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Take a deeper look at crawl behavior, bot verification, and technical SEO signals through log file analysis. The post What Can Log File Data Tell Me That Tools Can’t? – Ask An SEO appeared first on Search Engine Journal. View the full article

Assessment from MPC adds to sell-off in gilts and prompts traders to increase bets on higher borrowing costsView the full article

Ride-hailing app to buy as many as 50,000 autonomous vehicles and invest an initial $300mn in California EV companyView the full article

As conversational search gains traction, the bigger question isn’t who has more users, but who can monetize them. Google enters this phase with a massive advantage: mature ad systems, deep advertiser adoption, and decades of optimization. Early AI Mode signals point to a measured rollout. The panic phase is over After a period of panic within the company, Google’s built-in advantages, coupled with massive capital expenditures, have helped it regain ground on category leader ChatGPT in LLM search. In December 2025, Google’s own code red became OpenAI’s code red. The dust will continue to settle, and analysts have different takes. But one signal stands out: in a major validation, Apple has chosen Google to power its own AI. It was perhaps premature to assume Google Search would simply lose to ChatGPT on product. That was the consensus at the start of 2025. Google shares fell about 30% from peak to trough before rallying 130%. Today, the company is valued at roughly $3.6 trillion, just behind Apple. Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with Why monetization will decide the winner Why did Google’s recent progress in LLM conversational queries — in the form of AI Overviews and AI Mode — have such a large impact on the company’s valuation in such a short time? Ultimately, it comes down to visibility of financial projections. In a company with so much to defend, Google’s CFO and leadership team needed to determine whether shifts in user behavior — in how search works and how it makes money — would weaken the business model or reinforce it. Net-net: Google before the shift: huge. Google after the shift: ditto. Google stock price. The market changed its mind. Visibility — in the sense of financial planning, not in the SERP — means a great deal to Google’s advertisers, too. A large proportion of your annual digital advertising budget is likely allocated to Google. You also still care about how you appear in organic results and increasingly, how your company appears in AI Mode, ChatGPT, Claude, and similar environments. “I’m fine with 30% less of my business coming in from Google, and figuring out lots of complicated ways to replace it,” … said no advertiser ever. How monetization will play out in AI search The competition between monetization models in LLM conversations — especially between the two leaders, ChatGPT and Google’s AI Mode — will play out differently from the broader race for overall user share. There are several moving parts to keep an eye on: Overall assumptions about ad formats and “how to monetize.” Pace of rollout. Whether users and public opinion recoil at ads. Advertiser success rates based on performance measurement. Advertiser adoption, including adoption by the agency ecosystem. Platform targeting options. Advantages of fuller-funnel ad journeys and data collection. Privacy, safety, policies, and enforcement. An all-encompassing consumer brand vs. a better mousetrap. And a few other factors. Right now, OpenAI is at a critical moment because it’s still so early in its monetization. It’s still testing an inefficient auction model confined to a small group of large advertisers. (Some ads, from their pilot, spotted here.) It may be some time before more mature tools and reporting emerge. Most recently, OpenAI brought ad platform Criteo (often used for retargeting) on as a partner. The Trade Desk, the world’s largest non-Google DSP for programmatic, is also in the mix. Some observers have speculated about deeper partnerships or even an acquisition of The Trade Desk, though that seems unlikely. In any case, outsourcing inventory to programmatic partners is a pragmatic step in OpenAI’s monetization strategy. It also underscores how early the company is in building a scalable ads business. Despite a broad rollout with partners, OpenAI is stepping back from “checkout in chat” integrations after limited adoption from both merchants and consumers. When your primary competitor has a 25-year head start, the learning curve is steep. So does it make sense now for advertisers to lean into evolving Google user behavior and figure out how to ride the wave? AI Mode considerations for Google advertisers Expect the transition to more AI Mode sessions — and eventual monetization — to be smoother than initially anticipated. If you’re an advertiser, AI Mode need not equal panic mode. How do these LLM sessions look to users? Obvious to you and me, but likely less so for many searchers. Depending on how you search, AI Overviews may appear above other results on the SERP. That’s becoming a natural extension of Google Search sessions. But that’s not the real conversational layer. The LLM workflow happens in AI Mode. How often users go there remains to be seen. It’s improving quickly. Unlike ChatGPT, Google AI Mode downplays how it finds information, whether it is “reasoning,” and which model is being used. The experience feels relatively seamless. It’s still early, but ads are already appearing in some cases. The key question is how this evolves, and what advertisers should be paying attention to. The key areas to watch are: Extent of monetization. Different ways to monetize. Advertiser control and campaign types. Reporting. Funnel stage. 