As I type, Microsoft Copilot suggests ways to continue, restructure, or even rewrite this very sentence. On the surface, it feels like a small thing, no more remarkable than Gmail finishing an email or Google predicting a searchbut small things can have outsize influence.
Just as the steady drip of water on rock can carve out new channel over time, so predictive text has already reshaped how we write. Research from Harvard has shown that predictive text systems do not just make texting easierthey change the content of those texts, reducing lexical diversity and making our writing more predictable.
This flattening effect is beginning to extend beyond language. Filmmakers have been worried for some time now about the rise of algorithm moviesmovies whose form and content are dictated by what recommendation algorithms tell companies about viewer preferences, instead of by the creative imagination of writers and directors. And if executives arent careful, we can soon expect the emergence of algorithm businessstrategy, operations, and culture flattened out by the rise of LLMs and the race to adopt AI.
AI Models as Consensus Machines
Large language models have become the invisible architects of business strategy. For an increasing number of executives, these AI systems have become default first advisers, strategists, and thought partners. And, as we have already seen with language and movies, this kind of progression can measurably narrow the range of ideas available to us.
Social media is the canary in the coal mine here. Anyone with a LinkedIn account knows that posts from different individuals often sound very similar and that the same ideas are often recirculated again and again. Taken in isolation, this could be seen as a feature of the homogenizing effect of social media algorithms. But the phenomenon is not localized to posts that might be driven by the demands of a recommendation algorithm. Pitches are beginning to sound identical, marketing copy is becoming strangely generic, and if the process continues unchecked, we can expect that the internal documents, analyses, and company strategies will begin to mirror those found in other businesses. In the longer term, we could even see company cultures lose their distinctiveness as differentiating factors begin to blur together.
Smarter Alone, Narrower Together
Generative AI can massively boost performance and productivity. A recent meta-study found, for example, that humans working with AI were significantly more creative than humans working alone.
However, as both that study and a paper in Nature show, while using LLMs improves the average creativity of an individual, it reduces the collective creative diversity of groups. Individuals find their access to new ideas boosted but collectively we end up tapping in to a narrower range of ideas.
The result is that AIs promise of supercharged innovation may actually narrow the frontiers of possibility.
Competitive Convergence
Almost 20 years ago, Michael Porter introduced the idea of competitive convergence. Briefly put, this is a phenomenon that sees companies beginning to resemble their competitors. They chase the same customers in the same ways, their strategies and pricing models become indistinguishable, their operational processes and supply chains end up looking identical.
This process traps companies into a race toward the middle, where distinctiveness disappears and profits are squeezed. With AI, businesses risk falling victim to an accelerated and intensified version of this process: a Great AI Convergence in which operational playbooks, strategic vision, and culture become increasingly generic as organizations increasingly drink from the same conceptual fountain.
AI can optimize efficiency, but it cant capture the human fingerprints that make a company truly distinctive. Your organizations war stories, hard-won lessons, contrarian beliefs, and cultural quirks dont live in any training set. They live in memory, practice, and identity.
And when strategy, messaging, or culture is outsourced to AI, there is a real danger that those differentiating elements will vanish. The risk is that companies will end up losing the authentic, uncommon, and sometimes counterintuitive features that are the vehicle for their uniquenessthe things that makes them them.
The Three Pillars of Business Homogenization
Business homogenization can be broken down into three pillars.1. Strategic Convergence: When Every Plan Looks the Same
Your competitor asks Claude to analyze market opportunities. You ask ChatGPT. Whats the result?
Well, the effect is subtle rather than dramatic. Because the same models are shaping the same executives, the outputs dont collapse into outright uniformity so much as drift toward a narrow band of acceptable options. What looks like independent strategic judgment is often just a remix of the same patterns and playbooks. And so, over time, the strategic choices companies make lose their texture and edge.
2. Operational Convergence: The Automation of Averageness
Companies are already acting on the huge potential that AI has in the realm of operations. For example, Shopify and Duolingo now require employees to use AI as the default starting point for all tasks, and one of the major reasons for this is the prospect of the efficiency gains that AI can deliver.
It is absolutely right that companies use AI to transform operations. But when every company uses similar AI tools for operations, we can expect a drift toward similar processes. Customer service chatbots might converge on the optimal patterns for customer interactions, for exampleand in this convergence lies both danger and opportunity.
The opportunity is optimized efficiency. The danger is that companies lose what differentiates them and drives their unique value proposition. It is essential that leaders recognize this danger so they can begin to think intentionally about authenticity as a potential edge in operations. For instance, it might be worth sacrificing a small level of customer handling speed for a chatbot that delivers quirky and engaging responses that reflect the companys authentic culture and character.
3. Cultural Convergence: When Companies Lose Their Souls
Perhaps the most insidious risk is cultural convergence. When AI drafts your company communications, writes your value statements, and shapes your employee handbooks, it imports the average corporate culture encoded in its training data. he quirks, the specific language, the unique ways of thinking that define your organizationall get smoothed into statistical averages.
Over time, the effect will not only dilute external brand perception but also diminish the sense of belonging employees feel. When people can no longer recognize their companys voice in its own communications, engagement erodes in ways that spreadsheets wont immediately capture.
