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At an event for pharmaceutical executives, biotech founders, and researchers on Tuesday, Anthropic announced Claude Science, a major new product intended to support scientific research in the same way that Claude Code supports software engineering. Like Claude Code, Claude Science can autonomously carry out meaningful work when given concise, high-level instructions, and it has access to tools that make it particularly useful for research in computational biology and drug development. Along with launching and previewing Claude Science, which is now available to all paid Claude subscribers, Anthropic also announced that it will be using the product to pursue some of its own research into drugs for rare, neglected diseases.

This is not Anthropic’s first foray into AI for science. In October, the company released plug-ins that help Claude make use of scientific software and databases under the heading “Claude for Life Sciences.” But unlike this earlier release, Claude Science is a full-featured, standalone product. Anthropic’s decision to elevate Claude Science to the same rank as Claude Code and Claude Cowork indicates that the company is taking AI’s scientific applications very seriously—or at least wants to give the impression that it is.

“It represents how important this is to our mission that this is right up there with Claude Code and Claude Cowork as the next really significant product that we’re releasing,” says Eric Kauderer-Abrams, Anthropic’s head of life sciences. “Our mission is to develop AI that serves humanity’s long-term well-being, and we believe that by far the greatest opportunity to do that is in the life sciences.”

For the past decade, one company—Google DeepMind—has been at the vanguard of AI for science. CEO Demis Hassabis and researcher John Jumper won the Nobel Prize in chemistry for their work on the company’s AlphaFold model, and DeepMind has also made major contributions to meteorology, materials science, and a variety of other disciplines. But in the past several months, the fast-advancing frontier of AI progress seems to have left DeepMind in the dust. When it comes to coding, which has become the most lucrative use case for LLMs, DeepMind is stuck playing catch-up.

Though Claude Science could in principle assist with any area of scientific research, it seems designed and marketed as a tool for molecular and cellular biology, and for drug development in particular. It can interface with various tools used in genetics, chemistry, and protein biology, all of which could come in handy for researchers on the hunt for new drugs.

And Anthropic isn’t leaving all that work to the pharma companies and university labs. Armed with Claude Science, it will be pursuing its own research into drug candidates for neglected diseases—both to help move science forward and to gain a clearer sense of how Claude Science works in the real world.

There are obvious humanitarian reasons to prioritize drug development when creating a general-purpose scientific research tool, and AI industry leaders often cite curing disease as a major potential upside of the technology. But it’s also notable that pharmaceutical companies have far deeper pockets than academic researchers. Anthropic says it’s set to see its first profitable quarter, and if major new contracts with pharmaceutical companies are forthcoming, they could help ensure it stays profitable as the tokenmaxxing craze dies down—something that’s ever more important as an IPO approaches later this year.

The strategy frameworks that most executives rely on were forged in what we might call the “stuff” economy. Michael Porter’s seminal five forces model the resource-based view and Blue Ocean strategies were the frameworks made sense in a world where most corporate value resided in tangible things: factories, distribution networks, inventory, and equipment. In 1975 roughly 83% of the assets on the books of Fortune 500 companies were tangible. Strategy was, in essence, about identifying opportunities or defending positions in physical space.

The shift has been accelerated by what the economic historian Carlota Perez calls a technological revolution—the kind of once-in-a-half-century transformation that reshapes not just technology but the entire logic of how economies work. She identifies five such revolutions in the history of capitalism, each driven by a cheap input with economy-wide applications: the original industrial revolution; steam and railways; steel and electricity; oil, automobiles, and mass production; and now information and telecommunications.

Each revolution follows a pattern. In the disrruption and installation phases, financial capital rushes in, bubbles form, and inequality surges. Then comes a turning point—a period of crisis and institutional adjustment. Finally, in the deployment phase, the new paradigm takes hold, institutions adapt, and a new age of broad-based prosperity becomes possible.

We are at a turning point right now. The symptoms are unmistakable: massive income inequality, political instability, widespread dissatisfaction, and an old strategic paradigm whose productivity has been exhausted but has not yet been replaced. The defining characteristic of this transition is what the author calss dematerialization: Value creation is shifting decisively from physical stuff to digital services, coordinated ecosystems, intangible assets, and experiences.

Strategic centering is deliberately choosing one organizing principle to guide resource allocation, opportunity selection, and organizational identity in a dematerializing world. It involves answering a simple but profound question: What are we really about?