1. Extent of monetization AI Mode is in a popularity contest and a price war with ChatGPT. Google will likely try to grind down competitors in LLM conversations by monetizing lightly and gradually. Perplexity and Anthropic, for their part, are completely shunning ads. An ad-free AI Mode results page. We’re going to see a lot of this. The result will be less ad volume in this space than you might expect. It may also increase the commercial value of organic visibility in LLM-driven results, leading to renewed focus on content and reputation fundamentals. Forget ad campaign FOMO, then. It will be interesting to place ads alongside AI-driven sessions, but don’t break the bank. Implement, watch, and learn at your own pace. 2. Different ways to monetize Experienced advertisers know there are a few ad formats to consider in any situation like this. The main ones would be: text ads triggered by keywords or similar signals, in a reasonably native format, and feed-based Shopping type ads. Another way to make money is to allow direct checkout — to take a cut of transactions. As noted above, OpenAI is backtracking on this approach, though not eliminating it entirely. How important it will be for Google merchants (and Google itself) remains to be seen. Google’s experience likely allows it, again, to play the long game, study the data, and bring partners and advertisers along for the ride, on an impressive scale. Recently, Loblaw inked an integration deal with OpenAI. A week later, it made a similar deal with Google. Get the newsletter search marketers rely on. See terms. 3. Advertiser control and campaign type In terms of execution, we’ll want to be on the lookout for which kinds of campaign types in Google Ads make your ads eligible to show in AI Mode. You can learn everything you want about how ads will show in AI Overviews in Google’s help files. Unsurprisingly, text and shopping campaigns from Performance Max, standard shopping, and keyword campaigns make your ad eligible to show in AI Overviews. Google says less about AI Mode in its documentation, for now. Our agency recently received a Google deck outlining a “Shopping Expansion” beta. There’s little mention of AI Mode, though one table, in a subtle way, refers to both AI Overviews and AI Mode. My expectation is that Google will gradually ease users into AI Mode and test ads sparingly. Even if ads appear in a small share of sessions — say 0.5% — that will still generate significant data and feedback. Advertiser control will likely be even more limited than it is today. In the world of feed-based ads, you have some levers, but the massive machine learning that controls matching is held by Google and the real-world behavioral ecosystem. To a lesser extent, that’s also how keyword matching works. Micromanagers won’t be too comfortable, but the impact of the ads could still be powerful, especially with data-driven attribution. Here’s hoping new signals, new reporting breakouts, and new levers become available to advertisers. Namely: audiences including cool personas; demographics; novel larger buckets around life stages; novel characteristics we haven’t even dreamt of yet, such as their language ability level or aspects of how they interact with the LLM. 4. Reporting The real question is: will reporting be transparent and insightful? We need to at least be able to look at all available metrics for ads that showed in AI Mode specifically. Time will tell. Microsoft seems to be the first out of the gate with AI-conversation-specific reporting breakouts. We expect no less from Google and are impatiently awaiting further guidance on this front — primarily on what kind of reporting will be directly available in the Google Ads interface. It would be easy for the casual observer to blindly believe that somehow, you’ll never be eligible to show up in AI Mode or AI Overviews unless you adopt certain Google Ads campaign types. There’s a lot of rhetoric around AI Max. I’d advise advertisers to do their own research and run their campaigns to suit themselves. Hint: AI Max isn’t the only magical gateway to AI-using users and might not even be a good or appropriate one for many advertisers. Once reporting is beefed up, you’ll want to know how well the AI-specific inventory is doing, however your campaigns wind up serving there. 5. Funnel stage But that leads us to a wrinkle. Although ads appearing astride AI Mode conversations could certainly be low-funnel (think Shopping ads in high-intent situations), much of the opportunity here is thematic. Your company may now enjoy new opportunities to associate itself with higher-order thinking, new audience definitions, and new intent characteristics. This opportunity probably comes to your door dressed up as “lower ROAS.” It may be tempting, therefore, to shy away. That’s a mistake. Why? Like what happened when everyone started using mobile phones, that’s where the consumer will be. Ugly early numbers shouldn’t blind us to the imperatives associated with scale. See the complete picture of your search visibility. Track, optimize, and win in Google and AI search from one platform. Start Free Trial Get started with When the funnel moves, everything moves Midsized to larger advertisers should step back and reimagine how they approach growth and market impact. There are meaningful opportunities for companies to align more closely with their audiences. This has little to do with AI Max, and everything to do with how LLM-driven research works. Compare how publishers have traditionally assembled consumer personas — often from fragmented behavioral signals — with the much richer context that can emerge from ongoing interactions with an LLM. A net shift up-funnel could follow. Imagine a world where a significant share of Google search sessions takes place within conversational experiences. Your ads will need to show up there, where appropriate. If that happens, your funnel — and your competitors’ — will move with it. Will you be ready? View the full article

Darren Graves will become Big Four firm’s new chief if approved by colleaguesView the full article

