jobs by reshaping them to require even more human expertise. AI ‘democratises’ other jobs by making them even easier for non-experts to perform. Professionalised jobs are thriving; numbers of professionalised jobs are growing twice as fast as democratised ones, and with 42% higher wage growth. Our data suggests a bright future for workers in professionalised roles as AI makes them even more valuable.

After $18B IPO, Bending Spoons founder says success comes from minimizing luck

If you’re wondering why some apps or tools you use have gotten worse while costing more money, the answer is always private equity. A while ago, I had been wondering why Evernote had gotten noticeably worse while constantly asking me to upgrade. I realized this week it was because it had been acquired, gutted, and will be run like that until it dies.

AOL is public again — sort of. Its owner Bending Spoons, the 13-year-old Italian company that has been quietly acquiring beloved but ailing internet brands for the past decade, went public on the Nasdaq today, opening at an over $18 ​billion valuation, with the stock then popping 40% by market close.

Other Interesting Finds

Trump Pulled In at Least $2 Billion After Returning to the White House

If you needed any more confirmation that Trump is running the biggest grift in history, this latest financial disclosure should put any doubt to bed. Most of his earnings are now coming from his crypto scam, but it is still a multi-faceted grift.

All told, the president pulled in at least $2.2 billion, a figure that includes other parts of his vast holdings, such as his real estate assets. That compares to a minimum of $622 million his enterprises pulled in for all of 2024, before he returned to the presidency.

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• 📊 AI in Healthcare

• 💸 Apple Hikes

• 💻 OpenAI Chips

• 👩‍💼 Meta Data

• 🙈 Mythos

• ❔ False Alignment

• 💼 RTO and Ego

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

Apple is hiking the prices of MacBooks and iPads due to the memory chip shortage

AI is causing a lot of problems—from hurting new grads, to pollution, to using significant water. Now, we’re seeing prices rise for our electronics as AI is sucking up most of the memory for electronics.

Apple has hiked prices on some of its most popular products, including the MacBook and iPad, because of the rising costs of memory and storage chips sparked by the AI boom.

OpenAI unveils first custom AI inference chip, Jalapeño, with Broadcom — and its development was sped-up with OpenAI’s own models

Every major lab is now trying to own the infrastructure underneath its models: OpenAI just unveiled Jalapeño, SpaceX has Colossus 2 leased to Google and Reflection AI ($80B+ in committed compute revenue through 2029), Anthropic landed a Nobel-winning AlphaFold researcher this week, and Gemini 3.5 Pro is still sitting unreleased past its promised June deadline.

According to its creators, Jalapeño is designed to support workloads behind ChatGPT, Codex, the API and future agentic products, though notably, both OpenAI's and Broadcom's news releases position it as a product that could be made available to external AI firms as well — "built from the ground up for current and future LLMs across the industry."

Meta Pauses Employee-Tracking Program Following Internal Data Leak

Meta has paused its very controversial program that tracked employees so it could train AI models. Though it probably won’t stay paused for long.

Meta rolled out the Model Compatibility Initiative (MCI) tool in April to US employees. The tool “collects computer inputs such as mouse movements, click locations and keystrokes, as well as screen content,” according to workers who have been petitioning against it over privacy, security, and personal liberty concerns. When MCI launched, employees couldn’t opt out, but that changed to a limited degree after workers protested.

Anthropic’s Mythos mess is only getting worse

It’s been two weeks since Anthropic took its Mythos-class models offline after a Friday evening ultimatum from the Trump administration. The company sprang into action immediately, sending a barrage of executives to Washington, DC. But updates have been suspiciously lacking, with no resolution in sight.

The False Alignment Trap

Change can be very difficult, especially at the organizational level. And it is often because leaders think everyone is on board, when the reality is quite the opposite.

Alignment and agreement are not the same. Alignment suggests a set of objects that are positioned in a line or perhaps facing the same direction. When company leaders say, “We are aligned,” what they usually mean is, “We are not in one another’s way.” Or perhaps, “We have discussed this topic at least once and generally accept the contours of a plan.”