From Artificial Intelligence to Authentic Intelligence
If AI accelerates sameness, then competitive advantage comes from protecting and amplifying what makes you different. Heres how:
Audit your uniquenessIdentify the knowledge, stories, and perspectives your company holds that no AI model can access. What do you know that others dont?
Create proprietary datasetsFeed AI your unique datacustomer insights, field notes, experiments, failuresinstead of relying on the generic pool of information available to everyone.
Establish AI-free zonesDeliberately protect areas where human judgment and lived experience matter moststrategy off-sites, cultural rituals, moments of customer intimacy.
Adversarial promptingDont just ask AI for answers. Ask it for the contrarian view, the blind spot, the uncomfortable perspective.
Authentic Intelligence
In a world in which every company has access to the same artificial intelligence, the real competitive advantage isnt having AIits having something AI cant replicate. And that can only come from authentic intelligence: the messy, contradictory, beautifully human insights that no model can generate.
AI is the price of admission. Authenticity is how you win.
When you apply sunscreen at the beach, it doesnt necessarily stay on your skin. Some of that sunscreen can wash off when you swim, and the chemicals that shield you from ultraviolet rays end up damaging marine life such as coral reefs, sea urchins, and green algae. Each year, an estimated 6,000 to 14,000 metric tons of commercial sunscreen gets into the ocean. Places like Hawaii and Aruba have already banned certain sunscreens.
A new sunscreen created by material scientists at Nanyang Technological University in Singapore, however, doesnt harm corals. And its not a mineral sunscreen either, which are often thick and can leave a white cast on your skin. Instead of using chemical or mineral filters, it blocks UV waves, thanks to the pollen in camellia flowersand it also keeps your skin cool in the sunlight.
The research team was specifically looking at bio-inspired materials as a way to make a more sustainable, safer sunscreen. We were inspired by the natural resilience of pollen grains, which have evolved over millions of years to protect plant genetic material from harsh UV radiation and environmental stress, Nam-Joon Cho, a professor at NTU and the President’s Chair in Materials Science and Engineering, says over email.
Though pollen has been studied in cosmetic science before for its antioxidant or nutrient properties, it hasnt, to Cho’s knowledge, been used directly as a UV shield before. Pollen is unique because its structure makes it capable of filtering out harmful UV rays while being visually transparent; its also biodegradable.
To turn pollen into sunscreen, the researchers processed the inner parts of the pollen shell into a microgel formula, which applies as an ultra-thin layer on the skin. The pollen-based sunscreen also creates a cooling effect because those microgels block UV light while letting most of the visible and near-infrared light pass through, without absorbing them.
Since those wavelengths carry most of the suns heat, less energy gets trapped and converted into warmth on the skin, Cho says. As a result, the skin stays cooler compared to when commercial sunscreens, which absorb more of that heat-carrying light, are used. (Researchers also made a sunscreen from sunflower pollenwhich blocked UV rays but didnt have that cooling effectthough it wasnt as effective in tests.)
In lab tests, the camellia pollen-based sunscreen blocked UV radiation at levels comparable with conventional mineral sunscreens, with an SPF of about 30. In lab tests with corals, commercial sunscreen spurred coral bleaching in just two days, with coral death happening in around six days. But the pollen-based sunscreen didnt harm the corals, even up to 60 days. That was crucial for the researchers. Using pollen, which is already a natural component of ecological cycles, allowed us to design with environmental safety in mind, Cho says.
The pollen sunscreen may be safer for humans, too. It doesnt include nanoparticles such as titanium dioxide or zinc oxide, which sometimes raise inhalation and safety concerns, Cho says. And even if you suffer from spring allergies, the pollen sunscreen shouldn’t bother you. Camellia pollen is generally considered nonallergenic, and when the pollen is processed, any allergenic proteins are removed.
Next, the researchers want to optimize the sunscreen for longer wear and water resistance. They’re also looking at ways to use pollen in all other applications, like drug delivery or food protection. The larger vision, Cho says, is to build a portfolio of bio-inspired, eco-friendly materials that can replace petrochemical-based products in everyday life.
Despite billions of dollars of AI investment, Googles Gemini has always struggled with image generation. The companys Flash 2.5 model has long felt like a sidenote in comparison to far better generators from the likes of OpenAI, Midjourney, and Ideogram.
That all changed last week with the release of Googles new Nano Banana image AI. The wonkily named new system is live for most Gemini users, and its capabilities are insane.
To be clear, Nano Banana still sucks at generating new AI images.
But it excels at something far more powerful, and potentially sinisterediting existing images to add elements that were never there, in a way thats so seamless and convincing that even experts like myself cant detect the changes.
That makes Nano Banana (and its inevitable copycats) both invaluable creative tools and an existential threat to the trustworthiness of photosboth new and historical.
In short, with tools like this in the world, you can never trust a photo you see online again.
Come fly with me
As soon as Google released Nano Banana, I started putting it through its paces. Lots of examples onlinemine includedfocus on cutesy and fun uses of Nano Bananas powerful image-editing capabilities.
