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2025-10-20 10:00:00| Fast Company

The difference between OpenAI and Anthropic has never been clearer. OpenAI is constantly in the news with a new consumer app or feature, and is being billed as the next great consumer tech platform. Most recently it made news by offering a social network around its Sora image generator, and even says it plans to allow NSFW content on ChatGPT. Anthropic, meanwhile, has chosen a different path. The company stresses that because it gets most of its revenues from businesses and developers, its not trying to capture the mass market, and its not terribly concerned about how long users spend on its platform every day.  We are interested in our consumer users to the degree they are doing work, solving problems in their life, says Anthropic design chief Joel Lewenstein during an interview with Fast Company this week. Because we’re not interested in passive consumption and image generation and video generationwe just sort of have ruled those out from a mission perspective . . .  Anthropic was famously founded by a group of OpenAI execs who defected in 2021 to found a more safety-focused AI lab. That focus hasnt changed. Our interests are in making things that are beneficial while minimizing the risks of those same products because everything has a double-edged sword, Lewenstein says. We see . . . helping people grow and expand and create and solve problems as being the right risk-reward tradeoff.  The San Francisco-based startup believes that work-first focus will ultimately win out as AI eventually shows its profoundest effects in the lives of businesses, not consumers. At a conference Wednesday, Anthropics cofounder and policy director Jack Clark says Anthropic will eventually overtake OpenAI because of its enterprise focus, its strong technological roadmap, and because its research is accelerating faster than its rivals.  All of this is reflected in the look and feel of its Claude chatbotthe main entry to access Anthropics powerful modelsbut also in its attitude.  Not warm and fuzzy When it comes to work, Claude is pleasant, even empathetic, but seriousand it comes with a free BS detector. Sycophancy in AI models, after all, has become a serious problem. OpenAI recently admitted having to push an update to its GPT-4o model to fix its sycophantic behavior. And its CEO Sam Altman stated in a post on Oct. 14 that users will be able to reintroduce that personality if they liked it. The model reportedly had a habit of praising or validating user statements even when they were delusional or concerning (one user claimed a divine identity). Some analysts believe that such behavior in a model is more than a bug, but a choice made by the model maker in the interest of getting people to use the platform more.  A sycophantic chatbot in a work setting can act something like a yes-man, embracing and offering to further develop even the worst business ideas. This can lead to a range of reputational and financial harms, not to mention seriously damaging trust in the AI.  Sychophantic AI could be especially dangerous to Anthropic, which wants its user to use Claude not just for quick content generation, but as a collaborator or thinking partner to do serious work. In order to do that, the user needs to build confidence and trust in the reasonableness of the AI. So Anthropic trained the models behind Claude to push back on logically suspect thoughts from the user. Lewenstein says his company worked especially hard to train this into its newest model, Claude Haiku 4.5, which it says is the most sycophancy-resistant model available in its size. The artifacts shift The idea of Claude as collaborator has directly impacted the chatbots user interface. With the introduction of Artifacts last year, Anthropic added a highly functional workspace around the chatbot. The idea of the Artifacts UX is to show a working draft of the project the user and the AI are working on in real time, within a panel at the right side of the interface. This might be a document draft, a chart, or a code preview, which the user can inspect, click, highlight, and suggest changes. The user can tell Claude to write something in a new way, or integrate a new idea from an uploaded PDF or text file.  I cannot overstate how big of a shift that is, and [it] anchors a lot of the way that we think, Lewenstein says. By this he means that Artifacts encourages the user to think of Claude as a smart work companion, rather than just a content generator. It creates this sense of you’re making something alongside Claude, Lewenstein says. We’re not just giving you the answer. We’re not having you just download it and we’re done . . . Rather, the human and chatbot enter a dialog where they gradually shape the output into what the user wants. Lewenstein acknowledges that while AI tools have a growing number of power users, a significant percentage of users have yet to scratch the surface of whats possible. He says a major challenge of the user interface design is to invite people to Claudes features more fully. Artifacts can show users their options so that they can proceed in an experimental way, learning as they go. And, as of last month, Claude now can automatically remember past chats, so it might proactively ask if the user wants to include some theme or piece of data (perhaps a relevant piece of proprietary product research or a business plan) its encountered before.  