The debate over which blockchain will dominate is finished. Bitcoin long ago established itself as the number one global store of value, and we’ve seen Ethereum cement its place as the primary settlement layer for digital finance.

Early blockchain development was shaped by rivalry. Each new network tried to outperform the others on speed, cost or decentralisation. It was a period that helped drive innovation but also distracted many in crypto from the real question: ‘How can these systems now serve people and businesses?’

Now it’s all about execution. These are pivotal moments for the industry, and we’re beginning to see blockchains move from theory to practical usage.

Crypto’s early years revolved around price and speculation. And they were needed — they served a purpose. Attention and hype brought in invaluable capital, but, unfortunately, also narrowed how people saw the technology. Mainstream investors and traditional finance watched the 2017 boom in ICOs, and it turned blockchain into a byword for wild speculation.

The industry has matured and is finding real-world uses for its products. The adoption of stablecoins alone is expected to generate an additional $1.4 trillion in demand for US dollars by 2027. It now begs the question of not whether blockchain works, but how it can scale to billions of users.

Related: This Ownership Shift is Going to Open Global Wealth to Everyone

The rise of execution layers

Enter execution layers. They make transactions fast, reliable and affordable, bridging Ethereum’s security with the ease people expect from modern payment systems. Bitcoin and Ethereum have different but complementary roles. Bitcoin is the secure digital reserve, a hedge against inflation and policy risk, while Ethereum is the programmable base for settlement and trustless transactions.

Neither one of these two giants of crypto was built for speed. Their strength is security and finality. Growth now depends on the systems built on top of them. These networks make blockchain fast and reliable enough to match modern payment and banking systems.

The goal of an execution layer is to make blockchain invisible to users while keeping every transaction transparent. When payments clear instantly, and fees cost less than a cent, people stop thinking about the technology and just use it.

Stablecoins now move money across borders instantly and at almost no cost, but only when the networks beneath them can handle constant activity without slowing or breaking. The same principle applies to every form of digital value, from savings products to payments and onchain lending. Growth stalls before it reaches scale if it isn’t underpinned with dependable infrastructure.

Fintechs are starting to act on this. Stripe’s launch of stablecoin payments on Polygon shows that blockchain is becoming part of everyday finance and not a side experiment. The infrastructure is used to move tokenised assets, settle trades and connect new digital markets with traditional finance.

This results in a single, more fluid system where value can travel anywhere. Tokenised funds are already moving onchain. Franklin Templeton’s OnChain US Government Money Fund, built on Polygon, is proof that traditional assets can operate directly on public blockchain infrastructure.

Related: Why Everyday Transactions, Not Wall Street, Will Drive Crypto Adoption

The next challenge

A major challenge now is connection. Users, assets and activity remain scattered across different chains, limiting scale and liquidity. For Web3 to grow, these systems must work together as one network.

At Polygon, this is the problem we are addressing with Agglayer, a framework that links multiple blockchains so they can share value and security while keeping their independence. It lets developers expand to new users without rebuilding everything from the ground up.

When that connection happens, Web3 starts to look like a functioning economy rather than isolated silos. The importance of linked networks lies in the fact that it allows value to move freely.

Real adoption is strongest where the need is greatest. Across Latin America, Africa and Southeast Asia, stablecoins are part of everyday life. Families in Argentina use them to protect savings from inflation amid an ongoing economic crisis. Freelancers in the Philippines receive wages in digital dollars.

Around the globe, there are real economies powered by blockchain systems that focus on speed and low cost. Once people can send money instantly without thinking about what enables it, adoption will become permanent.

Competition in Web3 has shifted from ideology to execution. The debates over consensus models or technical purity matter less than how well a network performs. The leaders will be those who offer a smooth, reliable experience and can handle millions of users without strain. When blockchain becomes simple and invisible, users stop discussing crypto.

The era of competing base layers has run its course. What matters now is how well execution networks turn that foundation into practical tools for people, businesses and governments.

The next wave of adoption will be led by those who make blockchain useful, not just possible. The builders who focus on making it invisible will define its most visible impact.

The debate over which blockchain will dominate is finished. Bitcoin long ago established itself as the number one global store of value, and we’ve seen Ethereum cement its place as the primary settlement layer for digital finance.

Early blockchain development was shaped by rivalry. Each new network tried to outperform the others on speed, cost or decentralisation. It was a period that helped drive innovation but also distracted many in crypto from the real question: ‘How can these systems now serve people and businesses?’

Blake Lawrence launched Opendorse — now the leading NIL marketplace — from his Nebraska dorm room with cofounder Adi Kunalic, nearly a decade before most people even knew what “NIL” meant.

Today, the platform supports more than 100,000 athletes and has facilitated close to a billion dollars in name, image, and likeness transactions — a scale once unimaginable.

“In North America, only about 5,000 pro athletes earn money through endorsements,” Lawrence tells Entrepreneur. This includes everything from social media promotions to commercials and billboards.

“Opendorse stepped in to give those athletes one platform to manage everything: who’s paying them, what they’re getting paid for, their deliverables, contracts, tax documents and compliance.”

Opendorse began in 2012 as a tool Lawrence built to help his former Nebraska football teammate, Prince Amukamara, manage endorsements after he reached the NFL. Lawrence and cofounder Adi Kunalic created an app to automate the process and, essentially, “help him get paid to tweet.”

It didn’t take long for reality to set in.

“When we onboarded Prince, I immediately got a call from his agent asking what we were doing,” Lawrence says. “I told him we were getting Prince paid to tweet, and he shut it down fast: ‘You can’t do that — that’s my client.’”

So Lawrence added an agent workflow. Then payments hit Amukamara’s account, and his financial manager called next, demanding documentation. After that, the NFLPA reached out. One by one, every stakeholder had a say.

At the time, it was exhausting. Looking back, Lawrence sees it differently.

“We were getting our asses kicked left and right by rules and policy changes early on,” he says. “We had to constantly tweak and adjust just to survive. I wouldn’t wish it on my worst enemy — but I wouldn’t trade it for anything.”