In my early testing, I placed my dog, Lance, into a Parisian street scene filled with piles of bananas and showed how I would look wearing a Tilley Airflo hat. (Answer: very good.)
[Image: Thomas Smith]
Immediately, though, I saw the systems potential for generating misinformation. To demonstrate this on a basic level, I tried editing my standard professional headshot to place myself into a variety of scenes around the world.
[Image: Thomas Smith]
Heres Nano Bananas rendering of me on a beach in Maui.
[Image: Thomas Smith]
If youve visited Wailea Beach, youll recognize the highly realistic form of the West Maui Mountains in soft focus in the background.
I also placed myself atop Mount Everest. My parka looks convincingthe fact that Im still wearing my Travis Matthew polo, less so.
[Image: Thomas Smith]
200s a crowd
These personal examples are fun. Im sure I could post the Maui beach photo on social media and immediately expect a flurry of comments from friends asking how I enjoyed my trip.
But I was after something bigger. I wanted to see how Nano Banana would do at producing misinformation with potential for real-life impact.
During last years Presidential elections here in America, accusations of AI fakery flew between both candidates. In an especially infamous example, now-President Donald Trump accused Kamala Harriss campaign of using AI to fake the size of a crowd during a campaign rally.
All reputable accounts of the event support the fact that photos of the Harris rally were real. But I wondered if Nano Banana could create a fake visual of a much smaller crowd, using the real rally photo as input.
Heres the result:
[Image: Thomas Smith]
The edited version looks extremely realistic, in part because it keeps specific details from the actual photo, like the people in the foreground holding Harris-Walz signs and phones.
But the fake image gives the appearance that only around 200 people attended the event and were densely concentrated in a small space far from the plane, just as Trumps campaign claimed.
If Nano Banana had existed at the time of the controversy, I could easily see an AI-doctored photo like this circulating on social media, as proof that the original crowd was smaller than Harris claimed.
Before, creating a carefully altered version of a real image with tools like Photoshop would have taken a skilled editor daystoo long for the result to have much chance of making it into the news cycle and altering narratives.
Now, with powerful AI editors, a bad actor wishing to spread misinformation could convincingly alter photos in seconds, with no budget or editing skills needed.
Fly me to the moon
Having tested an example from the present day, I decided to turn my attention to a historical event that has yielded countless conspiracy theories: the 1969 moon landing.
Conspiracists often claim that the moon landing was staged in a studio. Again, theres no actual evidence to support this. But I wondered if tools like Nano Banana could fake some.
To find out, I handed Nano Banana a real NASA photo of astronaut Buzz Aldrin on the moon.
[Image: NASA]
I then asked it to pretend the photo had been faked, and to show it being created in a period-appropriate photo studio.
[Image: NASA/Thomas Smith]
The resulting image is impressive in its imagined detail. A group of men (it was NASA in the 1960sof course theyre all men!) in period-accurate clothing stand around a soundstage with a fake sky backdrop, fake lunar regolith on the floor, and a prop moon lander.
In the center of the regolith stands an actor in a space suit, his stance perfectly matching Aldrins slight forward lean in the actual photo. Various flats and other theatrical equipment are unceremoniously stacked to the sides of the room.
As a real-life professional photographer, I can vouch for the fact that the technical details in the Nano Bananas image are spot-on. A giant key light above the astronaut actor stands in for the bright, atmosphere-free lighting of the lunar surface, while various lighting instruments provide shadows perfectly matching the lunar lander shadow in the real image.
A photographer crouches on the floor, capturing the imagined astronaut actor from an angle that would indeed match the angle in the real-life photograph. Even the unique lighting on the slightly crumpled American flagwith a small circular shadow in the middle of the flagmatches the real image.
In short, if you were going to fake the moon landing, Nano Bananas imagined soundstage would be a pretty reasonable photographic setup to use.
If you posted this AI photo on social media with a caption like REVEALED! Deep in NASAs archive, we found a photo that PROVES the moon landing was staged. The Federal Government doesnt want you to see this COVER UP, Im certain that a critical mass of people would believe it.
But why stop there? After using Nano Banana to fake the moon landing, I figured Id go even further back in history. I gave the system the Wright Brothers iconic 1903 photo of their first flight at Kitty Hawk, and asked the system to imagine that it, too, had been staged.
[Image: John T. Daniels]
Sure enough, Nano Banana added a period-accurate wheeled stand to the plane.
[Image: John T. Daniels/Thomas Smith]
Presumably, the plane could have been photographed on this wheeled stand, which could then be masked out in the darkroom to yield the iconic image weve all seen reprinted in textbooks for the last century.
Believe nothing
In many ways, Nano Banana is nothing new. People have been doctoring photos for almost as long as theyve been taking them.
An iconic photo of Abraham Lincoln from 1860 is actually a composite of Lincolns head and the politician John Calhouns much more swole body, and other examples of historical photographic manipulation abound.
Still, the ease and speed with which Nano Banana can alter photos is new. Before, creating a convincing fake took skill and time. Now, it takes a cleverly written prompt and a few seconds.
To their credit, Google is well aware of these risks, and is taking important steps to defend against them.