I think the more things that Claude is able to doClaude can now make PowerPoints and make Excel documentsthe more things that it makes, the more important it is that there is some space that you can actually see and engage with that content, Lewenstein says. The reason Claude can make presentations and spreadsheets is because of skills, or packets of knowledge that Claude can call up when the user needs them. On Thursday, a day after announcing its new Claude Haiku 4.5 model, the company announced that Claude users can now make their own agent skills.” If a user worked with Claude to create a presentation, for example, and called in a number of style sheets and marketing guidelines to do it, they can package all that work up in a skill and use it again the next time they need to do a presentation.  In essence, Claude is enabling a user to create a kind of agent that has expertise and experience working with the user on a specific task.  Agents AI agents can reason and act autonomously to do things like fetch data, perform actions, create plans. OpenAI recently announced a new tool called Agent Builder that provides a simple, graphical interface to create agents, define their workflows, and pull in tools the agent can use (a safety guardrail tool, for example). OpenAI says this could speed up the process for developers, and reduce the need to build agents from scratch.   Anthropic believes that the right UX for building and managing agents depends on the type of user and their level of expertise. When developers within businesses build agents, Lewenstein explains, they write them as code, and Anthropic provides them a number of governance and security ools to help manage them. Theres no abstraction layer that represents the parts as objects that can be dragged around on a screen (at least not yet).  Lewenstein says consumers, prosumers, and average knowledge workers usually just want to describe a goal they want the agent to achieve, then let the AI carry out the necessary functions behind the scenes to make it happen. That’s the direction Anthropic is pursuing now. Whether users even want to think about agents as a concept remains an open question, he says.   Still, Anthropic is exploring several different kinds of agent approaches within Claude, some of them tightly integrated with chat, some of them less so. The focus is on what people are trying to accomplish, Lewenstein says. Anthropic will provide whatever is needed in any form factor to achieve that, and the company isn’t wedded to any particular UX paradigm yet. He cites the old marketing adage: Users dont really want a quarter-inch drill bit, they want a quarter-inch hole. Claude of the future Right now, users are still trying to understand how AI agents can fit into their overall workflows. In a work setting they may be skeptical that the agent will produce reliable, actionable work. They will naturally want to know a lot about how the agent is doing its work, how it’s getting from a directive to a result. Lewenstein says that Claude now lets users click to see all the steps the agent (powered by the model) took to reach a result. Building that into the UX, he says, wasnt a terribly challenging problem. But, over time, Claude will become more autonomous and capable of working unsupervised for longer periods of time (already the Claude Sonnet 4.5 model can work by itself for 30 hours). This could create challenges for the UX, which will have to show an audit of every step in the work that was done. We have these components in the UI which we’ve been working on for the last couple of years, which is a short little summary and then if you expand it, it actually shows you, Here’s everything I did for the last X hours, so that you can really build up an understanding but also a trust. In the first phases of AI agents being used within enterprises, users will have to think through what tasks they can delegate to agents, and what tasks to keep for themselves. Future versions of Claude, Lewenstein says, might help the user understand this. I think this is the future of where a lot of these products need to gounderstanding someone’s workflow enough, [and] its own capabilities enough, to proactively say, I will take this work off your plate and I will leave you with this thing, and that should feel very empowering to people, Lewenstein says. An AI for work Even for its consumer users, Anthropic is interested in helping them do work, not pass the time. So the same Claude user interface works pretty well for both personal and business use cases, Lewenstein says. He says consumers use Claude for a lot of personal things that might as well be work thingscomplex problems like planning a vacation or navigating a complicated renovation. We see consumers or people who are not doing it for their employer finding a lot of benefit in basically all the same basic features that we have [in Claude] for work. Eighty percent of Anthropics revenues come from enterprise customers. After crossing $1 billion a year in annualized revenue run rate (ARR) at the beginning of 2025, the company expects to hit $9 billion in ARR by the end of the year, Reuters reports, and then $26 billion in 2026.  While OpenAI doesnt usually talk about its revenue mix, its CFO Sarah Friar said in 2024 that the company made 75% of its money from consumer subscriptions. As of June 2025, OpenAIs ARR was reportedly $10 billion (excluding licensing revenue from Microsoft and large one-time deals). Analysts expect OpenAI to reach about $12.7 billion in total revenue in 2025.