Related: “You Have to Grow Up Fast”: How This College Athlete Became a CEO Before Turning 18

Half a million athletes. One very complicated marketplace.

When NIL entered college sports in 2021, Opendorse quickly shifted its focus to younger, less experienced athletes who needed more support — and represented a far larger market. There are roughly 500,000 college athletes, making the space 10 times bigger than the pro market.

“When you add college athletes, the scale changes dramatically,” Lawrence says. “But that size also brings added complexity.”

The platform functions the same for college and pro athletes, but the key difference is compliance. NCAA athletes face strict rules around what they can and can’t endorse — no tobacco, alcohol or betting brands, for example. And every deal must be disclosed and approved. These regulations are enforced at both the state and national levels through NCAA policies overseen by the College Sports Commission.

That is far from the only complexity involved with this multi-level marketplace, however.

Serial entrepreneur and self-described ‘industrial athlete’ Steve Denton joined Opendorse a few years in to help scale the business. He had no sports background beyond being a fan. Still, having lived through the early internet era as a businessman, he immediately saw parallels between that moment and the rise of NIL in college sports.

“From a monetization standpoint, the internet did around $400 million in ad sales in its third year,” Denton says. “NIL? $800 million. I’m not saying it’s the same thing, I’m just saying it’s off to a great start.”

When Denton met the cofounders, he saw a winning team with a good business and a lot of potential that just needed some help getting to the next level.

“I’m terrible at zero to $5 million,” Denton laughs. “But if you need to go from $5 million to $100, that’s where I’m comfortable.”

The biggest thing that stood out to Denton was the ridiculous TAM (total addressable market).

“I saw a platform that was moving hundreds of millions of dollars of payments, and was keeping 175,000 kids compliant,” he remarks. “I don’t know the last time you tried to get a hold of an 18-year-old for negotiations, but this certainly makes it a lot easier.”

Related: The Cavinder Twins and Raising Cane’s Owner & Founder Reveal the Secret Sauce of Success

A war on two fronts

Opendorse operates on two fronts: the brand side and the athlete side.

On the brand side, the first challenge is helping companies figure out which athletes to work with. Denton calls Opendorse’s matching technology a “fish finder” — it surfaces the right athletes based on a brand’s audience, goals, budget, and safety guidelines.

Once a brand decides to move forward, Opendorse handles everything: sending offers, delivering contracts, outlining deliverables, managing taxes, securing approvals, ensuring the athlete completes the work and handling all NCAA and school reporting.

Since college athletes are balancing classes, practices, and games, they’re not full-time creators. Opendorse’s technology makes the whole process simple and manageable for them.

On the athlete side, Lawrence and his team focus on getting athletes onto the platform — a process that often involves on-campus visits and hands-on onboarding. These sessions walk athletes through downloading the app, setting up their profiles and learning how to present themselves professionally.

Lawrence compares it to building a résumé: why should a brand choose you out of hundreds of athletes on your campus? Schools play a role, too, overseeing deals to ensure compliance.

Plus, it’s a massive boon to participating schools.

“If you’re the first school in your conference to partner with Opendorse, you gain a real recruiting edge — you can tell prospects you’re the only program in the market with a top-tier NIL marketplace,” Lawrence says. “Schools need a partner like Opendorse to give athletes a simple, compliant way to access NIL deals, and that’s how we build the supply side of the platform.”

Related: He’s Helping College Athletes Navigate a Multi-Billion-Dollar Industry — But His Top Money Tip Can Help Anybody Grow Substantial Wealth

Moguls and machetes

Lawrence and Denton complement each other well — one coming from the athlete world, the other from entrepreneurship.

“Blake has forgotten more about NIL than I could ever know,” Denton says. “I didn’t appreciate the complexity of it when I first joined.”

Lawrence feels the same way, calling Denton a mentor.

“As an entrepreneur, even with a cofounder, it’s like you’re in the jungle with a machete,” he says. “You’re hacking away, and at least someone’s next to you, but they don’t know where you’re going either.”

Denton, he says, is the seasoned guide — helping navigate the dense forest of compliance and regulation.

“I can’t say enough about what it means to have somebody who’s done it before and can help us take those steps,” he adds.

By the end of the decade, Opendorse aims to move $10 billion to college athletes. But day to day, the team isn’t fixated on the finish line — they’re focused on execution.

“We want to do really great work every day,” Denton says. “We have to, because the college economy has changed so much in just the last year. You’ve got the House settlement, salary caps, a third-party entity defining fair market value, and the people who made the rules now trying to rewrite them. Congress is being lobbied, payment companies want in — the entire ecosystem is shifting at once.”

Because of this, resilience is critical.

“It’s like skiing moguls,” Denton adds. “You need a strong core and flexible knees. And we’re definitely hitting some moguls right now.”

When OpenAI CEO Sam Altman announced in March 2025 that the company’s COO would take on an expanded global role, the news signaled more than just an internal reshuffle. With AI adoption accelerating and public scrutiny mounting, leadership decisions at OpenAI now ripple across industries. In moments such as these, how a leader reacts — and just as importantly, how they don’t — becomes a defining factor.

But the strongest leaders take a different approach. They don’t rush to spin a story, control the narrative or make decisions just to be seen doing something. They stay focused on what’s happening now, keeping both what happened yesterday and what could happen tomorrow in context but at arm’s length. They think clearly, act deliberately and stay grounded. That’s the heart of neutral thinking.

Neutral thinking isn’t about staying quiet or avoiding emotion. It’s about stepping back just enough to see clearly and reserve the need to jump to conclusions too quickly. When the stakes are high, clarity is often the most valuable thing a leader can bring. Practicing neutral thinking doesn’t require a total shift in leadership style. It comes down to a few deliberate behaviors that help you stay grounded when it matters most.