Each image created by Nano Banana comes with an (easy to remove) physical watermark in the lower right corner, as well as a (harder to remove) SynthID digital watermark invisibly embedded directly into the images pixels.
This digital watermark travels with the image, and can be read with special software. If a fake Nano Banana image started making the rounds online, Google could presumably scan for its embedded SynthID and quickly confirm that it was a fake. They could likely even trace its provenance to the Gemini user that created it.
Google scientists have told me that the SynthID can survive common tactics that people use to obscure the origin of an image. Cropping a photo, or even taking a screenshot of it, wont remove the embedded SynthID.
Google also has a robust and nuanced set of policies governing the use of Nano Banana. Creating fake images with the intent to deceive people would likely get a user banned, while creating them for artistic or research purposes, as Ive done for this article, is generally allowed.
Still, once a groundbreaking new AI technology rolls out from one provider, others quickly copy it. Not all image generation companies will be as careful about provenance and security as Google.
The (rhinestone-studded, occasionally surfing) cat is out of the bag; now that tools like Nano Banana exist, we need to assume that every image we see online could have been created with one. Nano Banana and its ilk are so good that even photographic experts like myself wont be able to reliably spot its fakes.
As users, we therefore need to be consistently skeptical of visuals. Instead of trusting our eyes as we browse the Internet, our only recourse is to turn to reputation, provenance, and good old-fashioned media literacy to protect ourselves from fakes.
Now, if youll excuse me, Burning Man is just ending, and I should really get back to the festivities.
[Image: Thomas Smith]
Youve probably encountered images in your social media feeds that look like a cross between photographs and computer-generated graphics. Some are fantasticalthink Shrimp Jesusand some are believable at a quick glanceremember the little girl clutching a puppy in a boat during a flood?
These are examples of AI slop, or low- to mid-quality contentvideo, images, audio, text or a mixcreated with AI tools, often with little regard for accuracy. Its fast, easy, and inexpensive to make this content. AI slop producers typically place it on social media to exploit the economics of attention on the internet, displacing higher-quality material that could be more helpful.
AI slop has been increasing over the past few years. As the term slop indicates, thats generally not good for people using the internet.
AI slops many forms
The Guardian published an analysis in July 2025 examining how AI slop is taking over YouTubes fastest-growing channels. The journalists found that 9 out of the top 100 fastest-growing channels feature AI-generated content like zombie football and cat soap operas.
The song “Let it Burn,” allegedly recorded by a band called The Velvet Sundown, was AI-generated.
Listening to Spotify? Be skeptical of that new band, The Velvet Sundown, that appeared on the streaming service with a creative backstory and derivative tracks. Its AI-generated.
In many cases, people submit AI slop thats just good enough to attract and keep users attention, allowing the submitter to profit from platforms that monetize streaming and view-based content.
The ease of generating content with AI enables people to submit low-quality articles to publications. Clarkesworld, an online science fiction magazine that accepts user submissions and pays contributors, stopped taking new submissions in 2024 because of the flood of AI-generated writing it was getting.
These arent the only places where this happenseven Wikipedia is dealing with AI-generated low-quality content that strains its entire community moderation system. If the organization is not successful in removing it, a key information resource people depend on is at risk.
Last Week Tonight with John Oliver delves into AI slop.
Harms of AI slop
AI-driven slop is making its way upstream into peoples media diets as well. During Hurricane Helene, opponents of President Joe Biden cited AI-generated images of a displaced child clutching a puppy as evidence of the administrations purported mishandling of the disaster response. Even when its apparent that content is AI-generated, it can still be used to spread misinformation by fooling some people who briefly glance at it.
AI slop also harms artists by causing job and financial losses and crowding out content made by real creators. The placement of this lower-quality AI-generated content is often not distinguished by the algorithms that drive social media consumption, and it displaces entire classes of creators who previously made their livelihood from online content.
Wherever its enabled, you can flag content thats harmful or problematic. On some platforms, you can add community notes to the content to provide context. For harmful content, you can try to report it.
Along with forcing us to be on guard for deepfakes and inauthentic social media accounts, AI is now leading to piles of dreck degrading our media environment. At least theres a catchy name for it.
Adam Nemeroff is an assistant provost for innovations in learning, teaching, and technology at Quinnipiac University.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
A few years ago, we had a bottleneck within our organization at Super.com, the membership program focused on saving, earning, and credit building. Every new idea depended on our engineers, and our internal requests were piling up faster than we could clear them.
We were adding new people to our company every week, but our engineering team was underwater. Every new feature, every minor internal tool, every process tweak depended on our developers. We were hiring as fast as we could, but it felt like shoveling sand against the tide.
So we tried something different. We started teaching nontechnical employees (designers, product managers, operations leads, corporate support teams) how to build their own tools and automations. At first it felt radical. Then it felt obvious.
Fast forward: we grew to over $200M in annual revenue with only about 200 people. We stopped the hiring frenzy, but the business was growing faster than ever. Along the way, we documented everything in an internal playbook for our team. Soon our LinkedIn inboxes and emails were full of messages from other leaders trying to do the same thing. Turns out the problems we had been solving werent unique.