Category: E-Commerce

 

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2025-10-20 09:30:00| Fast Company

OpenAI has announced that starting in December, ChatGPT will allow the generation of erotic content for verified adult users. At the same time, Elon Musks xAI has launched Grok Imagine, an image-generation system that already includes an NSFW mode for producing explicit imagery.  None of this should surprise anyone. Desire, fantasy, and pornography have always been powerful engines of technological adoption. Photography, video, the internet, and even online payments all grew, in part, because of it. The interesting question is not about sex: its about what these decisions reveal about the kind of humanity Big Tech companies are shaping.  Desire as a managed service  This is not about prudishness or panic. Sexuality will, of course, find its digital expressions. Whats unsettling is not the presence of eroticism in technology, but its industrialized management.  The difference between eroticism and algorithmic consumption is the same as that between experience and dopamine: one is built through relationship; the other is dosed from the outside. By integrating sexuality into large language models and visual generators, platforms are not liberating desire: they are administering it.  They decide which fantasies are acceptable, which bodies exist and which dont, what limits imagination deserves, and which ones are preemptively censored. The promise is freedom; the result is regulation of pleasure.  From exploration to domestication  When excitement, tenderness, and curiosity are mediated through an interface, our relationship with our bodies and with others changes. This isnt moralism. Its behavioral architecture.  Algorithms learn what attracts us, replicate it, reinforce it, and turn it into dependence. Users stop exploring desire; they repeat it. And repetition, safe, comfortable, and risk-free, becomes a form of domestication.  Theres no need to manipulate people with ideology when you can condition them with pleasure. Constant stimulation is a far more effective form of control than censorship ever was.  A new vector of capture  Its no coincidence that this expansion arrives just as large language models mature and corporations compete to keep users inside their closed ecosystems.  Sex, in this context, becomes just another vector of attention capture, a way to deepen the emotional bond between humans and machines.  The goal is no longer for AI to respond, but to accompany, excite, soothe, and replace. The fantasy isnt companionship: its containment. An artificial partner designed never to challenge, never to refuse, never to feel.  This is not technological liberation. Its the automation of comfort.  From entertainment to managed desire  As I said a couple of weeks ago, weve been here before. From social networks to gaming, digital entertainment has followed the same logic of permanent stimulation. What changes now is the terrain: its no longer about free time: its about desire itself, that core where emotion and biology meet.  Turning desire into a managed service run by algorithms is the final step toward a docile humanity, one in which even intimacy becomes a subscription.  Digital sex vs. algorithmic sex  The point is not to moralize about pornography: its to understand what it means to hand over control of erotic imagination, one of humanitys most powerful creative forces, to closed systems that do not explain how they learn, what they filter, or whom they serve.  The problem is not digital sex. Its algorithmic sex. Not pleasure, but control.  Once these systems learn to measure, adjust, and stimulate desire, free will becomes just another optimization parameter.  The new anesthesia  Behind this apparent liberalization of content lies a simpler, more effective strategy: keep us busy, satisfied, and distracted.  Not indoctrinated: anesthetized.  A form of emotional livestock, fed by impulses engineered on distant servers. Algorithmic sheep: artificially happy, productive, and unable to tell the difference between genuine desire and manufactured stimulus.


Category: E-Commerce

 