If you’ve spent any time on social media lately, it’s easy to believe that video is the be-all and end-all. Instagram Reels, YouTube Shorts, TikToks, LinkedIn’s video feed: it’s everywhere, and it feels like every platform is building for it. If you’re looking to build an audience, “more video” is often touted as the answer. But is that true? It turns out — as is often the case with social media — it depends. Video certainly performs best on some platforms, but it’s not quite as cut-and-dried on others. This data comes from our 2026 State of Social Media Engagement report, which analyzed millions of posts across all major platforms. And, at the risk of sounding like a clickbait-y video hook (sorry) — the results might surprise you. While video often gets the spotlight, it’s not always the best path to engagement. Let’s examine how different content types perform on Threads, TikTok, LinkedIn, X (formerly Twitter), Instagram, Facebook, Pinterest, and Bluesky. Before we dig in, the usual Ts and Cs: The best content for you depends on your target audience. Every audience is different, so there is no one-size-fits-all approach that’s going to work for every social media account. To pinpoint what works best for you, I’d encourage you to start with a social media content strategy and, from there, experiment with different types of content in your social media content calendar. Use the data in this article as a starting point to help you figure out what kind of content is most likely to resonate with your followers. Jump to a section: Key takeaways Best content format by platform — at a glance The best content format on TikTok The best content format on Instagram The best content format on Facebook The best content format on Threads The best content format on LinkedIn The best content format on X The best content format on Pinterest The best content format on Bluesky So, which content format is the best? Key takeawaysLinkedIn carousels (PDF posts) earn a median engagement rate of 21.77% — 196% more than video and 585% more than text posts — the highest of any format across all platforms in this analysis.Instagram carousels drive 109% more engagement per person reached than reels — but reels reach 2.25× more people than single-image posts, making format choice goal-dependent.TikTok video earns 77% more engagement than carousels and photos (3.39% vs. 1.92% median engagement rate).Pinterest video earns 83% more engagement than images (5.75% vs. 3.15%), despite the platform's image-first reputation.Threads video leads engagement at 5.55% — nearly double text posts (2.79%) — on a platform primarily associated with conversation.Facebook is the most format-agnostic platform in this dataset: images, video, and text posts all fall within one percentage point of each other.On X, text leads with a 3.56% median engagement rate — but images have narrowed the gap to just 5%.Reach and engagement often point in opposite directions: the format that reaches the most new people (usually video or reels) is rarely the format that drives the deepest engagement from existing followers (usually carousels).On to the data. Here are the best types of social media content for each platform in 2026. Best content format by platform — at a glance Platform Best format for engagement Engagement rate Runner-up LinkedIn Carousels (PDF posts) 21.77% Video: 7.35% Pinterest Video 5.75% Images: 3.15% Threads Video 5.55% Images: 4.55% Instagram Carousels 6.9%* Single images: 4.4%* Facebook Images 5.20% Video: 4.84% TikTok Video 3.39% Carousels/photos: 1.92% X Text 3.56% Images: 3.40% Bluesky Video 5 interactions† Images: 4 interactions† *Instagram engagement rate measured as a percentage of reach. Note: Reels outperform all formats for reach — 2.25× more than single-image posts. †Bluesky uses median total interactions rather than engagement rate; data is early-stage. ✨Did you know? Whether it's a video, carousel, image or text-post, you can schedule it right in Buffer! Get started for freeThe best content format on TikTokOn TikTok, video earns a median engagement rate of 3.39% — 77% higher than carousels and photo posts — making it the clear top-performing format on the platform. To say that video reigns supreme on TikTok feels a bit like stating the obvious. The short-form video-sharing platform is, after all, just that. Despite TikTok introducing carousels (multi-photo posts) in recent years, videos are still the TikTok algorithm's bread and butter. What's interesting is how much of a gap remains between the two formats. In this analysis, we measured success by median engagement rate. We found that videos pulled well ahead of carousels and photo posts. Here's a closer look at the numbers: 🏅 Videos claimed the top spot, earning a median engagement rate of 3.39% — 77% higher than carousels and photo posts at 1.92%.🥈 Carousels and photos placed second, but with a significant gap behind video.If you're aiming for engagement on TikTok, video isn't just a good bet — it's a significantly better one. 💡Using the median (middle value) rather than the average helps give a more realistic picture of how content performs for most creators and brands, without extreme outliers distorting the numbers.⏰Read more → The Best Time to Post on TikTokThe best content format on InstagramIt often feels like Instagram has gone all-in on video, with Instagram Reels getting their own discovery feed and even a dedicated video editing app. But our latest data says something different: carousels lead the platform with a 6.9% median engagement rate — higher than reels, single images, and stories. However, performance looks completely different when you look at reach, rather than engagement rate. Here's the engagement picture first. We looked at median engagement rate as a percentage of reach — in other words, how many of the people who saw your post actually interacted with it. 🏅 Carousels led the way, with a median engagement rate of 6.9% — the highest of any format on the platform.