Related: As a Leader, You Set the Tone — Here’s Why Staying Calm Builds a Stronger Business

1. Lead from what’s real, not what you wish were true

In executive coaching, neutrality is one of the most consistently useful tools leaders can develop. It’s not flashy, but it works, especially under pressure. Neutral leaders focus on the situation as it is, not as they wish it were. They avoid assumptions, don’t take one side too fast, acknowledge what’s real and ask, “What’s the next step we can take, based on what we know right now?” This kind of thinking creates calm in environments that are anything but calm. And when teams are watching their leaders for cues, calm is contagious.

Sheldon Yellen, CEO of BELFOR, a disaster recovery company that operates globally, understands this firsthand. His teams respond to some of the most chaotic situations imaginable, from wildfires to hurricanes. He puts it simply: “In a crisis, I look at the facts, what we can act on right now, what’s the next most logical step. It takes the emotion and noise out of decision-making, which keeps my team steady and moving forward.”

When leaders show up clear and collected, others tend to follow suit. That effect is a kind of emotional mirroring, and it’s what makes neutrality such a powerful stabilizer. It doesn’t just help the leader think more clearly; it helps the entire team perform more effectively.

2. Stay emotionally present without being led by emotion

There’s a common misunderstanding that neutrality means shutting down emotionally or becoming robotic. The opposite is true. Neutral leaders stay deeply connected to their teams; they just don’t let heightened emotions derail their judgment.

It’s possible to be empathetic and even emotionally present while staying centered. That balance is where strong leadership lives. The goal isn’t to suppress feelings, but to avoid being led by them. Good leaders know how to acknowledge tension, validate what others are experiencing and then guide the group forward.

Research supports this. A 2025 study published in Administrative Sciences found that key dimensions of emotional intelligence, including self-regulation and empathy, significantly predicted employee performance — even in crisis conditions. Self-regulation alone was found to be one of the strongest predictors of employee performance, making it a critical trait for leaders navigating high-pressure situations.

That’s why neutrality often feels steady, not cold. People want to know that their leader sees them and hears them, but also that their leader knows what to do next.

3. Set the emotional tone your team will follow

Stress spreads quickly in teams. When leaders lose their emotional control, the anxiety multiplies. People second-guess decisions, communication gets muddy, and progress slows down. But when a leader stays composed, the opposite happens. The room settles. Priorities become clearer. Energy shifts from reaction to action.

This mirror effect isn’t about personality. It’s about presence. People take emotional cues from the person in charge. The more consistent that presence is (in good times and bad), the more trust builds.

Recent research shows that emotionally grounded leaders help teams feel safer and more capable of adapting during periods of uncertainty. When leaders stay calm and focused, their teams are better able to regulate their own stress and continue performing effectively.

In coaching conversations, we often ask leaders, “What mood do you bring into the room?” That’s not about being upbeat or optimistic all the time. It’s about being intentional. Leaders set the tone, whether they mean to or not.

Related: The Best Leaders Have This Underrated Leadership Trait — and You Can Build It

4. Use daily rituals to stay steady under pressure

Neutral thinking doesn’t just happen in the heat of the moment. It’s built and maintained through habits. The most effective leaders practice this discipline long before they need it. They rely on what some call anchoring rituals — simple daily routines that keep them centered, even when everything else feels uncertain.

For some, that’s a morning routine that brings focus before the day starts. For others, it’s a brief check-in with direct reports to reset priorities and listen for friction points. Others rely on gratitude practices, quiet walks or even listening to the same song every day to clear their minds.

Jeff Weiner, the former CEO of LinkedIn, famously blocked “white space” on his calendar each day — time reserved for reflection, strategic thinking and resetting his mental state. That practice helped him make clearer, more deliberate decisions, even when external pressure was high.

What matters isn’t the specific ritual. It’s the intention behind it. These anchors create a sense of control in a world that rarely offers it. And when leaders feel steady, they lead more clearly and more consistently.

5. Model the behavior you want others to follow

The most impactful leaders don’t just stay calm — they show their teams what calm looks like in action. Whether it’s pausing before responding, focusing on facts or approaching problems step by step, the way a leader behaves under pressure becomes the blueprint others follow.

Sundar Pichai, CEO of Google, is known for maintaining composure in high-stakes environments — and doing so intentionally. He emphasizes the importance of staying grounded when under pressure, explaining that leadership isn’t about controlling others but about modeling the behavior you want to see. That steady presence is one reason Google’s internal culture continues to rank high in transparency and trust.

When leaders model steadiness, they give their teams permission to do the same. These actions don’t need to be dramatic. Often, it’s the quietest move — a pause, a clear sentence, a visible moment of composure — that sets the tone for everyone else.

Related: Leaders Aren’t Judged on Effort — They’re Judged on Their Judgment. Here’s How to Sharpen Yours.

The strongest move may be the quietest one

In difficult moments, leaders often feel the pressure to do something. Say something. Fill the silence. Show certainty, even when things are unclear. While taking action is critical for all progress, often, the most powerful move is the one that doesn’t look dramatic from the outside. It’s the choice that was made after a deep breath, good listening, a pause. To wait for clarity before making decisions. To hold the team steady when everything around them is shaking.

Neutral thinking gives leaders a way to do exactly that. It’s not about avoidance. It’s not about detachment. It’s about presence: clear, calm and committed. And in the moments that matter most, that might be the clearest leadership signal you can send.

When OpenAI CEO Sam Altman announced in March 2025 that the company’s COO would take on an expanded global role, the news signaled more than just an internal reshuffle. With AI adoption accelerating and public scrutiny mounting, leadership decisions at OpenAI now ripple across industries. In moments such as these, how a leader reacts — and just as importantly, how they don’t — becomes a defining factor.

But the strongest leaders take a different approach. They don’t rush to spin a story, control the narrative or make decisions just to be seen doing something. They stay focused on what’s happening now, keeping both what happened yesterday and what could happen tomorrow in context but at arm’s length. They think clearly, act deliberately and stay grounded. That’s the heart of neutral thinking.

Generative AI has revolutionized video content. The barrier between having a vision for a video and implementing it is now lower than ever. For video marketers, this presents a conundrum. On the one hand, they can streamline their production process. On the other hand, there’s the threat of oversaturation and content inflation.