The author’s research has identified five types of strategic centering

1. Mission.  What problem keeps us up at night?  Ideal for the large and enduring problem; the technologies for addressing it are in flux.  Risk could be mission drift.
2. Customer.  Whose needs do we understand better than anyone?  Suitable when customers have complex, evolving needs that cut across industries.  But the risk is it could conflict with other corporate goals.
3. Technology.  What capabilities do we have that are transferable across domains?  Good for companies having capabilities those are deep, on a long and exciting technological trajectory, and applicable in multiple markets.  Technological narcissism (failing to connect technological discoveries to real customer jobs to be done) could be the risk.
4. National Ecosystem.  What system are we essential to?  Good for the venture requires scale and patience beyond private capital; geopolitics create strategic value.  Major risks are: geopolitical strategic constraints; uncompetitiveness globally.
5. Friction Erasure.  What’s still absurdly hard in our space?  The domain has legacy complexity, regulatory fragmentation, and poor customer experience.  Scope creep (friction is everywhere).

What do value, desirability, and exclusivity mean to luxury consumers? Increasingly, the answer depends on where they live.

As the luxury market emerges from a period of slower growth, consumers in the United States and China will play an outsized role in determining which brands emerge as leaders. These two countries represent the industry’s most significant concentration of luxury demand: The United States remains the world’s largest luxury market by sales, while China is expected to be among its fastest-growing through 2030. Overall, the global luxury market is projected to reach $700 billion by the end of the decade, growing 4 to 6 percent annually.

Drawing on a survey of more than 2,000 luxury clients in the United States and China, and extensive interviews with clients across both markets, this year’s State of Luxury report examines client expectations across four dimensions—desirability, exclusivity, moments, and discovery—and what brands must do to remain relevant in a more fragmented luxury landscape.

If status doesn’t drive purchases, what does?  Consumers’ desire for status symbols, or highly covetable and visible goods, has long supported growth for luxury labels. That’s beginning to change.  Across both the US and Chinese markets, emotional connection now ranks as a top driver of brand desirability, ahead of traditional luxury markers such as craftsmanship, heritage, and exclusivity. Consumers are looking for brands that reflect their identity, values, and aspirations, rather than simply signaling wealth or status.

When anyone can buy a luxury product, what makes it exclusive?  Consumers are becoming skeptical of scarcity for scarcity’s sake. Being recognized by the right people—the “if you know, you know” crowd—is more important than being recognized by everyone.  Across both the United States and China, relatively few consumers say that a product being difficult to find is what motivates them to pay full price. Instead, exclusivity is tied to recognition, access, and experiences that feel earned rather than engineered.

How does a brand sell goods when experiences become luxury’s biggest competitor?  Consumers are evaluating their relationship with luxury according to the moments and memories that may be linked to a brand.  The shift is visible in how consumers say they would spend additional discretionary income. Travel ranks as the top choice in both markets, ahead of any luxury product category. But the broader implication is not that consumers prefer vacations to handbags. It is that they increasingly associate luxury with experiences that feel personal, memorable, and difficult to replicate.

What happens when brands lose control of discovery?  Consumers are using AI tools, resale platforms, creators, and peer networks to research, compare, and validate products before they ever enter a boutique. The path to purchase is becoming more intentional, more informed, and more influenced by platforms that brands do not fully control.  AI is accelerating this shift. Across both the United States and China, consumers most frequently use AI during the exploration phase of the purchase journey to understand product differences, compare options, and receive personalized recommendations.

In tomorrow’s luxury market, products may be the easier part of the equation for brands to get right. Across the United States and China, consumers are redefining what luxury should deliver: more emotional meaning, insider recognition, memorable experiences, and rewarding discoveries. The next generation of luxury leaders will be those that deliver on those intangible, irreplaceable elements that consumers value as much as the products themselves.

“Professionalism” encompasses the broad set of shared beliefs and expectations about how people within an industry or workplace should interact with one another.

Our conversations about professionalism tend to proceed like a garden that has been allowed to grow without controlling for weeds or pests and is then subject to endless debate over whether the result is “good” or “bad.” But that has never been the right conversation, because context matters: Are your organization’s professional norms good or bad for your particular workplace?

While some norms are common to many workplaces — such as following through on commitments, treating colleagues with respect, and communicating appropriately — professionalism has no single definition. It varies across regions, cultures, sectors, and industries. But as a set of norms for differentiating wanted (“professional”) from unwanted (“unprofessional”) behaviors, professionalism is inherently about excluding some for the benefit of the whole. When defined well and fairly, professional standards can effectively guard against harmful behavior while creating a shared sense of identity among people from a range of backgrounds, compounding their individual efforts into collective impact. But, defined poorly, professionalism can divide and distract teams, systematize active discrimination, and discount — or even incentivize — detrimental behavior.