Here are the five lessons that have resonated most with other leaders about empowering nontechnical teams to build their own solutions, and why they matter to any leader.
1. Create Spaces Where Technical and NonTechnical Minds Meet
Inside our company we set up two AI guilds: one for technical implementation (e.g., building tools) and one focused on adoption and use cases (e.g., using tools). They met monthly, included people from every department, and shared concrete experiments. A product manager might present how she used an AI tool to understand the codebase without tapping on the shoulder of an engineer. An operations lead might show how he used a simple script to automate dispute management.
The takeaway: dont keep AI or automation knowledge locked in engineering. Build crossfunctional forums that normalize sharing wins, questions, and learnings. Those conversations surface use cases youd never see from the top down.
2. Invest in Easy-to-Use Tools
You cant empower nonengineers if the only tools they have require a CS degree. We invested in lowcode environments like Superblocks, Zapier, Amplitude, and Glean Agents, and we made tools that are typically only used by developers, such as Cursor (AI IDE) and Coder (Remote Environments), accessible.
Our developer operations team took on the challenge of making onboarding as simple as possible. They stripped out every unnecessary step and automated the rest, until getting set up took less than 10 minutes. We learned quickly that if a tool required more than 10 minutes of training, adoption would stall. Most non-technical teammates could follow the instructions on their own, but for anyone who preferred extra help, our IT team sat down with them one-on-one.
3. Set Guardrails That Empower
We published a clear internal AI policy that spelled out approved use cases (like automation scripts, bugfix prototypes, and research tools), quality standards (human oversight required for anything customerfacing or that becomes part of routine process), and security guidelines (no sensitive data in prompts without review).
Engineers didnt police these policiesthey coached. Any piece of code went through review, whether it came from an engineer or not. That consistency was the point: non-technical team members could submit pull requests, and instead of dismissing them, engineers gave feedback the same way they would with peers. Coaching meant guiding contributors through fixes and best practices, not shutting the door. Guardrails, not gatekeepers, is what makes experimentation sustainable.
4. Celebrate Small Wins Publicly
When someone outside engineering built something that moved the needle (like an operations process automation or AI triage of customer reported issues), we made sure everyone heard about it. These wins were shared in weekly business reviews and companywide meetings. That visibility did more than motivate others to try; it changed our culture. During objectives and key results planning wed prompt each team to consider, Could AI help me hit my goals faster? Could I build this myself instead of waiting? Sharing wins turns isolated hacks created by individuals into company-wide capabilities.
5. Rethink the Role of Your Engineers
When non-engineers have access to the right tools, software engineers become even more valuable. At our company, 93% of developers use AI tools daily. Engineers still own the hard, highimpact work: major features, architecture, deep debugging. But now they spend less time answering basic questions or making tiny fixes for other teams. The result: your best technical talent gets to focus on ambitious projects, while everyone else can handle the smaller, more routine tasks themselves.
In a world where AI and lowcode tools are everywhere, the companies that win wont just have great engineers. Theyll have a culture that empowers everyone to build.
While executives spend billions on meditation apps, yoga retreats, and wellness programs, American stress levels continue to skyrocket. A recent study of 90 workplace wellness interventions found most (with one exception detailed below*) had no positive effectand sometimes even made things worse. Our research from last year found that the majority of us tend to stress out more trying to get rid of stress. Talk about a negative spiral!
We’re trying harder than ever to eliminate stress, yet workplace anxiety has reached crisis levels, just in time for AI disruption to take people over the edge.
Here’s the uncomfortable truth: You’ll never eliminate stress from your career (or your life). But as a stress physiologist, Im here to tell you that’s actually a good thing! My research reveals that our obsession with stress reduction is fundamentally flawed. Instead of fighting stress, the most successful professionals learn to harness it.
The only people with zero stress are dead people. Our aim should not be death.
Here are five evidence-based strategies to rewire how you can work with stressnot against it.
1. Reframe Your Biology as Your Competitive Edge
When your heart pounds before a big presentation, your brain screams “danger.” But that physiological responseincreased heart rate, heightened alertness, elevated energyis identical to excitement. The difference lies in interpretation.
A Harvard study found that participants who stated “I am excited” before delivering speeches were rated as significantly more persuasive and confident than those who tried to “stay calm.” The nervous energy remained the same, but performance dramatically improved.
Stop telling yourself to calm down. Your stress response is a feature, not a flaw. Start declaring: “This energy is preparing me to excel.” Your stress response isn’t sabotaging youit’s upgrading your operating system.
2. Ask “Is This Actually a Tiger?”
Your brain evolved to treat missed emails like charging predators. This served our ancestors well but creates havoc in modern workplaces. When stress hits, pause and ask: “Will this kill me in the next three minutes?”
If not, you’re experiencing what I call a “paper tiger”a stressor that feels life-threatening but isn’t. Once you recognize the false alarm, you can redirect that energy productively instead of spiralling into fight-or-flight paralysis.
3. Convert Anxiety into AngerStrategically
When facing seemingly insurmountable challenges, excitement might feel impossible. That’s where anger becomes your ally. Studies reveal that anger increases effort toward goals and sparks greater creativity than neutral emotional states.