🥈 Stories came in second at 5.1%, though the sample size here is small (n=520), so treat that one with caution.🥉 Single images followed in third at 4.4%.4️⃣ Reels landed last, with a median engagement rate of 3.3%.But wait! cue video rewind sound effect This analysis is not the whole story. Here, we measured engagement rate. But reels are often optimized for views rather than these kinds of interactions, so a lower engagement rate doesn't necessarily mean reels aren't working. It may just mean people are consuming them differently. Also, the format breakdown above doesn't capture the full picture, because reach and engagement point in different directions on Instagram. A separate analysis of 4M+ posts published via Buffer between January 2022 and October 2024 showed us that: Reels tend to get the most reach Reels vs carousels: 1.36× the reach (+36%)Reels vs single-image posts: 2.25x the reach (+125%)Instagram has a dedicated reels discovery tab, so reels have a built-in advantage for reaching people who don't already follow you — formats that live only in the regular feed don't get that same boost. Carousels keep people on the post longer, meaning more chances to save, share, and comment, and potentially multiple chances to reappear in-feed. It's a bit like Instagram is two different platforms in one, depending on where you post your content. And which 'platform' you choose depends on the goal of your content. Fascinating, right? So while reels are great for discoverability (and getting more followers on Instagram), if your goal is deeper engagement from your existing audience, carousels might deserve more space in your content plan. The "best format on Instagram" has no single answer — it really depends on your goals. The short version: use Instagram Reels when you want to reach people who don't follow you yet, and carousels when you want to deepen engagement with the audience you already have. ⏰Read more → The Best Time to Post on Instagram in 2026The best content format on FacebookOn old faithful Facebook, images still lead at 5.2% — but the real story is how close the race has become. Images, videos, and text posts are all clustered within one percentage point of each other. Here's a look at the numbers: 🏅 Images took first place for engagement rate on Facebook at 5.2%, edging out the other formats.🥈 Videos followed closely in second at 4.84% — only 7% behind images.🥉 Text posts were close behind at 4.76%, just 9% below images.4️⃣ Posts with links came in last at 4.43%, drawing the lowest engagement of all content types on the platform.The really notable thing here isn't who won, but rather, it's how close the race has become. The clearest signal in this data is actually at the bottom: links continue to underperform everything else, which fits with the broader trend toward zero-click content. Platforms and their users increasingly prefer to stay put. ⏰Read more → Best Time to Post on Facebook in 2026The best content format on ThreadsThreads surprised me in our last analysis — and it's done it again, just in a different direction. This time, video has taken the top spot with a 5.55% median engagement rate, up from second place in our previous data. The numbers: 🏅 Videos claimed first place for engagement rate on Threads at 5.55% — 22% ahead of images and nearly double text posts.🥈 Images followed in second at 4.55%, still well ahead of the text-based formats.🥉 Text posts landed in third at 2.79%, with 19% more engagement than link posts.4️⃣ Posts with links came in last at 2.34%.What I find most interesting here is the continued gap between visuals (video and images) and text or links. For a platform that's built around conversation, visuals seem to stop the scroll more effectively. Worth noting if you're looking to grow on Threads! That said, Threads is still a young platform, and its algorithms are actively evolving — so keep a close eye on your own analytics here, and watch the Buffer blog for updates. ⏰Read more → The Best Time to Post on Threads in 2026The best content format on LinkedInIf you've read any of our previous data studies, this one won't shock you: LinkedIn carousels are still on top. Carousels earned a median engagement rate of 21.77%, 196% more than video and 585% more than text posts. The numbers: 🏅 Carousels (document posts) earned a median engagement rate of 21.77% — 196% more than videos, 234% more than images, and 585% more than text-only posts.🥈 Videos came in second at 7.35%, with 13% more engagement than images.🥉 Images followed in third at 6.52%.4️⃣ Links landed in fourth at 3.81%, drawing more engagement than text-only posts.5️⃣ Text posts came in last at 3.18%.Those carousel numbers are tough to ignore. A 21.77% median engagement rate is exceptional for any platform, let alone one as crowded as LinkedIn has become. That said, the advice I gave last time still stands — LinkedIn is evolving fast, and video is clearly the format the platform is pushing. In an episode of our podcast, Buffer Chat, LinkedIn's Head of Premium Content & Community Strategy, Callie Schweitzer, recommended that creators lean into video. "Video, Video, Video, Video," she said, when I asked for her growth advice. If you have the time and energy to do both, carousels for engagement and video for reach is a solid combination. ⏰Read more → The Best Time to Post on LinkedIn in 2026The best content format on XText still sees the most median engagement on X (formerly Twitter). Even with the social network’s much-talked-about desire to become “the everything app,” X remains true to its microblogging roots. Here's a closer look: 🏅 Text posts saw a median engagement rate of 3.56% — 5% ahead of images, 20% ahead of videos, and 58% ahead of link posts. 🥈 Images followed closely in second at 3.40% — the gap between first and second is now razor-thin. 🥉 Videos landed in third at 2.96%, with 32% more engagement than link posts. 