To effectively use AI for video marketing, businesses must avoid common pitfalls that result in bland, unoriginal content that will disappear in the waves of AI content already crashing over social media platforms.

Here’s how.

1. Overcomplicating prompts or failing to personalize them

In using generative AI, the first key challenge video marketers face is to strike a balance between failing to personalize prompts and overcomplicating them.

A prompt should be specific enough to ensure that the resulting video content aligns with your brand voice. At the same time, you shouldn’t sink enormous amounts of time into overly complex prompts that include too many technical specifics or conflicting style requests.

Instead, use a concise, well-structured prompt. You should:

• Clearly outline the core requirements in one or two sentences
• Add two or three key details
• Give concise aesthetic directions
• Add the critical technical specifics, such as resolution and aspect ratio.

Overall, try to keep your prompt to 150 words max.

Related: How AI Is Completely Changing YouTube Content and What Creators Must Do Now

2. Ignoring audience preferences and analytics

In the rush of generating AI video, there are several standard aspects of video marketing that often fall by the wayside — including quality control and analytics.

Resist the temptation to rely on visually stunning content only, without accounting for the preferences of your target audience.

As with classical video marketing, you need to be clear on exactly who the target demographic is and how you can best reach them.

Keep a close eye on analytics to gauge how your AI video performance compares to that of other types of content you’ve uploaded. Visually complex, AI-generated content does resonate with some demographics. Others will prefer a more human, authentic and classically produced video.

It’s critical to let your analytics inform your content strategy, and to adjust it depending on the platforms and audiences you are targeting.

3. Failing to tailor AI content to the target platforms

There is no one-size-fits-all solution when it comes to video marketing across different platforms. TikTok, YouTube and Reels — all these social media platforms have their unique styles and audience preferences.

If you do not factor these nuances into your content strategy, your videos will end up underperforming.

The good news? AI video editing tools can, in fact, help you custom-tailor a video for different platforms, from reformatting long-form YouTube content to impactful Shorts and Reels, to adding just the right type of transitions and quick cuts popular on TikTok.

Related: This Fun Friday Night Family Ritual Taught Me a Surprising Lesson About AI and Creativity

4. Forgetting accessibility

Generating visually impressive content alone is not enough. To maximize the reach of your video, you also have to ensure that it’s accessible for as much of your audience as possible.

This includes going all-out on accessibility, including elements such as captions, voiceovers in multiple languages and audio descriptions.

Not only does this highlight your commitment to inclusivity for viewers who might have audio processing difficulties or visual impairments. It also caters to an international audience and silent scrollers — those 69% of people who watch online video with the sound off.

Fortunately, AI also offers options to facilitate this accessibility. Platforms like YouTube now offer not just auto-generated captions, which can be auto-translated into different languages. It also recently launched auto-dubbing, which has seen the reach of some channels that piloted it triple.

5. Going the AI-only route

Finally, the single most critical mistake that businesses make when it comes to AI video content is trying to go the AI-only route. That is, relying entirely on AI for the generation of video content, without extensive input from human video editors, strategists, or channel managers.

While AI is a fantastic tool to support video marketing, the human touch remains indispensable when it comes to creating content that stands out and resonates with your target audience.

Professional video editors can leverage AI tools to streamline their editing process, even seamlessly integrating AI-generated elements such as avatars, while preserving authenticity.

Similarly, YouTube channel managers can harness AI tools to better process vast amounts of analytics data. Interpreting that data and making actionable strategy suggestions, though, remains a human judgment call. Just like you can use AI transcription to lay the groundwork for custom captions — but you still need to double-check them, especially with respect to the names of your brand and products.

The bottom line? To successfully deploy AI — especially generative AI — for video marketing, human oversight and discretion are crucial. Use your judgment: Don’t blindly swim with the current of AI hype, but smartly ride the wave to success.

Generative AI has revolutionized video content. The barrier between having a vision for a video and implementing it is now lower than ever. For video marketers, this presents a conundrum. On the one hand, they can streamline their production process. On the other hand, there’s the threat of oversaturation and content inflation.

To effectively use AI for video marketing, businesses must avoid common pitfalls that result in bland, unoriginal content that will disappear in the waves of AI content already crashing over social media platforms.

Leadership would be simple if choices always fell neatly into categories of right or wrong. But the reality of leadership is far more complex. Leaders rarely deal with certainty; instead, they face ambiguity, competing priorities and incomplete information. Every decision they make sends ripples across teams, customers and stakeholders, sometimes in ways that are impossible to measure immediately.

In this kind of environment, hesitation becomes dangerous. Leaders who wait for perfect clarity often wait too long. Opportunities close, problems escalate and competitors move forward. The objective of sound leadership should not be to guarantee flawless decisions but to act decisively with the best information available — and then to commit with conviction.

Moving past “right” and “wrong”

One of the most common mistakes leaders make is treating decisions as binary: either success or failure, win or lose, right or wrong. This rigid mindset creates unnecessary pressure and narrows perspective. It also blinds leaders to the nuanced reality that most choices exist in shades of gray.

Consider a leader deciding whether to cut costs during an economic downturn. There is no single “right” answer. Aggressive cuts may protect short-term cash flow but risk damaging morale and brand reputation. On the other hand, preserving spending may support long-term innovation but create immediate financial strain. Neither path is entirely right or wrong. They are trade-offs that must be evaluated against the organization’s mission and values.

By moving beyond the illusion of perfect answers, leaders open themselves to broader thinking. They can weigh not just immediate outcomes but also cultural impact, strategic alignment and long-term resilience. The most effective leaders do not ask, “What is the right choice?” but rather, “Which path best advances our mission given the realities we face today?”

Related: How to Lead With Clarity — Even When Everything Feels Ambiguous

Letting data guide the way

When things are uncertain, data works like a compass. It may not eliminate all confusion, but it helps by showing patterns, probabilities and possible outcomes. Leaders who rely on data can make clearer choices and avoid mistakes that come from guessing or reacting too quickly. As economics professor Emily Oster said, “The key to good decision making is evaluating the available information — the data — and combining it with your own estimates of pluses and minuses. As an economist, I do this every day.”

