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When I first encountered AI, it wasnt anything like the sophisticated tools we have today. In the 1990s, my introduction came in the form of a helpful, but mostly frustrating, digital paperclip. Clippy, Microsofts infamous assistant, was designed to help, but it often got in the way, popping up at the worst moments with advice no one asked for. AI has evolved since then. Major companies like Apple are investing billions, and tools like OpenAIs ChatGPT and DALL-E have reshaped how we interact with technology. Yet, one challenge from Clippys era lingersunderstanding and adapting to user intent. The original promise of AI was to create experiences that felt seamless, intuitive, and personal. AI was supposed to anticipate our needs and provide support that felt natural. So, why do so many systems today still feel mechanical and rigidmore Clippy than collaborator? When AI assistance is a burden When first introduced, Clippy was a bold attempt at computer-guided assistance. Its purpose was groundbreaking at the time, but it quickly became known more for interruptions than useful assistance. Youd pause when typing, and Clippy would leap into action with a pop-up: It looks like youre writing a letter! Its biggest flaw wasnt just being annoying: It lacked contextual awareness. Unlike modern AI tools, Clippys interactions were static and deterministic, triggered by fixed inputs. There was no learning from previous interactions and no understanding of the users preferences or current tasks. Whether you were drafting a report or working on a spreadsheet, Clippy offered the same generic adviceignoring the evolving context and failing to provide truly helpful, personalized assistance. Is AI destined to be like Clippy? Even with todays advancements, many AI assistants still feel underwhelming. Siri is a prime example. Though capable of setting reminders or answering questions, it often requires users to speak in very specific ways. Deviate from the expected phrasing, and it defaults to, I didnt understand that. This is more than a UX flawit reveals a deeper issue. Too many AI systems still operate under a one-size-fits-all mentality, failing to accommodate the needs of individual users. With Siri, for instance, youre often required to speak in a specific, rigid format for it to process your request effectively. This creates an experience that feels less like assistance and more like a chore. Building a smarter assistant isnt just about better models. Its about retaining context, respecting privacy, and delivering personalized, meaningful experiences. Thats not just technically difficultits essential. Helpful AI requires personalization Personalization is what will finally break us out of the Clippy cycle. When AI tools remember your preferences, learn from your behavior, and adapt accordingly, they shift from being tools to trusted partners. The key to this will be communication. Most AI today speaks in a one-dimensional tone, no matter who you are or what your emotional state is. The next leap in AI wont just be about intelligence, itll be about emotional intelligence. But intelligence isnt only about remembering facts. Its also about how an assistant communicates. For AI to truly feel useful, it needs more than functionality. It needs personality. That doesnt mean we need overly chatty bots. It means assistants that adjust tone, remember personal context, and build continuity. Thats what earns trust and keeps users engaged. While not every user may want an assistant with a personality or emotions, everyone can benefit from systems that adapt to our unique needs. The outdated one-size-fits-all approach is still common in many AI tools today and risks alienating users, much like Clippys impersonal method back in the early days. For AI to thrive in the long term it must be designed with real humans in mind. Building Clippy 2.0 Now imagine a Clippy 2.0an assistant that doesnt interrupt but understands when to offer help. One that remembers your work habits, predicts what you need, and responds in a way that feels natural and tailored to you. It could help you schedule meetings, provide intelligent suggestions, and adapt its tone to fit the moment. Whether it has a personality or not, what matters is that it adapts toand respects the uniqueness of every user. It might even respond with different tones or emotions depending on your reactions, creating an immersive experience. This kind of intelligent assistant would blend seamlessly into your routine, saving you time and reducing friction. Clippy may have been a trailblazer, but it lacked the technological foundation to live up to its potential. With the advances weve made today, we now have the tools to build a “Clippy 2.0an AI assistant capable of transforming the way we interact with technology. Although maybe this time, it doesnt need to come in the form of a paperclip with a goofy smile. Oleksandr Kosovan is the CEO and founder of MacPaw.