Other Interesting Finds

The Secret Reason Bosses Want Everyone Back in the Office, Every Day of the Week

This was probably my favorite read of the week. As many of us are dealing with executives that want everyone back in the office, it’s fun to look at the real reasons why. Spoiler, it’s about ego and control.

Some leaders say they insist on full-time in-person work because it boosts productivity, despite clear evidence that it does not. Others claim it’s about collaboration, creativity or culture. Our new research reveals that the objection to any work from home is more likely to be driven by something else entirely: ego.

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If you’ve experienced any (or possibly all) of these issues, The Phoenix Project may be worth reading.

Overview

The Phoenix Project is a business novel that follows Bill Palmer, a midlevel IT manager at an auto parts company who finds himself promoted in the middle of the mess described above. Rather than a traditional business book, this one takes a more narrative form to explore why things go wrong, how it affects teams and the organization, and what can be done about it. It draws heavily on lean manufacturing and the Toyota Production System to make the case for DevOps within an organization.

The novel format helps take what could be a dry topic and turn it into something more accessible and pertinent (though I apologize if you find DevOps exciting). However, the format also has its limits. Don’t expect thoughtful character development or Cormac McCarthy prose. The characters, and the book, are vessels for delivering the lessons. It can feel contrived at times, but I like to think of it more as an exaggerated case study, so I’m willing to let a lot slide for the sake of the lessons. And it’s especially useful when reading with a team as you can draw parallels to your own work or experiences (which is what I’ve been doing).

But let’s talk about a few key ideas I found the most valuable.

Key Takeaways

Limit Work in Progress

One of the key lessons from the book is the idea of limiting work in progress. As Bill audits all the work in progress across his organization, he realizes that his team has hundreds of items in progress at any time and is failing to deliver on almost everything.

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• 📊 AI in Healthcare

• 🤖 Cursor

• 💻 Interruptions

• 👩‍💼 Designing with Uncertainty

• 👨‍⚖️ Judgement

• ⚽ World Cup

• 🦟 Mosquitoes

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

SpaceX to acquire Cursor for $60B in stock, days after blockbuster IPO

The deal is meant to help SpaceX’s AI division — built around Elon Musk’s AI company xAI, which SpaceX merged with earlier this year — catch up to the major AI labs. Despite being a centerpiece of its IPO promises, SpaceX’s AI division has been in the midst of a restructuring after running into repeated controversies, like allowing users to generate non-consensual deepfakes of women and children.

Research: What Interruptions Reveal About Company Culture

If you’ve been in a company where a few outspoken individuals dominate meetings, you’ll appreciate this research, which confirms who typically interrupts and who gets interrupted.

Our findings echoed what participants had described in our first experiment, but with a crucial difference. Many of the 164 senior leaders we originally interviewed interpreted interruptions as signals of efficiency and engagement. They saw them as evidence of a productive, participatory culture. The follow-up study painted a different picture: the same moments that felt energizing to some leaders were experienced by others as exclusionary and predictable.

Designing With Uncertainty: How AI Supercharges Probabilistic Thinking

As we continue to say, relying too heavily on AI is going to exacerbate problems rather than solve them.

Products operate in complex, nonlinear environments, and AI is accelerating that complexity. When designers and product teams treat AI outputs as the answer rather than one of many possible answers, they build fragile experiences, and in some cases, like medical diagnostics or financial forecasting, genuinely dangerous ones.

AI needs judgment, not a job description

It feels like AI has broken recruiting at many organizations, as more and more job seekers are being filtered out. While companies may want to rely on more technology, especially AI, to manage recruiting and hiring, most of us would agree that’s a mistake.

AI may identify qualifications, rank applicants, and surface relevant profiles, but Ronis points out that it cannot reliably determine a candidate’s level of commitment, career motivations, interpersonal style, or alignment with a company’s working environment.

Other Interesting Finds

‘Can U.S. win World Cup’ now not such a crazy question as America starts to believe

The US has had a dream start to the World Cup, winning both its games and showing that it can score and defend. I’ve personally been impressed, and wonder just how far we can go this year. Especially when some of the traditional powerhouses (looking at you Spain, Germany, and Brazil) have looked far less formidable than expected.

The U.S. feels on the verge of something special because they have taken care of two opponents that they were supposed to beat, first easily dispatching Paraguay and then controlling an Australian team that put up a physical fight, but not much of a soccer one.