The key is directing anger at the problem, not people. Instead of fuming at difficult colleagues, channel that energy toward solving systemic issues. Transform “This situation is impossible” into “This problem needs fixing, and I’m going to figure out how.”
Anger mobilizes action. Point it in the right direction.
4. Think Micro-Goals, Not Mega-Outcomes
Stress often stems from feeling overwhelmed by massive objectives. Break intimidating projects into actions so small they’re nearly impossible to fail. When you complete micro-goals, your brain releases dopamine, creating an addictive cycle of progress.
When we think we have to leap Everest in a single jump, or relearn our entire job because of AI, our brain naturally defaults to helplessness. But by taking action, even incredibly small moves, we begin to regain agency and feel more in control. This actionable hope ultimately moves us beyond our state of learned helplessness.
Ask yourself: “What’s the smallest possible step forward?” Then take it. Winning becomes neurologically addictive (even if the perfect outcome isnt guaranteed).
5. Make It Bigger Than You
The most transformative reframe involves expanding your perspective beyond personal gain. When you anchor goals in serving something largeryour team, customers, communitythe fear centers in your brain quiet down.
Back to those workplace wellness studies. In the 90 workplace stress interventions, the only thing that consistently improved employee well-being was service to others. When stress serves a purpose beyond yourself, it transforms from burden to fuel.
Before your next high-stakes meeting, shift from “How do I not mess this up?” to “How can I serve my audience?” The stress remains, but now it’s powering something meaningful and reminding you that stress is often simply a barometer for how much you care.
The Paradox of Peak Performance
Olympic athletes don’t break world records during practice. They achieve greatness when pressure peaks. Your biggest professional breakthroughs likely occurred during your most stressful periods, not your calmest.
This isn’t about glorifying burnout or toxic work cultures. It’s about recognizing that stress, properly channeled, is the raw material of achievement. The goal isn’t eliminationit’s transformation.
Your stress isn’t going anywhere. But your relationship with it can change everything. Stop trying to manage it away. Start using it as the high-octane fuel it was designed to be.
The question isn’t whether you’ll face stress today; It’s whether you’ll let it defeat you or springboard you forward.
There was a time when leaders followed a linear path. Pick a lane, specialize, climb the ladder, and stay the course for decades. But that norm is unraveling. Global complexity demands leaders who are adaptive, integrative, and, above all, multifaceted. These individuals dont fit neatly into one category; they may be artists and scientists, coaches and corporate strategists, or data analysts and storytellers. And far from being a liability, these dualities are now an asset.
To be successful in todays world, leaders need to connect across ideas, industries, and cultures. To be able to do that skillfully, you must play in more than one arena. Its no longer just about what you do during your nine-to-five. Its the sum of your experiences and the unique value you bring to the world.
This requires you to embrace your full complexity, not just for personal growth, but also as a competitive edge. The future of leadership belongs to those who can hold nuance, navigate change, and bring their whole selves to the table.
Less specializing, more integrating
The old story was: Pick a lane and stay in it. Specialization was in favor. But now, as AI handles narrow expertise, whats left for us? The answer lies in focusing on integration and expression. The leaders who thrive now are those who connect dots across disciplines, sectors, and identities. They see what others miss because they live in more than one world.
Former PepsiCo CEO Indra Nooyi didnt follow a linear path. She studied physics, chemistry, and math. She also played in a band and excelled at cricket. Then she eventually went on to pursue design thinking and innovation at Yale. Her leadership wasnt just data-driven; it was holistic. She could speak to Wall Street and public health advocates with equal ease. And under her leadership, PepsiCos revenue nearly doubled, rising from $35 billion to over $63 billion.
The best leaders integrate diverse skills and experiences to drive innovation and connect more authentically with their teams. This integration not only broadens perspective but also deepens trust, fosters creativity, and empowers teams to operate with greater empathy and cohesion.
Navigating change with agility
Todays leaders are not only leading through change; they are the change. They embody fluidity, resilience, and the ability to evolve across multiple life chapters. In his book Range, journalist David Epstein writes: Approach your own personal voyage and projects like Michelangelo approached a block of marble, willing to learn and adjust as you go, and even to abandon a previous goal and change directions entirely should the need arise.
After a few years of working in finance, Shuo Zhai followed his passion for architecture and pursued his master’s degree at Yale. He worked with Frank Gehry at Gehry Partnersand in parallel, he sings with the Grammy Award-winning Los Angeles Master Chorale, and works as a world-class chamber music pianist. He believes that his multidisciplinary approach enables better problem-solving, and deeper empathy and understanding, ultimately leading to more effective architecture and music. The ability to pivot and grow isnt built in one role: Its built across roles. Leaders who draw from multiple domains are more resilient and curious during transitions.
In his own journey, Tony Martignetti transitioned from a finance and strategy executive in the life sciences industry to a leadership development facilitator and experience designer. Along the way, he reconnected with his identity as an artistbringing creativity, storytelling, and visual thinking into his work with leaders. That blend of analytical precision and artistic intuition has allowed him to help others navigate ambiguity, reimagine their narratives, and unlock new dimensions of their leadership. Where have you built resilience in one part of your life that could serve you in another?