Every leader has the responsibility to create a version of professionalism designed for their unique workplace context. By incentivizing helpful behaviors that bring the best out of every person and disincentivizing harmful behaviors that impede performance, leaders can design a bespoke code of professionalism that serves people rather than functioning as an obstacle. Here’s how to lead a collaborative process of rethinking their workplace’s approach to professionalism, regardless of geographic region, sector, or industry.

Define success for your unique context. Take a step back to see the bigger picture. Ask your workers and key partners to share with you what they believe success looks like for your workplace.  Defining the outcomes that matter most to your organization grounds everything you do in a “why” that goes deeper than “because a leader said so.”

Identify deal-breaker behaviors. Imagine an employee who is highly effective at delivering results — but the way they do it is egregious enough that it compromises their own, or possibly their entire team’s, success.  But deal-breaker behaviors aren’t universal and may vary across cultures or industries. The practice of identifying your organization’s particular deal-breakers is powerful precisely because it can reveal cultural norms or shared beliefs so deeply held that they’re practically invisible. Discuss this as a group to identify where your key partners might agree or disagree about what behaviors constitute deal-breakers.

Identify the minimal expectations required for success. This is the most uncomfortable step. If professionalism is up to us to define, we might want to define it aspirationally, as the highest expectations we can set to be the best version of ourselves.  But no person is perfect in any setting, to say nothing of the workplace. As a pragmatic tool, professionalism is best used to define the minimum standards of behavior that we expect from our colleagues, one step above our deal-breakers.  

Understand the gap between expectations and reality. Ask your key partners what behaviors are really rewarded or punished in practice. You may find that aspirational norms have unintended consequences.  Gaps have a real cost, not just to people but in terms of your ability to align your actions with how you defined success in Step 1. If these gaps represent behavioral shortcomings of your starting point of “passive professionalism,” closing them will help you establish a far more functional and beneficial definition of professionalism, tailor-made for your context and directly linked to your organization’s success.

Incentivize what you want, and discourage what you don’t. Professional norms are not rigid policy but a means to an end. Your particular definition of professionalism can help ensure that everyone in your workplace is rowing in the same direction, is protected from abusive and harmful behaviors, and can expect the same standard of mutual respect throughout the workplace.  If old norms are no longer contributing to success, or new norms are needed to reach success — or both — it’s not enough to simply declare a policy change in an email or during a team meeting. Leadership has to align their behaviors — particularly their informal rewards and rebukes — with the professional norms they’ve defined.

Professionalism will always be a potential source of debate as times change and work evolves. Be open to revisiting what you consider professional behavior and asking yourself whether your norms are most effectively serving their purpose: empowering your people. When in doubt, it’s time to reset.

As AI automates routine tasks and redefines entire roles, the tools are creating a new workplace survival test—one where workers must evolve, or risk being left in the dust. Palo Alto Networks CEO Nikesh Arora warns that 90% of employees at big companies aren’t AI savvy—and it could determine the fate of their careers in the new world.

And the leader of the $278 billion cybersecurity firm is already witnessing the fallout. Hiring has screeched to a halt as companies slash thousands of staffers in the name of AI—and tech-savvy talent will have the best shot at career success.  It’s estimated that 39% of business leaders have already made employees redundant due to leveraging AI, according to a 2025 Orgvue study. 

The other way employers are broaching the issue is by gradually rebuilding their teams with AI-fluent workers. In leading Palo Alto into the next era, Arora says he’s hiring “only through” hackathons to bolster tech skills among his 21,000-strong workforce.   CEOs say it’s sink or swim in the AI era 

The Palo Alto CEO’s forecast reflects a growing concern among business leaders: the AI era will be a sink-or-swim moment for workers, with adaptability becoming the new career currency. No one is immune from the tech transformation—not even the CEOs calling the shots. 

Google leader Sundar Pichai has cautioned that no career path is fully protected from AI’s disruption, advising professionals to take matters into their own hands.  “People will need to adapt, and then there will be areas where it will impact some jobs. So, as a society, I think we need to be having those conversations,” Pichai told the BBC in a 2025 interview.

Micha Kaufman, the CEO of freelance marketplace Fiverr, also issued a warning to professionals: the tech is changing and automating every single role, all the way up to C-suite. And he echoes Pichai in also believing that his coveted, top job isn’t even safe from the AI shift. It’s essential that employees do more than simply talk about the tech—they need to experiment with it, develop their skills, and make it part of their everyday work.