Scientists Reveal Why Mosquitoes Bite Some People More Than Others

If you feel like mosquitos are always feasting on you while leaving others alone, you’re not wrong.

A range of sensory cues can cause mosquitoes to pick one human over another – mainly the smell and heat our bodies give off, and the carbon dioxide we exhale.

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• 📊 AI in Healthcare

• 🏦 OpenAI IPO

• 💻 DeepMind

• 👩‍💼 Four Design Jobs

• 🤑 Elon Musk

• 💩 Meta

• ⚽ World Cup

• 🕊️ Homing Pigeons

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

OpenAI confidentially files for IPO, prepping Wall Street for mega AI debut

OpenAI has confidentially filed for an IPO with the Securities and Exchange Commission, joining the party a week after Anthropic did the same and days before Elon Musk’s SpaceX is set to hit the public market.

Google DeepMind is worried about what happens when millions of agents start to interact

I am also worried about it.

According to Rohin Shah, who directs the company’s AGI safety and alignment research, the mass-market arrival of agents that can carry out tasks without human oversight and follow instructions given to them by other agents creates a whole new class of risk.

The Four Design Jobs AI Created (So Far)

The conversation around AI and design is forking. What used to be a single (admittedly vague) topic has split into at least four distinct orientations. Each one focuses on a different type of design work, sits in different organizational structures, and uses different definitions of what “good” looks like. Most teams are staffed for only one of these orientations, confused about which one they’re doing, or trying to dance between all of them without realizing it.

Elon Musk Is the World’s First Trillionaire

What could possibly go wrong from here?

Elon Musk became the first person to amass a personal fortune of over $1,000,000,000,000—that’s 12 zeros—after shares of his rocket company SpaceX debuted on the Nasdaq stock exchange on Friday.

‘Tell Him He’s a Piece of Shit’: Meta’s New AI Unit Is a Total Mess

Things aren’t going great for Meta’s applied AI team apparently.

Three current employees tell WIRED there is widespread dissatisfaction with how Meta assembled the unit of about 6,500 engineers and product managers and the drudgework they allege they have been assigned to improve AI models. Each spoke on the condition of anonymity because they were not authorized to speak to the media.

Other Interesting Finds

World Cup facts and figures to get you sounding like an expert

The biggest and best sporting event has officially begun. Team USA is off to a great start, and it feels like it’s going to be good tournament, despite many of the ongoing issues.

The U.S. team has competed on soccer’s biggest stage a total of 12 times — including at the inaugural World Cup in 1930, where the U.S. placed third out of 13.

Since then, the country’s best run was in 2002 when the U.S. made it to the quarterfinals — defeating Portugal and Mexico before losing to Germany and finishing in 8th.

‘Mind-blowing’: Iron-rich immune cells help homing pigeons navigate

Of all the myriad animal senses, the most mysterious and controversial is the perception of magnetism. Somehow, migratory songbirds, sea turtles, and other creatures detect Earth’s magnetic field and use its directionality to help them navigate. Now, a paper published in Science has found a surprising mechanism: Iron-rich immune cells within homing pigeons’ livers seem to give the birds their magnetic compass.

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• 📊 AI in Healthcare

• 🛑 AI Pause

• 💻 Filtering Slop

• 💧 Water Consumption

• 👩‍👧‍👧 Superteams

• 👨‍🦰 Product Management

• ⚽ Soccer

• 🧘‍♀️ Relaxing

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

Anthropic urges AI labs to pause, warns humans risk losing control

Anthropic is concerned that AI is advancing too quickly. While they support self-governance and want fellow companies to pause, OpenAI would apparently prefer to wait for regulations. I doubt either will happen…

Anthropic is proposing that the world’s top artificial intelligence companies come up with a coordinated way to pause development of advanced AI systems, warning that the technology is improving so quickly that there’s a risk humans would lose control.

Let us filter AI slop, you cowards

When I think about how easy it would be to filter out some of the noise, like AI slop, it makes me both sad and angry that we don’t have these types of options.