4️⃣ Posts with links came in last at 2.25%.X is fundamentally a text-first platform — hot takes, real-time reactions, and punchy one-liners are what it was built for. But images have crept up to almost match text in engagement rate, which is a shift worth watching. Short video clips can also give you an edge over static posts if you have them. ⏰Read more → The Best Time to Post on Twitter/XThe best content format on PinterestI'll admit — I wasn't expecting this one. Pinterest is basically synonymous with beautiful still images, so video leading on engagement feels counterintuitive. But the numbers are pretty clear. The numbers: 🏅 Videos earned a median engagement rate of 5.75% — 83% higher than images. 🥈 Images followed in second at 3.15%.Pinterest has been investing heavily in video, and the data suggests those efforts are paying off in engagement. If you're using Pinterest primarily as a visual catalogue — which, honestly, is how most people still use it — it might be worth testing a few video pins to see if the engagement bump holds for your audience. The best content format on BlueskyBluesky is the newcomer on this list, and we're working with earlier-stage data — so treat this as a first look rather than a final verdict. That said, the early signal is clear: video leads with a median of 5 interactions, 25% more than images. The numbers: 🏅 Videos earned a median of 5 total interactions — 25% more than images. 🥈 Images followed with a median of 4 interactions. 🥉 Links and text posts tied in last, both earning a median of 3 interactions.A few caveats worth keeping in mind: Bluesky's user base is still relatively small compared to the other platforms in this analysis, and video content on the platform is far less common than images (253K video posts vs. over 2 million image posts in our dataset). We'll be watching this one closely as the platform matures. So, which content format is the best?As I touched on above, that really depends on you and your audience. What works for most creators or brands might not be the sweet spot for you, and it’s always, always worth experimenting with other content types to see what works. Perhaps even more importantly: What is the content format you’re going to be able to create most consistently? In other studies, we’ve found that content performance on all platforms is strongly linked to consistency. (In fact, it might yield as much as 5x more likes, comments, and shares across the board.) So if you’re going to be able to show up more consistently with text-based posts, great — stick to those. Back to video: while it performs well across nearly every platform — and is often really great for reach — it’s not universally the highest engagement format. On some platforms, like LinkedIn and Facebook, carousels and photos steal the show. On X, text still rules. My (probably oversimplified) summary of all these numbers: video is fantastic for reach and discoverability, helping you attract new followers and audiences. Other formats (carousels, images, text) can be better for engagement, deepening connections with your existing audience. Ultimately, the best content format is the one you can produce consistently — and the one that resonates with your target audience. View the full article

When electricity demand is set to surge—say, from a new power-hungry data center—the default response from a utility is often to build a new (and expensive) power plant and other infrastructure. A new report released by a cross-industry coalition called Utilize argues that we can make better use of existing power on the grid instead. Roughly half of the total capacity goes unused most of the time because the grid was built to meet spikes in demand. But as technology has shifted, it’s become easier to unlock that extra power. Smart thermostats, for example, can pre-cool your house when demand is lower. EVs can charge at optimal hours (and, in some cases, send power back to the grid when it’s needed.) Networks of home batteries, being rolled out by startups like Base Power, can also store power when demand is low and then provide it later. Data centers and other large power users can use load flexibility, moving their power use to certain times of the day. Sensors, software, and other new tech can help transmission lines carry more power. A mix of these solutions added together, along with others, can free up more power for new uses, from data centers and factories to millions of drivers charging new EVs. If new electric demand can be added without a major new investment in infrastructure—and more customers are actually sharing the same fixed costs—the cost of electricity can go down for everyone. The same solutions can also make the grid more resilient in extreme weather. “We’ve heard a lot about affordability of electricity in the last year,” said Utilize executive director Ian Magruder at a press conference yesterday. (The group includes members like Google, Carrier, and Tesla.) “We think that there are a lot of solutions being proposed, but our view is that this solution of grid utilization is one of the only near-term solutions that can meaningfully reduce the cost of electricity at scale in short order.” The report modeled what could happen at a typical midsized utility, and then calculated what the approach could mean nationally. By increasing grid utilization by 10% as electricity demand increases, the report says that consumers could save between $110 billion and $170 billion on electric bills over the next decade. That’s on top of savings that people could get from participating in specific utility programs that pay consumers to use appliances or charge EVs at certain times. Virtual power plant programs already exist throughout the country, and there are a variety of ways that they can scale up. Base Power, for example, owns the batteries that it deploys at homes (consumers save on electric bills and have backup power if the grid goes down, while Base Power makes money by selling the