For example, market signals during periods of disruption are often contradictory. One set of metrics may show declining customer engagement, while another points to new opportunities emerging in niche markets. By analyzing the data carefully, leaders can see beyond the noise and recognize the underlying patterns.

It’s just as important to listen to the team’s perspective. People working directly with customers or daily operations often spot problems, feedback or risks before leaders do. When leaders include these insights in their decisions, they gain a clearer picture and also make the team feel more involved and valued.

Embracing risk without recklessness

No decision in uncertain times comes without risk. Leaders who try to eliminate risk end up paralyzed, while those who ignore it entirely veer into recklessness. The challenge lies in striking a balance.

This balance begins with recognizing that inaction carries its own risks. Delaying a decision can mean missed opportunities, deteriorating conditions or eroded trust. Leaders must weigh the cost of doing nothing against the risks of moving forward.

Mapping best- and worst-case scenarios is a practical way to evaluate options. This process does not remove uncertainty, but it ensures leaders are making deliberate, transparent choices. It also provides teams with a clearer understanding of potential outcomes, helping them prepare mentally and operationally for what lies ahead.

Turning decisions into commitment

Perhaps the most overlooked element of decision-making is commitment. As Zig Ziglar mentioned, “It was character that got us out of bed, commitment that moved us into action.” Ambiguity may surround the decision, but once it is made (after proper analysis of data and proper use of frameworks), wavering creates confusion and erodes trust. A leader who changes direction at the first sign of resistance signals weakness, leaving teams uncertain about the future.

According to Professional Planner, “When a leader continuously changes their mind or reverses decisions, it creates confusion among team members, leading to frustration, as employees struggle to understand the direction they should follow.”

Commitment, however, should not be mistaken for stubbornness. Effective leaders recognize when conditions change and course corrections are necessary. What sets them apart is how they communicate. When leaders explain the reason for a pivot by outlining what has changed, why it is essential and how it connects to the organization’s purpose, they can maintain credibility even while changing direction.

Related: Knowing When — and How — to Pivot Is Key to Your Business’ Survival. Here’s What You Need to Do.

Conclusion

Leading in uncertain times demands the courage to move beyond the false comfort of right and wrong. Decisions cannot be reduced to absolutes. They must be framed in terms of alignment with mission, evidence-informed reasoning and carefully managed risk.

The leaders who thrive are those who step into ambiguity without hesitation. They embrace data and team insights, weigh risks with discipline and commit with clarity. Their decisions are not flawless, but they are effective because they move the organization forward while staying true to its purpose.

Ultimately, leadership is not about finding the perfect answer. It is about creating progress in the gray zone.

Leadership would be simple if choices always fell neatly into categories of right or wrong. But the reality of leadership is far more complex. Leaders rarely deal with certainty; instead, they face ambiguity, competing priorities and incomplete information. Every decision they make sends ripples across teams, customers and stakeholders, sometimes in ways that are impossible to measure immediately.

In this kind of environment, hesitation becomes dangerous. Leaders who wait for perfect clarity often wait too long. Opportunities close, problems escalate and competitors move forward. The objective of sound leadership should not be to guarantee flawless decisions but to act decisively with the best information available — and then to commit with conviction.

Anthropic recently conducted a research study of its own engineers to determine how AI is transforming work — and found that AI tools are boosting productivity while sparking concerns about skill atrophy, reduced human collaboration and job loss.

Anthropic shared the findings of its August research study in a blog post published on Tuesday. The startup, last valued at $183 billion in September, surveyed 132 of its own engineers, conducted 53 detailed interviews and studied internal use data for Claude Code, its coding tool. The study sought to get a better understanding of how AI use is changing work at Anthropic, a startup with 3,000 employees.

“We find that AI use is radically changing the nature of work for software developers, generating both hope and concern,” the researchers wrote in the blog post.

Engineers reported getting more work done with the help of AI and being able to succeed at a variety of technical tasks beyond their usual expertise. Workers could fully delegate up to 20% of their tasks to Claude, mainly tedious work.

Related: Anthropic Is Now One of the Most Valuable Startups of All Time: ‘Exponential Growth’

Employees were able to tackle a wider range of tasks, but were concerned that they could lose more specialized technical competence in favor of breadth. Many worried about losing deeper coding skills, like writing and critiquing code, with one employee noting in an interview for the study that it is more difficult to learn when coding assistants like Claude are available to readily code solutions.

Anthropic CEO Dario Amodei said in March that AI will write all code for software engineers within a year. “On the jobs side of this, I do have a fair amount of concern,” he said that month at an event.

Some Anthropic engineers are also worried about their jobs, expressing genuine uncertainty about the future. In the study, one employee noted that it was “hard to say” what their job might look like in the next few years. Others were “optimistic in the short term” but predicted that “AI will end up doing everything” in the long run.

One employee said in the report: “It kind of feels like I’m coming to work every day to put myself out of a job.”

Related: The CEO of a $183 Billion AI Startup Says There’s a ‘Need to Warn the World’ About AI Taking Jobs

The addition of AI also means that workplace social dynamics are undergoing significant changes. Employees often go to Claude with questions, rather than their peers, resulting in fewer opportunities for mentorship and collaboration.

A separate report on AI in the workplace, released in January by McKinsey, found that nearly all employees (94%) report familiarity with AI tools and the majority of workers (59%) describe themselves as optimistic about AI. Some of the top concerns cited by employees as risks associated with AI are cybersecurity, inaccuracy and workforce displacement.

Anthropic recently conducted a research study of its own engineers to determine how AI is transforming work — and found that AI tools are boosting productivity while sparking concerns about skill atrophy, reduced human collaboration and job loss.