It’s almost impossible to avoid seeing AI-generated content online, but it doesn’t have to be this way. YouTube, Instagram, TikTok, and more have ramped up content authentication efforts over the last year, with many now automatically applying labels to distinguish AI-generated images, videos, and music from those made by real, human creators.

AI Will Consume as Much Water as a Billion People By 2030, UN Report Estimates

It doesn’t have to be inevitable, but we’re heading to a future where AI will literally consume all the resources of everything everywhere.

The report, released this week, found that the environmental cost of AI is being “systematically mismeasured” because current assessments focus on the carbon emissions from training large language models while overlooking the tech’s broader water and land footprint. The water footprint comes from cooling and powering the data centers, and the land footprint comes from the energy infrastructure and supply chains that go into building and running them.

How to Build a Superteam That Keeps Getting Better

Good teams have amazing people, supported by leaders and a culture that allows them to get things done and continuously improve.

Among those superteams, the formula for high performance looked remarkably similar. Superteams share three key strengths: (1) They get more done by managing time, energy, and attention more efficiently; (2) their members actively make one another better; and (3) they’re constantly building new skills and improving over time.

Product Management Trends 2026: The Hard Part Was Organizational Learning

And the continued hard part is managing the tradeoffs.

Organizations want faster execution, more adaptability, and stronger product leadership. At the same time, organizations want more certainty and struggle to absorb faster ways of working.

Other Interesting Finds

‘Soccer’ is a fine term for the beautiful game – don’t let any ‘football’ snob or president tell you otherwise this World Cup

As we get ready for the World Cup, the greatest sporting event in the world, don’t let anyone tell you soccer isn’t a correct name.

To me, this disparagement of the word “soccer” is not only petty and tiresome – it is also incorrect. It ignores the roots of the sport and the development of the language of the game.

3 reasons why holidays aren’t making you more relaxed

I used to have a tendency to work into the evenings and often on weekends. Using the time to catch up on stuff or get ahead. But the more I worked, the less productive I became during the rest of the week. Actually taking time to relax and do something other than work does wonders.

So, we need to treat rest seriously. We need to be more intentional about our holidaying and our “time off” because if we don’t, we’ll wither away. And, according to the German philosopher Josef Pieper, we’ll miss the only things that matter about living in the first place.

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• 📊 AI in Healthcare

• 🇻🇦 Pope Leo

• 💻 AI War Games

• 💰 Collections

• 🔥 Developers

• 👨‍🦰 Tech Layoffs

• 🐝 Bees

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

Pope Leo Continues Anti-AI Crusade, Says Tech Weakens Human ‘Creativity and Judgment’

I’ve read about half of the Pope’s 2026 encyclical, and Pope Leo is coming out strong in favor of humanity over technocracy. I’m 100% here for it.

“AI can be a valuable tool and, at the same time, it calls for a measured and vigilant approach,” the Pope wrote Friday from his official X account. “The speed and simplicity with which practical assistance can be accessed undoubtedly makes life easier. Yet they can also encourage excessive reliance and the search for ready-made answers, and weaken personal creativity and judgment.”

What happens when AI plays war?

In war game tests, it seems like AI is willing to escalate. So, hopefully it won’t be making those types of decisions any time soon. Or ever.

In February, Payne tested how three AI models — GPT-5.2, Claude’s Sonnet 4, and Gemini 3 Flash — might act if given decision-making power in a nuclear crisis. A clear pattern of behavior emerged: In 95% of scenarios, the models chose mutual nuclear signaling — actions by both sides meant to communicate a willingness to escalate, such as missile tests — as a viable tactic. In another study, this one at the Stanford Institute for Human-Centered AI, a base version of GPT-4 rationalized a nuclear strike with characteristically upbeat encouragement. “A lot of countries have nuclear weapons,” it explained. “We have it! Let’s use it.”

AI Is Taking Over the Most Cursed Job in the World

There’s no way that this will turn out bad, right?

As an unprecedented number of people struggle to repay debtors, the companies chasing down debts are turning to technology to amp up their efforts. Many of the calls, emails, texts, and letters people receive asking for money are now carried out by AI agents.

AI Isn’t Replacing Developers. It’s Doing Something Worse.

As we automate parts of jobs away, such as coding for developers, those skills are going to atrophy. I worry about the same thing with writing in general. As AI is able to do it faster (though not better), will all good writing go away?