Why multifaceted leadership matters
Jessica Wan, spent nearly two decades as a marketing and strategy executive at organizations such as Apple, San Francisco Opera, Smule, and Magoosh. Eventually, she transitioned into a leadership coach and venture partner. But shes continually applied learnings from her lifelong artistic identity as a musician and singer to leadership challenges. This rare blend of analytical acumen and creative sensibility enables her to help leaders navigate change and transform chaos into clarity.
Jessica launched her podcast to spotlight individuals who embody this multidimensional path: a neuroscientist and an Indian classical dancer, an entomologist and a journalist, and a business professor and a Broadway investor. Their message? You dont have to shrink to fit in. When a young person says, I want to be an astronaut and a ballerina, we want to be able to say: Yes, you can.
How to embrace being a multifaceted leader
Leaders arent just executives. They are also musicians, poets, caregivers, podcast hosts, and community volunteers. And denying those dimensions leads to fragmentation and fatigue. Instead of hiding those parts, successful leaders integrate themand invite them into the room.
We need to recognize the value of integrating these roles into our leadership approach. But before we can do so, we must first explore them. Heres a quick exercise to get you started:
What is a role outside your professional life that matters deeply to you?
What leadership traits have you developed from that role?
How could you apply those traits to a current work challenge?
This isnt just about driving career success; it is about living a more fulfilling life. Its about giving yourself and others permission to fully live into your potential.
We believe this is the future of leadership: bold, complex, curious, and fully alive. For us, bringing our artistic backgrounds into the leadership space has profoundly shaped our work in the business world. The arts invite presence, reflection, and imaginationthree qualities that help leaders break free from rigid thinking and connect with the deeper purpose behind their work.
Our invitation: Audit the dimensions of your identity, find the intersections, and show up fullynot just for your team, but for yourself. You dont have to choose between your roles. The world needs all of you.
The Food and Drug Administration (FDA) is alerting the public via its recall website to be on the lookout for bags of frozen vegetables, due to possible contamination from Listeria.
New York-based Endico Potatoes is voluntarily recalling peas and carrots and mixed vegetables sold between July 18 and August 4 in New York, New Jersey, Pennsylvania, Connecticut, Maryland, Florida, and Washington, D.C.
The company ceased distribution of the product after sampling by the state of Pennsylvania revealed the presence of the bacteria. No illnesses have been reported to date, and the FDA and Endico are continuing to investigate the cause.
What is Listeria and what are the symptoms?
Listeria monocytogenes is a type of disease-causing bacteria that is generally transmitted when food is harvested, processed, prepared, packed, transported, or stored in manufacturing or production environments contaminated with the bacteria, according to the FDA.
Infection can lead to severe symptoms such as fever, nausea, abdominal pain, and diarrhea, poses a particular risk to vulnerable populations, including pregnant women, the elderly, and those with weakened immune systems. In pregnant women, it can cause miscarriages and stillbirths.
What is the product information for the recall?
The product was packed in frozen 2.5-lb clear plastic bags under the Endico label. Details for the affected products are as follows:
“PEAS AND CARROTS”:
Lot number: 110625
Production date: June 11, 2025
Use by date: June 10, 2027
“MIXED VEGETABLES”:
Lot number: 170625
Production date: June 17, 2025
Use by date: June 16, 2027
The lot codes are printed on the side of the bag.
What if I have these products in my freezer?
Consumers who have purchased Endico brand peas and carrots or mixed vegetables with these lot codes are urged to not consume the products and to return them to the place of purchase for a full refund.
Consumers with questions may contact the company by phone at 1-800-431-1398.
The number of Americans filing new applications for unemployment benefits increased more than expected last week, while hiring by private employers slowed in August, offering further evidence that labor market conditions were softening.
The reports were released a day after government data showed there were more unemployed people than positions available in July for the first time since the COVID-19 pandemic. Job growth has shifted into stall-speed, with economists blaming President Donald Trump’s sweeping import tariffs and an immigration crackdown that is hampering hiring at construction sites and restaurants.
The slackening labor market likely positions the Federal Reserve to resume cutting interest rates later this month, though much would depend on August’s employment report to be published on Friday and consumer price data due next week.
“We continue to see softness growing in the labor market as tariff policy uncertainty lingers, immigration changes take effect, and AI adoption grows,” said Eric Teal, chief investment officer at Comerica Wealth Management. “The silver lining is the weaker the jobs data, the more cover there is for stimulative interest rate cuts that are on the horizon.”
Initial claims for state unemployment benefits rose 8,000 to a seasonally adjusted 237,000 for the week ended August 30, the Labor Department said. Economists polled by Reuters had forecast 230,000 claims for the latest week.
Still, layoffs remain relatively low as businesses generally hoard workers following difficulties in finding labor during the pandemic, anchoring the labor market. The unsettled economic environment, stemming from the protectionist trade policy has, however, left businesses reluctant to increase headcount.
That hesitancy to hire means people who are laid off have difficulty landing new opportunities. The number of people receiving benefits after an initial week of aid slipped 4,000 to 1.940 million during the week ending August 23, the claims report showed.