2025-10-20 09:00:00| Fast Company

People are fascinated with leadership, and rightly so. After all, most of the big things that happen in the world (both good and bad) can be directly traced to decisions, behaviors, or choices of those who are in charge: presidents, prime ministers, CEOs, executives, and anyone tasked with turning a group of people into a high-performing unit, coordinating human activity, and shaping the impact institutions have on society, all the way down to individuals. In line, scientific research shows that up to 40% of the variability in team and organizational performance can be accounted for by the leaderin other words, who we put in charge, or who emerges as leaders, drastically influences the fate of others. This begs the obvious question of how and why some people become leaders in the first place. Furthermore, few psychological questions have intrigued the general public more than the question of whether nature or nurture is responsible for shaping and creating leaders: so, are leaders born or made? {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/tcp-photo-syndey-16X9.jpg","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/tcp-photo-syndey-1x1-2.jpg","eyebrow":"","headline":"Get more insights from Tomas Chamorro-Premuzic","dek":"Dr. Tomas Chamorro-Premuzic is a professor of organizational psychology at UCL and Columbia University, and the co-founder of DeeperSignals. He has authored 15 books and over 250 scientific articles on the psychology of talent, leadership, AI, and entrepreneurship. ","ctaText":"Learn More","ctaUrl":"https:\/\/drtomas.com\/intro\/","theme":{"bg":"#2b2d30","text":"#ffffff","eyebrow":"#9aa2aa","buttonBg":"#3b3f46","buttonText":"#ffffff"},"imageDesktopId":91424798,"imageMobileId":91424800}} If you want the quick and short answer, it is YES. Or if you prefer, a bit of both (which is generally the case in psychology). Lets start with the nurture part, which is the one more likely to resonate with popular or laypeoples views . . . (1) Environment shapes character and competenceOur early environments (especially during childhood) play a profound role in molding the attitudes, motivations, and habits that underpin leadership. Supportive parents, good schooling, early exposure to responsibility, access to a stimulating wider community, and opportunities to practice decision-making all nurture proto-leadership skills such as conscientiousness, self-control, curiosity, assertiveness, and empathy. On the flip side, adversity can also build resilience, independence, and determination. In other words, leadership potential often germinates in the soil of early experiences, but its impossible to accurately predict the direction of the development, which is what makes life interesting and fun. At the same time, things arent random, and science-based predictions will work more often than not (on average, for most people, we can improve from a 50% guesswork to around 80% hit rate). (2) Expertise legitimizes leadershipNo one wants to follow a leader who doesnt know what theyre talking about. Thats why domain-specific knowledge is essential for legitimacy. You cant lead a tech team without understanding technology, or a marketing department without grasping customers and branding. Expertise breeds credibility, and credibility breeds followership in turn. This is why great football coaches will probably fail as corporate CEOs, and why even the best military leaders may not be adequate startup founders. While charisma or confidence may get you noticed, sustained leadership requires demonstrable competence. This is learned, not inherited, because its about harnessing the social proof that makes you a credible expert in the eyes of others (and I mean other experts not novices!). (3) Personality evolves through life experienceTraits like curiosity, openness, emotional stability, and conscientiousness (all strong predictors of leadership effectiveness) are partly malleable. They evolve in response to life experiences, feedback, and learning. The so-called bright side of personality (ambition, sociability, diligence) and the dark side (narcissism, impulsivity, arrogance) both reflect a mix of innate dispositions and environmental reinforcement. The first decade of life is particularly critical, but development continues throughout adulthood. So while personality sets the stage, experience writes the script. Now for the less popular, but equally important nature side of the debate. (4) Leadership is partly heritableBehavioral genetics (especially twin studies) show that leadership is not purely learned. Roughly 30 to 60% of the variance in who becomes a leader can be attributed to genetic factors. Rich Arvey and colleagues at the National University of Singapore found that identical twins, even when raised apart, are significantly more likely to occupy leadership roles than fraternal twins. This doesnt mean leadership is predetermined, but it suggests some individuals are born with psychological and biological predispositions, like higher energy, extraversion, or risk tolerance, that increase their odds of taking charge. (5) Intelligence and personality are strongly geneticTwo of the most powerful predictors of leadership (cognitive ability and personality) are themselves highly heritable. Robert Plomins decades of research suggest that around 50% of the variance in both IQ and personality traits can be traced to genetics. Since these traits strongly predict who emerges as a leader and how effective they are, we can reasonably infer that part of leadership is literally in our DNA. Brains, not just behavior, matter: smarter, more emotionally stable individuals tend to make better decisions, handle stress, and inspire confidence; all qualities that attract followers. (6) The unfair advantages of birthFinally, theres the uncomfortable truth that social class, privilege, and demographic factors like gender, race, and attractiveness (each partly determined by who you are born to) also shape leadership opportunities. Tall, good-looking, well-spoken individuals from higher socioeconomic backgrounds are more likely to be perceived as leadership material, regardless of actual competence. These advantages arent earned, yet they strongly affect leadrship trajectories. Nature determines the lottery ticket; society decides how valuable it is, even if this is arbitrary and unfair. To be sure, societies that dislike this fact (including most Western democracies) are seeing big decreases in upward social mobility. For instance, in the U.S., approximately 50% of a fathers income position is inherited by his son (in Norway and Canada, the figure is less than 20%). With wealth and money come advantages and access to leadership positions, so while nature isnt destiny, it certainly inhibits or amplifies opportunities. In sum, the science of leadership suggests that it is both born and made. Genetics endows us with certain predispositions (intelligence, temperament, even physical appearance) that make leadership more or less likely. And our socioeconomic status and parental resources at birth shape the nature of whats possible, or at least likely. But environment, learning, and experience are the catalysts that turn those predispositions into performance. Leadership, in other words, is a potential meeting opportunity. And while we cant control our genetic hand, we can absolutely learn to play it better. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/tcp-photo-syndey-16X9.jpg","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/tcp-photo-syndey-1x1-2.jpg","eyebrow":"","headline":"Get more insights from Tomas Chamorro-Premuzic","dek":"Dr. Tomas Chamorro-Premuzic is a professor of organizational psychology at UCL and Columbia University, and the co-founder of DeeperSignals. He has authored 15 books and over 250 scientific articles on the psychology of talent, leadership, AI, and entrepreneurship. ","ctaText":"Learn More","ctaUrl":"https:\/\/drtomas.com\/intro\/","theme":{"bg":"#2b2d30","text":"#ffffff","eyebrow":"#9aa2aa","buttonBg":"#3b3f46","buttonText":"#ffffff"},"imageDesktopId":91424798,"imageMobileId":91424800}}


Category: E-Commerce

 

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