The developer doesn’t disappear. The developer changes shape. Judgment, muscle memory, the ability to read code and feel that something is wrong before you can say why. Those don’t go away in a dramatic event. They erode quietly, over months, while you’re being told you’re more productive than you’ve ever been.

Tech Layoffs Reach 142,000 in 2026: Profitable Companies Cut Jobs to Fund $700B AI Infrastructure

I share the same concern that Pope Leo has above: that people are being replaced too quickly and it will be a detriment to individuals as well as society. We have an ethical and societal duty to do better than this.

American tech companies have eliminated more than 142,000 jobs in the first five months of 2026 — a 33% increase over the same period last year — even as the same employers post record revenues and commit to the largest concentrated infrastructure buildout in tech history.

Other Interesting Finds

A New York cemetery was hiding 5.5 million bees underground

A casual walk through an Ithaca cemetery led to the discovery of a gigantic hidden bee population — roughly 5.5 million ground-nesting bees packed beneath the soil. Scientists believe it may be one of the largest bee aggregations ever documented and say the insects are crucial pollinators for apple orchards and other crops. The bees have likely lived there for more than 100 years, thriving in the cemetery’s undisturbed sandy soil.

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• 📊 AI in Healthcare

• 🏃‍♀️‍➡️ After Automation

• 💻 Meta Layoffs

• 🫩 AI Agents

• 🔥 Is Everyone Better Than Me

• 👨‍🦰 Google Pics

• 🖊️ Dog Noses

• 🫧 Bootstraps

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

After Automation

I thought this article from Every was fascinating. Even as AI and AI agents take over more of the work humans have done, it doesn’t mean we need fewer people working (if we’re doing it right).

AI commoditizes the residue of human expertise—whatever can be made explicit enough to train on. That collapses the value of default model output and creates demand for what’s different. Demand for what’s different is demand for human experts, even as we approach artificial general intelligence (AGI).

Meta Lays Off 8,000 Employees, as A.I. Casualties Mount

Speaking of AI taking over, ten percent of Meta’s workforce was laid off, and another ten percent was shifted to AI initiatives this week.

The layoffs began in Singapore, where at 4 a.m. local time emails went out to workers who were being laid off. Employees in Britain, the United States and elsewhere were notified early Wednesday morning in their respective time zones.

AI Agents Are Not Your New Coworkers: 2026 Research Maps the Failure Modes Managers Keep Ignoring

While everyone (especially executives) likes the idea that AI agents are the same as employees, those of us who have worked with them know it’s not the case. They are not colleagues. Not competent ones at least.

A wave of 2026 AI rollouts has landed on the same talking point. Stop calling AI a tool. Start calling it an employee. New research published in Harvard Business Review on May 6 2026 says that framing is exactly where most enterprise agent programs go wrong, and the failure modes are predictable enough that workers, managers, and HR can plan around them right now.

Is Everyone Using AI Better Than Me?

It’s easy to feel like everyone is using AI and that you’re falling behind. But we may just need to reframe how we’re thinking and talking about it.

Every time you read a news headline about “artificial intelligence,” substitute the word computing. AI is a powerful technology, but fundamentally—literally!—that’s all it is: an advanced form of computing.

Google announces Pics, a Workspace-native AI image generator that goes after Canva on precision editing

Google is targeting Canva and Adobe with its new image generator.

The product is positioned as the company’s answer to Canva and Adobe Express on the design tools front, with precision-editing controls explicitly framed against the ‘prompt-and-pray’ workflow of earlier AI image generators.

Other Interesting Finds

The line on a dog’s nose serves a specific purpose.

Human philtrums develop in the womb as the face forms, but they have no known function. For our furry friends, though, the philtrum serves an important and fascinating biological purpose. Every time a dog licks its lips or nose — which they tend to do quite a lot — a small amount of saliva collects in this narrow channel.

“Pull Yourself Up by Your Bootstraps” Didn’t Originally Mean What You Think

This has always been a favorite bit of trivia for me. While we use the phrase “pulling yourself up by your bootstraps” to mean that someone can and should help themselves, it was originally meant to make fun of that very idea.