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E-Commerce
Over the past two decades, our team and I have spent countless hours in homes, healthcare settings, and community spaces, watching how people navigate the rhythms of everyday life. What stays with me are the quiet adjustments or life hacks. A bed lifted on risers to slide a storage bin of medical supplies underneath to stay within reach or to better facilitate a transfer. A bottom dresser drawer left empty because it is out of reach and theres concern it could lead to a fall. A nightstand pulled a few inches away to make space for a CPAP hose or oxygen tubing. These arent rare exceptions. Theyre everyday adjustments to the built environment that hadn’t previously caught up with real life wants and needs. In response to these observations, we design products to fill the gaps. From medical aids like canes and bath safety products to household furniture that directly addresses these needs, integrating novel functional enhancements into the product design helps create environments that work better for people. Responding to one definition of disabilitya mismatch between a persons abilities and their environmentwe strive to ensure that built environments are accessible, functional, and welcoming for as many people as possible. From the edge to the universal In design and in business, were often taught to prioritize the average user. But the most meaningful, enduring innovations tend to come from the edgesdesigning with people who experience the world differently, whether through disability, age, or temporary limitation. What begins as a targeted accommodation often becomes something far more universal. Accessible features in furniture, kitchen tools, or other housewares tend to become quietly indispensable. Not because they draw attention to themselves, but because they solve problems most people didnt even realize they shared. When you design for the margins, you dont exclude the mainstream; you elevate it. Take, for instance, a bed designed with integrated armrests to support safer mobility, as we recently created in collaboration with Pottery Barn. It may have been crafted with accessibility in mind, but it ultimately benefits anyone recovering from surgery, dealing with aches and pains, or simply trying to get up more easily in the morning (or reposing in bed to comfortably watch TV or use devices). The same goes for a nightstand designed with discreet space for powering medical equipment. It meets a real need, while also improving daily use for people managing cords, devices, or the clutter of modern life. These design choices never come out of thin air. They come from time spent with real people, in real environments, observing where traditional products fall short and responding to those gaps with practical, thoughtful solutions. Michael Graves often referred to this as common sense. Design for accessibility Situational disability is something most of us experience regularly without really thinking about it. You dont need a formal diagnosis to encounter friction in your environment, yet it can be improved by surrounding yourself with thoughtful products. Think about navigating a dark hallway, opening a door with full hands, or focusing in a space thats too loud or too bright. These are temporary or contextual limitations that can turn an ordinary task into a source of frustration. Designing with these moments in mind doesnt dilute a projects creativity; it strengthens it, and leads to better customer experiencesa universal business goal. Theres still a lingering belief that designing for accessibility means sacrificing style or inflating cost. But in practice, starting with constraints leads to sharper, more intentional design decisions; products with smarter features and a clearer sense of purpose. Many of todays most widely adopted design featurescurb cuts, touchless faucets, voice control, ergonomic gripsoriginated as accessible solutions. They didnt stay niche. They became standard. The real opportunity today is not just designing for users, but designing with them. When we observe how people actually live, what they reach for, struggle with, work around, we find the insights that matter most. We call this approach Design With, a process built on listening early and often, where lived experience isnt just part of the feedback loop, its part of the product development foundation. Accessible design isnt a feature or a trend. Its a foundation. When baked in from the beginning, it expands a products relevance, strengthens emotional connection, and makes the experience feel more human. It reflects the reality that ability exists on a spectrum, and that good design considers everyone on it. If we want to create more useful, more beautiful, and more accessible environments for Every Body, we have to start by looking at the edges. Thats where the friction lives, and where the most meaningful design breakthroughs often begin. Ben Wintner is CEO of Michael Graves Design.
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E-Commerce
Meta, which owns and operates Facebook and Instagramas well as Threads, Messenger, and WhatsApphas tapped Alexandr Wang, the CEO and founder of the startup Scale AI, to head up its new artificial intelligence research lab, according to The New York Times. It is also in talks to invest over $10 billion in the company, Bloomberg reported. The lab will be dedicated to pursuing AI superintelligencean AI system that would reportedly surpass human intelligenceand is part of Meta’s larger reorganization of its AI efforts as it faces internal struggles over the technology and some of its products, per The Times. Meta is just one of many tech companies to throw its hat into the competitive, high-stakesand expensiveAI development space. Back in January of this year, Meta’s CEO Mark Zuckerberg said the social technology company plans to invest between $60 billion and $65 billion in capital expenditures this year alone to build out its AI infrastructure. (Meta is also building a large data center that would reportedly “cover a significant part of Manhattan to power its AI offerings, according to Zuckerberg.) What does Scale AI do? Scale AI delivers high-quality training data for AI applications to a number of tech companies in the AI space, including: Open AI, Google, Microsoft, and of course, Meta. The company expects revenue to more than double to $2 billion this year, from about $870 million in 2024, per CNBC. Scale AI is already working with governments in Asia, the Middle East, and Europe, and recently signed a deal with Qatar in February that will include developing AI voice, chat, and email agents for contact centers, Business Insider reported. Scale AI also signed a contract with the U.S. Defense Department to enable the military to use AI for “operational decision-making.” While its financials are confidential, Scale AI is reportedly planning a potential tender offer for employees and early investors at a valuation of $25 billion, Business Insider reported. Who is Alexandr Wang, the young billionaire behind Scale AI? Wang founded Scale AI in 2016 in San Francisco at age 19, out of Y Combinator‘s startup incubator, after dropping out of MIT. In 2022, at age 25, Wang became the world’s youngest self-made billionaire after Scale AI raised $325 million in funding, putting the company at a valuation of $7.3 billion; by 2024, Scale AI was valued at $13.8 billion, the Observer reported. Wang owns 15% of Scale AI, making his net worth over $2 billion.
Category:
E-Commerce
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