Anthropic shared the findings of its August research study in a blog post published on Tuesday. The startup, last valued at $183 billion in September, surveyed 132 of its own engineers, conducted 53 detailed interviews and studied internal use data for Claude Code, its coding tool. The study sought to get a better understanding of how AI use is changing work at Anthropic, a startup with 3,000 employees.

Amazon believes consumers have a need for speed. The company just started testing 30-minute delivery in Seattle and Philadelphia through a pilot called Amazon Now. It’s shipping thousands of everyday items — from diapers to electronics — in half an hour or less.

Workers pick and pack items at nearby facilities before Amazon Flex drivers whisk orders away, aiming to leave within two minutes. It’s fast, sure, but Walmart is still in the lead. With more than 4,600 stores, Walmart can reach 95 percent of U.S. households in under three hours, and some orders arrive in minutes.

Analysts say Amazon’s ultrafast strategy may not be realistic. The infrastructure required, including more warehouses, more drivers, and more inventory, could increase. At a certain point, consumers may prefer savings over a sprint.

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Chick-fil-A Serves Up Chicken and Waffle Sandwiches—But Only in Two Cities

^Chick-fil-A

Customers asked for it, and they got it. Chick-fil-A is testing a chicken and waffle sandwich. The new item swaps the classic bun for maple-flavored waffles and adds fried chicken, honey butter and bacon, plus a cup of syrup for dipping. There’s also a spicy version.

For now, only two cities are getting the test run. Baltimore will offer both breakfast and all-day sandwiches, while San Antonio will offer breakfast only. Prices range from about $5 for the breakfast version to nearly $9 for the spicy all-day option.

Early reviews are enthusiastic. TikTok users praised the sweet-and-savory combo, though some wished the waffles were crispier.

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Macy’s Just Had Its Best Quarter in Years. Don’t Throw a Parade Just Yet.

^{Adam Gray/Bloomberg via Getty Images}

Macy’s shocked Wall Street with its strongest sales growth in three years and raised its full-year outlook after beating earnings estimates for the third straight quarter. The retailer credits sharper merchandising, increased staffing, and redesigned “First 50” stores — a strategy now rolling out to more than a third of its remaining locations.

But the celebration comes with a warning. Macy’s says consumers are growing more selective, and higher tariffs will keep pressuring prices heading into the holiday season. The company has already shuttered dozens of underperforming stores and expects more closures as part of its turnaround.

Despite the good news, investors weren’t impressed. Macy’s shares fell in premarket trading. CEO Tony Spring said the company is taking a cautious view of the holidays. The brand is betting that better stores and broader price points can win shoppers back.

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Gas Dips to $2.99 Nationwide. Trump Says Prices Will Continue to Slide.

^{Photo by Jeremy Hogan/Getty Images}

For the first time in more than four years, gas prices have dropped below $3 a gallon, according to AAA. The national average for regular gas hit $2.99, with several Southern and Midwestern states seeing prices as low as $2.40.

President Donald Trump says the slide isn’t over. He predicted prices could fall to $2 a gallon and possibly “crack” that level, crediting increased domestic production and a push to rebuild the Strategic Petroleum Reserve.

Energy officials argue that cheaper fuel will put more money back into consumers’ pockets, though critics warn volatile markets could quickly reverse course.

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What’s the Most Popular New College Major? AI

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AI isn’t just taking over the business world; it’s now Big Man on Campus. Universities across the country are launching AI majors to meet the huge demand from students who want to build the next big thing.

Schools like the University of South Florida, UC San Diego and SUNY Buffalo have rolled out new AI programs. MIT’s “AI and decision-making” major has already become the institution’s second-most-popular field of study. More than 3,000 students enrolled in South Florida’s brand-new AI college this semester alone.

The boom comes as tech giants pour billions into AI, and students see the field as a faster path to jobs than traditional computer science.

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Amazon believes consumers have a need for speed. The company just started testing 30-minute delivery in Seattle and Philadelphia through a pilot called Amazon Now. It’s shipping thousands of everyday items — from diapers to electronics — in half an hour or less.

Workers pick and pack items at nearby facilities before Amazon Flex drivers whisk orders away, aiming to leave within two minutes. It’s fast, sure, but Walmart is still in the lead. With more than 4,600 stores, Walmart can reach 95 percent of U.S. households in under three hours, and some orders arrive in minutes.

Analysts say Amazon’s ultrafast strategy may not be realistic. The infrastructure required, including more warehouses, more drivers, and more inventory, could increase. At a certain point, consumers may prefer savings over a sprint.

The AI market is crowded with promises: major players across industries are dominating headlines with bold claims and polished messaging. But in my 25-plus years of experience in the healthtech sector, I’ve seen time and time again that the products customers tend to stick with are those presented transparently, honestly and without surprises.

When we began building our own AI-powered solution (an ambient listening and note-taking tool designed to help providers reclaim their time), we knew we couldn’t compete based on bold claims. We focused on telling the truth instead. How do you actually use the tool? How will it change your day-to-day experience when you start work in the morning?

This meant being transparent about our tool’s capabilities, limitations and pricing. An approach that’s becoming less and less common in the health IT industry. We took that route because our goal was to build lasting trust in a product that our current and future customers truly need. And that didn’t just make us stand out. It made customers lean in closer.

Clarity is the fastest way to build trust

The current conversation around AI is saturated and often abstract, which means it can be a challenge for practice decision-makers to translate buzz into a practical strategy. Recent reports show that more than half of healthcare organizations still don’t have a clear AI strategy, and only about 30% of pilot programs reach full implementation. That gap often starts with unclear expectations; if teams don’t see the promised benefits, they’ll move on quickly.

In software and tech, setting clear expectations is one of the most overlooked parts of product design. For the healthtech industry in particular, the urgency to create clarity is even more essential. Most physicians are burnt out and dealing with incredible challenges, and while they might be an extreme compared to other industries, they’re also a clear illustration of just how little time and attention the average buyer has to offer today.

That’s why so many companies take a “bigger is better” approach to communication about their products, hoping flashy ad copy and unscrupulous promises will cut through the noise and catch customers’ attention.