And while Nvidia billionaire Jensen Huang doesn’t personally believe that AI can replace his role, he does recognize that competition comes with tech-savvy talent.  “It is unlikely most people will lose a job to AI,” Huang said during an interview at the Stanford Graduate School of Business earlier this year. “It is most likely that most people will lose their job to somebody who uses AI. And so we have to make sure that everybody uses AI.”

Reliable donors give nonprofits something every organization needs: the ability to plan ahead with greater confidence. But keeping those supporters engaged takes more than an automatic receipt or the occasional broad update. It requires clear, thoughtful communication that helps them see why their continued support matters.

When donors feel genuinely appreciated, they’re more likely to stay connected to the mission, deepen their commitment and understand the role they play in sustaining the work. Below, members of Forbes Nonprofit Council discuss the strategies they use to show regular donors the importance of their ongoing support and the impact that appreciation has on both supporters and nonprofits.

1. Treat Donors Like Mission Investors.  It’s so important to treat donors as mission investors while giving them real-time visibility into the impact they’re making. Sharing frequent, tangible updates focused on outcomes, not just activities, helps them clearly see how their investment comes to life. With transparency comes trust, and with trust comes long-term, mutually beneficial relationships that truly enrich the organization as a whole.
2. Build Long-Term Corporate Partnerships.  Approach corporate engagement as a long-term partnership, not a transaction. Nonprofits can tap into clear alignment on purpose and priorities to position themselves for deeper support. But alignment alone isn’t enough. Corporate leaders are increasingly looking for evidence of real impact, not just activity. When nonprofits demonstrate how their work drives meaningful and lasting change, they give companies a reason to invest in the long run.
3. Make Donors The Story’s Heroes.  According to one of the Experts, years ago, a development professional taught him to center donor communications around what the donor is accomplishing. The donor—not the nonprofit or executive director—is the hero of the story. The impact exists because of their generosity. When people see themselves reflected in the mission and its outcomes, they become more deeply engaged in the work.
4. Show Donors Where Their Dollars Go.  Focus on transparency. Too often, we don’t want to share with donors how dollars are spent, particularly as they relate to operations. But donors want to know how their gifts are used, including ensuring that there are staff to do the work. Lay out goals on how dollars are to be spent for the year, then report back to donors how dollars were actually spent. In some instances, it may result in additional gifts.
5. Let Real Impact Drive Connection.  We let impact do the talking. Regular donors receive real stories—a life changed, a barrier removed, a person who made it further because of a program we built together. When donors see themselves in the outcome, appreciation becomes connection, and connection drives retention.

The other advices are:  Position Donors As Agents Of Change; Tie Updates To Each Donor’s Giving; Share Specific, Human Outcomes; Tell Consistent Impact Stories; Invite Donors To See The Work; Reflect Donors’ Original Motivation; Recognize The Power Of Consistency; Pair Gratitude With Personal Updates; Send A ‘Just Because’ Note; Record A Quick Personal Video; Connect Supporters With Recipients; and Host Donor Appreciation Events.

You’ve landed a project and it’s about to start. It’s expected you’ll deliver on your promise of driving results for your client. Just don’t wait till the end of the engagement to showcase your success. Building a reputation as an independent consultant who’s worth the investment happens when you’re managing expectations at different touchpoints.

According to the author, across nearly two decades of his consulting business, he has made the mistake of overly focusing on the details of the work at the expense of orchestrating an intentional relationship with the client.  Accoring to the author he did the work to the best of his ability, but did any of it matter? He never heard from them again, and no surprise, as he didn’t think they had enough clarity as to the value he provided the team.  That’s a missed opportunity. They might have hired him again for a new project or referred him to their colleagues on a different team or at another firm if he was better at showcasing his impact.  Based on his experience he suggested four steps any consultant, coach, fractional leader, or solo business owner can take to build a reputation as a results-focused, client-centric partner that’s well worth the cost.