power it stores back to utilities). Utilities lead other programs. Hyperscalers could also help. “One interesting emerging model is referred to as the ‘bring your own distributed capacity’ model, where a hyperscaler like Google could come into a utility service territory where the hyperscaler is hoping to develop a new data center, and actually pay for these resources themselves,” says Ryan Hledik, a principal at the Brattle Group, a consultancy that partnered on the report. “For example, pay to expand the utility’s energy efficiency and demand response portfolio beyond what the utility was already planning to do. And then take credit for the new capacity that creates on the system.” Utilize is advocating for new policies that can help grid utilization grow, such as a newly passed bill in Virginia that will require utilities to provide grid utilization metrics to regulators for the first time, and incorporate those metrics into planning. “We see this as an exciting first step, and we think that other states are already interested in following,” Magruder told Fast Company. “We’ve received a lot of inbound [interest] from red, blue, and purple states. This is not a partisan issue.” The U.S. has been slower than some other countries to adopt grid utilization, but there’s more interest now. “I think the urgency hasn’t been there in the past,” says Magruder. “For 25 years, we had very stable load growth in this country. Electricity demand wasn’t meaningfully changing. The price of electricity that Americans pay was relatively stable. We’re in a very different environment now in the last couple of years, and that’s creating new political and economic pressures that are forcing us to think differently.” View the full article

Prediction markets like Polymarket and Kalshi have hit the headlines—not least because of their role in making some people filthy rich off the back of the Middle Eastern war. But they’ve also drawn the attention of legislators concerned about their growing prominence. Many officials have privately raised concerns about platforms like Polymarket and Kalshi. Arizona’s attorney general has gone further, charging Kalshi with offering what the state alleges are illegal bets on election outcomes. “Kalshi may brand itself as a ‘prediction market,’ but what it’s actually doing is running an illegal gambling operation and taking bets on Arizona elections, both of which violate Arizona law,” said Kris Mayes, the state’s attorney general, in a statement. At the same time, Sen. Chris Murphy and Rep. Greg Casar, both Democrats, have introduced the BETS OFF Act, which would ban wagering on government actions, terrorism, war, assassination, and events where an individual knows or controls the outcome. The recent developments are “wild,” says John Holden, associate professor of business law and ethics at the Kelley School of Business at Indiana University. “This is the most aggressive we have seen a state be with going after any of the prediction market sites.” Gaming law specialist lawyer Daniel Wallach adds that “this represents a true inflection point.” For Holden, what stands out is that Arizona is pursuing Kalshi under both general betting laws and specific prohibitions on election wagering. “Election wagering is something that many states prohibit via specific statutes,” he says. That approach could criminalize betting on elections, rather than relying solely on civil enforcement. “This is clearly an escalation,” says Karl Lockhart, assistant professor of law at DePaul University. The strategy itself marks a shift. “Arizona, and actually a lot of states, have these laws that forbid people from gambling on elections,” says Lockhart. Using those statutes to argue that Kalshi cannot serve customers in the state is a novel attempt to rein in the platform. “Arizona is going to be the first to test this, to see if this election betting law approach works,” he says. The companies’ expansion into a wider range of markets has helped regulators begin building a potential case against them—while also underpinning their rapid growth. In December, Kalshi was valued at $11 billion. But that diversification is also part of the companies’ defense. Lockhart says prediction market firms have broadened their offerings by arguing they are tied to real economic outcomes that users may want to hedge, from weather events to government decisions. The goal, he suggests, is to avoid resembling traditional sportsbooks. “They don’t want to just be purely offering sports contracts, because then it seems very, very clear that this is just what they’re doing,” he says. By offering contracts on elections, policy outcomes, and other real-world events, the companies can argue they are something more expansive—and more financially legitimate—than gambling sites. That argument has come under increased scrutiny alongside the BETS OFF Act. “Too often, prediction markets are becoming yet another place for rich and powerful people to cash in on insider information,” said Rep. Casar in a statement. “This bill will put a stop to that.” However, Wallach doesn’t believe this is going to be a perceived problem solved through legislation alone. “This battle over the legality of event contracts is going to be waged in the courts,” he says. More broadly, Arizona’s approach marks a significant escalation in enforcement. “The criminal charges are a different approach from the civil litigation that has been going on in a seemingly ever-growing list of states,” says Holden. “Ultimately, however, it looks like the ends that the state is looking for would be roughly the same, stopping prediction market sites from serving customers in the state, if they are not licensed and registered through the same channels as other gaming companies.” A Kalshi spokesperson said in a statement: “Sadly, a state can file criminal charges on paper-thin arguments. States like Arizona want to individually regulate a nationwide financial exchange, and are trying every trick in the book to do it.” (Polymarket did not respond to Fast Company‘s request for comment.) If Arizona succeeds in applying criminal election-wagering statutes to a federally regulated prediction market, other states may follow. “There are a number of states that have these election wagering specific statutes,” says DePaul’s Lockhart. “So it will be interesting to see if there are other states that are willing to sort of take this escalating the stakes for Kalshi.” For now, he says, it is a “very, very interesting, quickly evolving situation.” View the full article