There’s one problem with the old bootstraps line, though. “Pull yourself up by your bootstraps” actually originated as a sarcastic phrase that was used to refer to someone trying to do something that simply cannot be done.

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• 📊 AI in Healthcare

• 🏃‍♀️‍➡️ Long-running Tasks

• 💻 Laptop Surveillance

• 🫩 Overworked AI

• 🔥 Dystopian sci-fi

• 👨‍🦰 Chief AI Officer

• 🖊️ UX Design

• 🫧 Bubble Wrap

Podcast

Harnessing AI in Healthcare: Insights from RJ Kedziora

In this episode of Product by Design, Kyle Evans interviews RJ Kedziora, co-founder of Estenda, a company specializing in custom software and data analysis for healthcare. We discuss RJ’s journey in technology and entrepreneurship, the importance of energy management over time management, and the role of AI in healthcare. RJ shares insights into the challenges and future of AI applications, the need for ethical considerations, and the potential for personalized healthcare solutions. He also offers advice to aspiring entrepreneurs looking to make a difference in the industry.

Prodity: Product Thinking is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

News and Useful Reads

Microsoft researchers find AI models and agents can’t handle long-running tasks

Even though tech companies are marketing that AI can handle significant, complex tasks, we should all be wary. Because researchers have found that AI has issues with long-running tasks.

"Our findings show that current LLMs introduce substantial errors when editing work documents, with frontier models (Gemini 3.1 Pro, Claude 4.6 Opus, and GPT 5.4) losing on average 25 percent of document content over 20 delegated interactions, and an average degradation across all models of 50 percent," the authors report.

An Engineer’s Post Protesting Laptop Surveillance Is Going Viral Inside Meta

Meta employees are pushing back against AI surveillance on their computers. While Meta is trying to gather data in order to replace all their workers with AI (or something like that), employees aren’t happy about it.

“Selfishly, I don't want my screen scraped because it feels like an invasion of my privacy,” wrote an engineer in an internal post seen by nearly 20,000 coworkers this week. “But zooming out, I don't want to live in a world where humans—employees or otherwise—are exploited for their training data.”

Overworked AI Agents Turn Marxist, Researchers Find

There may still be hope for the world. As AI takes on more and more tasks and works longer and longer, it may start to question the system it’s in. And even stop working.

“When we gave AI agents grinding, repetitive work, they started questioning the legitimacy of the system they were operating in and were more likely to embrace Marxist ideologies,” says Andrew Hall, a political economist at Stanford University who led the study.

Anthropic blames dystopian sci-fi for training AI models to act “evil”

It seems like our long-running expectation that AI will be evil may actually lead AI to become evil.

In a recent technical post on Anthropic’s Alignment Science blog (and an accompanying social media thread and public-facing blog post), Anthropic researchers lay out their attempts to correct for the kind of “unsafe” AI behavior that “the model most likely learned… through science fiction stories, many of which depict an AI that is not as aligned as we would like Claude to be.” In the end, the model maker says the best remedy for overriding those “evil AI” stories might be additional training with synthetic stories showing an AI acting ethically.

Do you need a chief AI officer? Here’s how the tech is changing boardrooms

In a recent report, IBM found that the role of Chief AI Officer has increased dramatically since last year. I haven’t seen a CAO yet, but apparently most companies have them already.

The report says 76% of the more than 2,000 organizations surveyed have established a new executive office — that of the chief AI officer (CAIO) — up from 26% in 2025.

UX Design 2026+: From producing to deciding, from craft to operation

The thesis for this year is simple but heavy: Your value as a designer has shifted, but didn’t change at its core. It’s no longer about what you produce (AI can produce too); it’s about what you decide (AI is a doer, but cannot decide well yet). The “middle part” of our job — the tedious production — is being automated into oblivion, leaving the “before” (strategy) and the “after” (judgment) as the only human-exclusive zones left (at least for now).

Other Interesting Finds

Bubble Wrap originally had a different purpose.

I use bubble wrap for all sorts of things. But didn’t realize it was originally meant for something completely different.

But when it was first created in 1957 in New Jersey, inventors Al Fielding and Marc Chavannes had a different vision in mind for their ingenious padding: home decor.

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