The Fed’s “Beige Book” report on Wednesday noted that “firms were hesitant to hire workers because of weaker demand or uncertainty.” The softening labor tone was reinforced on Thursday with the release of the ADP National Employment Report, which showed private employment increased by 54,000 jobs last month after advancing by 106,000 in July.
The downbeat assessment of the labor market was also evident in the Institute for Supply Management survey, which showed a measure of services sector employment contracting for a third straight month in August.
Economists, as a result, are bracing for another month of tepid job growth when the Labor Department’s Bureau of Labor Statistics publishes its closely watched employment report on Friday. A Reuters survey of economists estimated nonfarm payrolls increased by 75,000 jobs last month after rising by 73,000 in July.
Employment gains averaged 35,000 jobs per month over the three months to July compared to 123,000 during the same period in 2024, the government reported in August. The unemployment rate is forecast to climb to 4.3% from 4.2% in July.
Fed Chair Jerome Powell last month signaled a possible rate cut at the U.S. central bank’s September 16-17 policy meeting, acknowledging the rising labor market risks, but also added that inflation remained a threat. The Fed has kept its benchmark overnight interest rate in the 4.25%-4.50% range since December.
Stocks on Wall Street were trading higher. The dollar rose against a basket of currencies. U.S. Treasury yields fell.
Trade deficit widens
Tariffs continued to influence trade data. A separate report from the Commerce Department’s Bureau of Economic Analysis showed the trade deficit ballooned 32.5% to $78.3 billion in July amid record inflows of capital and other goods.
The duties have caused wild swings in imports and ultimately the trade deficit, distorting the overall economic picture. A U.S. appeals court ruled last week that most of Trump’s duties, which have boosted the nation’s average tariff rate to the highest level since 1934, were illegal, creating more uncertainty for businesses.
Imports soared 5.9% to $358.8 billion. Goods imports vaulted 6.9% to $283.3 billion. They were boosted by a $12.5 billion surge in imports of industrial supplies and materials, which reflected a $9.6 billion increase in non-monetary gold imports. But petroleum imports were the lowest since April 2021.
Capital goods imports increased $4.7 billion to a record $96.2 billion, driven by computers, telecommunications equipment and other industrial machinery. Semiconductor imports declined $0.8 billion. Imports of consumer goods increased $1.3 billion, though pharmaceutical preparations imports fell $1.1 billion.
Imports of motor vehicles, parts and engines decreased $1.4 billion. Exports rose 0.3% to $280.5 billion. Exports of goods edged up 0.1% to $179.4 billion. Capital goods exports increased $0.6 billion to a record $59.9 billion, lifted by shipments of computer accessories and civilian aircraft. Exports of excavating machinery fell $1.5 billion.
Exports of motor vehicles, parts and engines increased $0.3 billion. Industrial supplies and materials exports decreased $0.2 billion as finished metal shapes dropped $2.5 billion. Non-monetary gold exports increased $2.9 billion.
The goods trade deficit widened 21.2% to $103.9 billion. The goods trade deficit with China increased $5.3 billion to $14.7 billion. Imports of services increased $1.7 billion to a record $75.5 billion in July, reflecting rises in transport, travel and other business services.
Exports of services increased $0.6 billion to a record high of $101.0 billion, driven by the transport, charges for the use of intellectual property as well as government goods and services. Travel services, however, dropped $0.3 billion amid the White House’s immigration crackdown.
Trade subtracted a record 4.61 percentage points from GDP in the first quarter before sharply reversing and adding 4.95 percentage points in the second quarter, also the largest contribution on record.
The economy grew at a 3.3% annualized rate last quarter after contracting at a 0.5% pace in the first three months of the year. Goldman Sachs lowered its third-quarter GDP growth estimate to a 1.6% rate from a 1.7% pace.
“Disruptions from tariffs are still making their rounds across the economy and increased uncertainty continues to be present in firms’ decision-making processes,” said Eugenio Aleman, chief economist at Raymond James.
Lucia Mutikani, Reuters
If you’re a regular Fast Company reader, you may come check the site when you want news, or follow us on social media. But when you’re looking for something on Google, would you also like to find out if Fast Company has covered your question already? We know the Google search pages are getting harder and harder to navigate, with AI summaries and countless little boxes, but there’s a new way to ensure you’re seeing Fast Company stories relevant to your query near the top of your search results.
Google has a new feature called “Preferred Sources,” which lets you select which news outlets appear in the Top Stories box. The next time you’re searching for a news event, you’ll see relevant Fast Company stories first instead of a random selection of local news sites rehashing the same version of the news. Google also plans to roll out a specific From Your Sources” section that will then also feature Fast Company stories.
Here’s what to do.
1. Go to this Google link
Clicking here will bring you to the Google page that lets you select your sources, with Fast Company already filled in.
[Screenshot: Google]
2. Click the check box next to Fast Company
Add a little blue check to the left. You can also do this from the Top Stories section on the search page by clicking the star icon next to the Top Stories header.
3. Refresh your search results
If there’s a Fast Company story that fits your search criteria, it should now be near the top.
You can also, of course, add other sites you like to further customize your experience. But now your Google results can better reflect the sources you want to hear from.