In my experience, a more direct approach is the one that really builds trust, not just getting someone through the door, but keeping them coming back through service and customer experience. In our case, we made an early decision to speak plainly about what our AI tool is made to do, the tasks it can handle and just as importantly, what it can’t. That level of clarity wasn’t about underselling the product. It was about building confidence. And it worked in ways that even surprised us.

Related: I’m Extremely Competitive — Here’s How I Keep It from Becoming a Problem in my Business

Empathy is the best foundation for product decisions

Running a healthcare technology company for nearly three decades has given me an empathy-driven approach to creating and selling products. And the more time I spend around clinicians, the more I see where tools really help and where they quietly add burden. That experience shaped every decision we made when venturing into our first AI-powered product.

Rather than chase trends, we built around patterns we had already seen. Clinical note-taking isn’t just an annoying task. It’s often the most burdensome administrative hurdle for providers. We made early development decisions by observing how providers moved through their day. What slowed them down. What actually got used. Rather than what looked the shiniest and most appealing on a list of product features.

We also brought frontline users into the process early, whose feedback allowed us to course-correct, optimize and build something genuinely worthwhile. That translated into a product that didn’t need gimmicks to sell, healthcare providers could see the value at one glance.

One of the most clear examples of this came from Dr. James Brewer, M.D., who’d spent years relying on paper charts alone because he feared a typical EHR would only add time to his workflow.

“Having an e-scribe was the only way I was willing to make that transition,” he explained. “[This technology] will only get better and better as it learns how I practice and chart, and I am confident that I will be using it for many years to come.”

Other customers saw immediate, measurable improvements in their workload. For one user, documentation time decreased by 70%. That meant 12+ hours per week spent working on notes after hours disappeared overnight, providing more time to focus on rest, fun and family, the things every human ultimately wants to focus on. Those results aren’t marketing claims or projections; they’re the direct outcome of building a tool around real workflows, real pain points and real customer needs.

Related: Who’s Your Biggest Threat? These 4 Questions Hold the Answer — and It’s Not Who You Think

Why we will always choose trust and service over hype

We don’t aim to match the vast resources of the largest AI giants in our vertical. As a bootstrapped team, our goal is not to outspend the competition but to out-trust and out-service them, and we do it by prioritizing transparency and empathy. That focus has allowed us to build a competitive ambient AI solution that stands on merit first and marketing second.

This approach relies on a fundamental belief that clarity matters more than cleverness, and service more than hype. We delivered a tool that genuinely supports our customers, rather than simply adding to the noise. That’s not just helping us sell one exciting new product, but building long-term trust in our entire suite of medical practice software.

As AI is integrated more deeply into the healthcare system, the industry’s most significant test will not be technical capability, but ethical restraint. The pressure to oversell is immense, but we believe that when the dust settles, the only thing that will matter is who stays honest and provides real value to the people who use their product every day.

The AI market is crowded with promises: major players across industries are dominating headlines with bold claims and polished messaging. But in my 25-plus years of experience in the healthtech sector, I’ve seen time and time again that the products customers tend to stick with are those presented transparently, honestly and without surprises.

When we began building our own AI-powered solution (an ambient listening and note-taking tool designed to help providers reclaim their time), we knew we couldn’t compete based on bold claims. We focused on telling the truth instead. How do you actually use the tool? How will it change your day-to-day experience when you start work in the morning?

When his young daughter’s eczema worsened, Brian Keller tried everything modern parenting prescribes. Nothing worked. Desperate, he replaced the ordinary showerhead in their bathroom with a filtered one. Within a couple of days, his daughter had perfectly clear skin. The speed of the change forced him to go online searching for a reliable filtration system. But what he found surprised him. “Pretty much one plastic product after the next,” he says.

He called his longtime partner, designer and engineer Charlie Carlisle. “I think there’s a pretty big opportunity here to build a business like Dyson in water filtration,” he said. Little did they know they’d spend the next three years building a filtration system piece by piece, rejecting shortcuts.

The result is Rorra — a science-backed water filtration company offering a countertop unit and filtered showerhead. Both run tap water through a multilayer carbon and media setup designed to reduce chlorine, disinfectant byproducts, PFAS, and 50+ other contaminants. In less than a year on the market, the company has placed over 10,000 drinking-water systems in homes across the country and reached an eight-figure run rate.

Related: How Can a Working Mother Be Successful These Days? 6 Strategies for Success as an Entrepreneur and Parent

The problem with tap water

While studying U.S. water infrastructure, the founders discovered some sobering stats. The average tap water pipe is 45 years old, and many are more than a century old. Chlorine and other chemicals, including lead, are in almost all American tap water, including compounds linked to increased risks of kidney and bladder cancer.

But replacing failing pipes across the country would cost more than a trillion dollars and require digging beneath major cities. The solution was to offer a reliable way for people to clean their water at home.

Built to last and be seen

The founders knew that if people were going to clean their water at home, the system had to be sleek. The flimsy plastic products Keller first saw online weren’t cutting it. “Everything we build is designed to last for years. We’re not building cheap, consumer products with engineered obsolescence,” Keller says.

The Rorra Countertop looks more like a piece of modern kitchen equipment than a filter—medical-grade stainless steel and sturdy enough to pass for something you’d find in a craft brewery.

Perhaps unsurprisingly, the design appeals to male consumers. “Over 50 percent of our customers are male,” Keller says. “We didn’t even really project that initially.” The product suggested something protective and strong, a kind of household sentinel.

For this reason, Keller and Carlisle designed the Rorra Countertop system to live where people could see it. Most filtration devices hide under sinks and get forgotten. They wanted the opposite. “A product that people are going to be proud to put on their countertop,” Keller says.

Related: Jason Momoa is Still Playing Aquaman… Just Not On Screen — How the Movie Star is Making Waves Against Plastic Waste With Boomerang Water

A flood of orders

The response came fast and furious, which was good and bad. When the first units shipped, the founders braced for modest demand. Instead, “customer service inquiries went overnight from like a ten a day to hundreds a day. We needed to scale our support team extremely quickly to keep up,” Carlisle said.