1. Deliver on the promise of your offerings as a starting point.  Whether that’s identifying security vulnerabilities as a cyber security consultant or decreasing the new-hire ramp up time as a fractional HR lead, getting the work done is priority one.  The floor here is you complete each deliverable or reach each milestone as laid out in your contract as no amount of communicating your impact will be beneficial without project delivery. Think of each project you’re working on as a two-way track of completing the required tasks and involving the client as a participant in delivering the final output.
2. Use your track record to illustrate the process.  It’s standard that you kick-off a client engagement by describing the process you’ll go through from start to finish. You want to make it easy for them to align with your workflow, so they know what you’ll need from them and when. To help make this explanation memorable and understandable for continued buy-in, reference how similar clients went through the process.  Referencing past customers with shared attributes makes the process more tangible and the outcomes verifiable as opposed to just points in a presentation or email.  Keep in mind, you’ve got to customize the work you’re doing for a new client and communicate this distinction, as even the impression of a one-size-fits-all approach could limit the perceived value of your offerings.
3. Send a weekly recap email for continued visibility.  For every client, it’s in your best interest to send the contact(s) that hired you a weekly recap email with a concise update on recent progress, roadblocks you’re up against, and next steps.  This recap gives them continued visibility into how the engagement is progressing, where they can offer assistance on a timely problem, and the ways you’re contributing at each stage.  Cumulatively they give clients confidence that the project is moving in the right direction, awareness of when complications arise and how they’ll be handled, and a documented track record of the support you provided.  
4. Find an immediate (meaningful) win.  Sometimes the big results come at the end of an engagement, which takes time, but don’t hold off until then to deliver tangible results. Small, meaningful wins early on and throughout the engagement can build immediate trust that you’re as valuable to the client as you’ve claimed.  Just don’t conflate a win with working on any task related to the project. You’re looking to solve an immediate challenge, move the project forward more quickly than expected, or pinpoint an unfolding issue or opportunity. In the best case scenario, you’re addressing an aspect of the work that the client mentioned directly. It shows you’re listening to their needs and adapting quickly.
5. Measure success by a client’s independence in addressing future challenges.  The best case scenario as a consultant is that your client does not become overly reliant on you for support, and is instead empowered by your guidance to be self-directed in the future.  Research indicates a successful consulting relationship is largely assessed by a client’s self-efficacy or enhancing the “clients’ intrinsic capabilities to navigate complex professional challenges independently.”

Entrepreneurship has always celebrated vision. Popular culture is filled with stories of founders who spotted opportunities before anyone else, built products the market didn’t yet know it needed and achieved success by seeing around corners. The implication is that great entrepreneurs possess a rare ability to predict the future.

The research tells a different story. Studies of entrepreneurial expertise suggest that successful founders are not distinguished by superior forecasting abilities. Rather, they develop ways of thinking that allow them to operate effectively when the future is unclear. Through experience, they become better at recognizing patterns, learning from setbacks, assessing risk and adapting to changing conditions.

This distinction matters because uncertainty remains one of the few constants in business. Markets shift, technologies evolve, and customer expectations change rapidly. In that environment, experience becomes more than a résumé credential. It becomes a strategic asset.

Great entrepreneurs don’t predict the future.  One of the most influential contributions to entrepreneurship research comes from Professor Saras Sarasvathy’s work on entrepreneurial, she found that expert founders approached decision-making differently from novices. Rather than focusing primarily on predicting future outcomes, they concentrated on what they could influence and control.  Less experienced founders often wait for more data, more validation or greater confidence before making important decisions. Experienced founders understand that those conditions may never arrive. They move forward with the information they have, learn from the results and make adjustments along the way. In fast-moving markets, the ability to adapt quickly is often more valuable than the ability to plan perfectly.

Experience turns information into recognizable patterns.  Across disciplines ranging from medicine and military strategy to chess and entrepreneurship, experts consistently outperform novices because they recognize meaningful patterns more quickly.  Experienced entrepreneurs build an internal library of observations accumulated through customer interactions, hiring decisions, negotiations, product launches and market cycles. Over time, they begin to see relationships that less experienced founders miss.  

Failure is only valuable when you learn from it.  Failure, by itself, has no educational value. What matters is how entrepreneurs respond to it.  Research on entrepreneurial learning has found that reflection plays a central role in transforming experience into expertise. 

Experience changes how entrepreneurs think about risk.  Popular stereotypes portray entrepreneurs as natural risk-takers. Research suggests that experienced founders are better described as risk managers.  As entrepreneurs gain experience, their relationship with uncertainty evolves. Rather than viewing decisions through a simple lens of success or failure, they become more sophisticated in assessing probabilities, trade-offs and downside exposure.   Experienced entrepreneurs rarely eliminate uncertainty. Instead, they structure decisions in ways that make uncertainty more manageable. 

The best entrepreneurs learn equally from both successes and setbacks.  Entrepreneurs often talk about learning from failure, but success can be equally instructive.  The challenge is that success often goes unquestioned, while failure invites scrutiny.  Research on entrepreneurial learning suggests that experienced founders develop a habit of examining both positive and negative outcomes. They look beyond results and ask what assumptions proved correct, what factors contributed to success and which lessons can be applied elsewhere. It becomes a framework for making better decisions in the future.