It’s one of the trickiest questions for any leader, especially in times of transformative change: when to follow the herd and when to go it alone. Since taking the reins as CEO of Tubi in September 2023, Anjali Sud has been finding a unique path for the Fox-owned streamer. The biggest streaming services in the world—Disney+, Netflix, Prime—battle for premium content and subscription dollars. Tubi, meanwhile, has gone all in on free, with its on-demand streaming app and library of more than 300,000 movies and shows. Tubi was the first streamer to add a TikTok FYP-style video scroll to its mobile interface to help users discover new shows by replicating the UX of the social media app that competes for their attention. (Netflix has since launched its own version.) All of this aligns with the streamer’s strategy to target young people who have never had a cable subscription and prefer rabbit holes to broad buckets of content (an approach Sud has called “niche as core”). Tubi’s genre-spanning library includes everything from blockbusters like Jurassic World and originals like the young adult sports romance Sidelined: The QB and Me to content from a growing roster of social media creators including Jubilee, Kinigra Deon, and FunnyMike. It’s working. While user growth seems to have slowed after exploding from 64 million in February 2023 to 97 million by the end of 2024 (Tubi now has more than 100 million users), profitability has arrived earlier than expected. Tubi generated $1.1 billion in fiscal year 2025 revenue and closed its second consecutive EBITDA-profitable quarter at the end of last year, powered by 19% year-over-year revenue growth and a 27% surge in user engagement. I spoke to Sud about how she got here—and how she plans to maintain Tubi’s momentum in the face of ferocious competition. When you left Vimeo for Tubi in 2023, you wanted to redefine the streaming experience, especially for younger users. Take us back to that moment. What was your vision for Tubi? I had spent almost a decade at Vimeo, helping to provide tools for creators to tell their stories. What I learned from that experience was that creators need audience, and it helps if the experience is free. Gen Z, Gen Alpha—they expect that streaming should feel as easy and personalized as when they open up Instagram or TikTok. Where Tubi has approached it a little bit differently is that most of the [free advertising-supported television] platforms out there [e.g., Pluto TV and Roku] were taking live linear television and putting that [up] for free. You open up an episode guide, you scroll through channels, and you watch. We made a different bet: free on-demand streaming. Think of it like a free Netflix. We have Hollywood movies and TV series all on demand. We make original movies, we now have creator content on the platform—all on demand. Audiences want what they want when they want it. Tubi’s fans seem to both love it and gently mock it. I’m curious how you see that. Does Tubi have to be cool? Or does Tubi just have to be thought of with affection, as long as people are using it. I love it [the mocking]! I really do. For years, Tubi, we’ve had a little shade, particularly, I’d say, Hollywood, this questioning of, well— The B movies, yeah. Wait, are you premium? But actually, I’ll tell you, I think the root [question] for consumers is more like: What’s the catch? In a world where streaming prices are dramatically increasing while the amount of original content is going down, you’ve got Tubi improving its value proposition, growing its content library. There is no catch. Andrew Boyle Well, the catch for any ad-supported medium is that the user is the product. You get something for free, advertisers sell to you. Fair enough— we’ve been willing to make that deal for a long time. But let’s go a little bit deeper on the modern economics of free. What does it take to make free TV profitable right now? Scale. It’s a typical flywheel business. The more people we have watching Tubi, the better we are at understanding what they want. That allows us to monetize through ads that engage, which then allows us to reinvest in the content and the experience. If you look at Tubi’s growth in engagement, it’s not coming from a single hit [show or movie], it’s coming from that flywheel. As we get better at that—as that flywheel spins faster and faster—our margins will improve. That profitability and that improvement doesn’t come through cost cutting. It comes through growth. Is there a particular ad tech or feature that you feel has especially high potential? With the latest foundation models and machine learning, there’s still plenty of room to improve personalization. The average person today, when they turn on their television, it takes them over 10 minutes to figure out what to watch. It’s got to go down to seconds, and I do think it’s possible. Something like 20% of us just give up and start scrolling [social media] on our phone. There’s no reason why we shouldn’t get to a point where you’re immediately like: Oh, there’s something here I want to watch. And then with advertisers, it’s the same thing. It’s our job to make ads feel seamless, helpful, and useful to our audiences. We will use AI to analyze every single millisecond of content on our platform and contextually target an ad based on the scene, based on the sentiment