They ran out of stock for weeks. Delays stretched to two months. But amid the chaos, they chose transparency over panic. “My phone number was on the credit card statements of every single customer,” Keller says. When a subscriber called late at night to complain about a charge, he picked up. “I’m the CEO,” he would tell them, before walking them through the benefits of the system. The response built a strange form of loyalty.

Popularity has grown organically. Athletes, doctors, and creators bought the product on their own, then reached out. One of the company’s biggest boosts came from partnering with Dr. Andrew Huberman, the Stanford neuroscientist and host of the hugely popular Huberman Lab podcast. “We’re definitely seeing a direct uplift in sales and people buying from his landing page,” Keller says.

It’s votes of confidence like this that prove their strategy was a good one. “It took three years versus probably one year that it could have taken us to launch,” says Carlisle. “But there’s a lot of benefits to us having something that’s truly unique in the space.”

When his young daughter’s eczema worsened, Brian Keller tried everything modern parenting prescribes. Nothing worked. Desperate, he replaced the ordinary showerhead in their bathroom with a filtered one. Within a couple of days, his daughter had perfectly clear skin. The speed of the change forced him to go online searching for a reliable filtration system. But what he found surprised him. “Pretty much one plastic product after the next,” he says.

He called his longtime partner, designer and engineer Charlie Carlisle. “I think there’s a pretty big opportunity here to build a business like Dyson in water filtration,” he said. Little did they know they’d spend the next three years building a filtration system piece by piece, rejecting shortcuts.

How well do top companies pay their employees? Federal filings from this year reveal the salary ranges that companies from Amazon to Microsoft use to compensate their staff, from software engineers to data scientists.

The data is drawn from thousands of documents that these companies filed with the U.S. Department of Labor this year while onboarding foreign workers through the H-1B visa program. The visa allows highly skilled foreign workers to work in specialized occupations in the U.S. for up to six years. The filings only reveal base annual salaries and omit stock options, signing bonuses and other perks.

According to these filings, Microsoft is paying software engineers from $82,971 to $284,000 in base salary. Google pays the same role from $109,180 to $340,000, while Meta pays anywhere from $120,000 to $480,000.

Related: These Tesla Jobs Pay Up to $318,000 — And You’ll Have Meetings With Elon Musk

Meanwhile, Amazon is paying software engineers in its Amazon Web Services cloud division as much as $185,000, while defense company Palantir pays the same profession anywhere from $155,000 to $240,000 in base pay.

Companies from Amazon to Walmart pay other roles as follows, according to the H-1B filings.

Amazon

• Applied Scientist: $83,491 to $260,000
• Business Analyst: $79,518 to $143,100
• Data Engineer: $70,262 to $236,344
• Product Manager: $109,782 to $200,000
• Program Manager: $81,600 to $162,700
• Quality Assurance Engineer: $86,320 to $185,000

Read more here.

Apple

• Data Scientist: $105,550 to $322,400
• Electronics Engineer: $108,160 to $264,200
• Hardware Developer: $124,942 to $293,800
• Machine Learning Engineer: $143,100 to $312,000
• Professional Services Consultant: $100,200 to $258,700
• Tools and Automation Engineer: $105,602 to $293,800

Read more here.

AT&T

• Lead System Engineer: $139,750 to $180,000
• Principal Data/AI Engineer: $163,737 to $197,464
• Senior Data/AI Engineer: $138,699
• Senior Data Analyst: $134,322
• Senior Data Scientist: $148,043
• Senior Tech Product Manager: $124,689 to $156,000

Read more here.

Disney

• Associate Ride Control Software Engineer: $134,700
• Decision Scientist, Worldwide Services: $119,028
• Financial Accounting Manager, Hulu: $127,570.79
• Lead Data Engineer, Streaming: $188,875.73
• Senior Data Analyst, Hulu: $139,404.80
• Senior Data Engineer: $177,322.31

Read more here.

Google

• Business Systems Analyst: $141,000 to $201,885
• Customer Engineer: $85,009.60 to $228,000
• Data Scientist: $133,000 to $260,000
• Electrical Engineer: $119,000 to $203,000
• Program Manager: $125,000 to $236,000
• Security Engineer: $97,000 to $233,000

Read more here.

Meta

• AI Research Scientist: $179,481 to $232,000
• Data Analyst: $168,000 to $204,000
• Design Engineer: $185,000 to $256,270
• Research Scientist Manager: $258,524
• Senior Product Manager: $224,323
• Software Engineering Manager: $219,978 to $328,000

Read more here.

Microsoft

• Business Program Manager: $102,380 to $195,100
• Cloud Network Engineer: $122,700 to $220,716
• Customer Experience Engineer: $126,422 to $239,585
• Data Analyst: $132,385 to $205,000
• Electrical Engineer: $138,995 to $247,650
• Research Scientist: $146,054 to $208,000

Read more here.

Palantir

• AI Machine Learning Researcher: $210,000 to $250,000
• Deployment Strategist: $120,000 to $192,000
• Product Designer: $135,000
• Quality Engineer: $136,000
• Technical Program Manager: $165,000

Read more here.

Walmart

• Distinguished Architect: $184,827 to $338,000
• Senior Product Manager: $121,000 to $286,000
• Senior Design Researcher: $142,002 to $234,000
• User Experience Design Senior Manager: $183,227 to $286,000
• Software Engineering Director: $190,486 to $312,000
• Product Management Director: $201,323 to $338,000

Read more here.

How well do top companies pay their employees? Federal filings from this year reveal the salary ranges that companies from Amazon to Microsoft use to compensate their staff, from software engineers to data scientists.

The data is drawn from thousands of documents that these companies filed with the U.S. Department of Labor this year while onboarding foreign workers through the H-1B visa program. The visa allows highly skilled foreign workers to work in specialized occupations in the U.S. for up to six years. The filings only reveal base annual salaries and omit stock options, signing bonuses and other perks.