and the feeling that the scene is evoking. What’s an example of that? Imagine you’re watching Fast & Furious, and you pause during a car-racing scene. First of all, we should be able to pop up stats and things that are relevant to that scene that you might find interesting. We should also be able to pop up a car ad that has the same sentiment and feeling—and maybe even makes a contextual reference—to the scene you were just watching. Let’s talk about “niche as core,” your strategy of embracing these culturally specific fandoms. First, we’re very committed to continuing to grow our library. Having a large library, it’s a listening tool. It’s a way for us to make sure we aren’t being prescriptive about what audiences want but letting them tell us what they want. We’ve recently added quite a lot of stories from creators. For each individual viewer, we know there’s a paradox of choice. When every viewer opens Tubi, we want to surprise them with something that our data tells us they might like, even though they wouldn’t know it. How do you define success for emerging storytellers on Tubi versus YouTube or TikTok? What is the pitch to them? It’s about expanding the pie for creators. We definitely don’t want to create a scenario where we’re saying: Don’t put your content on YouTube, or only put your content on Tubi. We’re not creating a walled garden. We’re not trying to own their IP or limit their creative freedom. And I think that approach is somewhat unique in the industry. When we talk to creators, what we hear from them—especially the ones that have already built thriving businesses—is that they just want to elevate their storytelling. They want to take more creative risks, they want to graduate into Hollywood in some instances, maybe they want to do more with longer-form formats. And if you look at the direction a lot of the other social platforms are going, they’re moving into even more short form. What is the default business model for creators on Tubi? Do you just calculate engagement and you give them a share of advertising, or is it more complicated than that? It’s actually the same pyramid we use for Hollywood content. We have nonexclusive content. Anyone can just work with us, and we will put their content on Tubi for a revenue share, very similar to what YouTube does. And then we listen. And when we see that our audience is really interested or fans are really interested in more from this creator, we will pay a licensing fee for an exclusive window on Tubi, all the way up to creating and producing and funding an original. You led Vimeo, which evolved into a SaaS company that made tools for creators. What did you leave behind as you transitioned to Tubi, and what did you bring with you? Both are businesses where technology is meeting creativity and storytelling, and you need to find a way to bring those two cultures together. And I actually think it’s very hard. We have to be at the intersection now of Silicon Valley, Hollywood, and Madison Avenue. You have engineers who are deep into ML [machine learning] research, having to work hand in hand with creatives on the Hollywood lot who are producing content, and then you’re having to translate all that to brands. And I think what I’ve learned is that those different cultures tend to be very siloed and there’s a lot of internal friction. How do you solve for that? First, the incentives have to be aligned. At Tubi, we have a single metric that we use to define success, which is viewer engagement. And increasingly, it’ll be viewer passion. It’s not just: Did somebody watch something? It’s: Did they love it? Did they comment on it? And every single [employee] has to feel like they will only succeed and fail if we are all together in that one thing. We just gathered our top 50 leaders in Orlando, Florida, last week, and we spent a lot of time together kind of working through the tensions and the trade-offs. What were some of the main tensions that you worked through? We have a core model and a business that’s working and growing, and yet there are so many other things we can expand into. There are so many different things that seem great, but which of these are just “shiny object syndrome” and which are actually leading indicators that this is the future? There’s no playbook for what Tubi is trying to do. The things we debate the most are: What are we going to stop doing? What are we going to say no to? Yeah, it’s such a hard question. There’s so much that you can do. Technology enables almost anything. But there’s only so much that you should do. We try hard to avoid the “let’s do this because other people are doing it” or because there are a lot of articles right now about how this is the new thing. That’s always a warning sign to me. And in our industry, there’s a lot of that. We try to think only about our audience. Instead of spending hours reading what everyone’s saying on podcasts and who’s buying who or all of that, it’s: How much time are we spending on Reddit or Wattpad understanding what fans are excited about? How much are we educating ourselves and taking the pulse on our culture and what our audience in particular cares about? How does your audience inform your leadership team? A diversity of perspectives leads to better decisions and better businesses. I’ve always been a big believer in that. The leadership team at Tubi is diverse. We are diverse from a gender, ethnicity, and industry perspective. We have the Silicon Valley technologists, we have the social-first brand builders, we have the Hollywood born-and-bred studio people. We just launched what we call the Tubi Builders Program for AI and machine learning. We have engineers right out of college, and we are letting them immediately build stuff on Tubi. We need the people who are AI-native, who are naturally embracing these new tools. And we have to hire people who represent the generation that we serve. If you look at our marketing team, there are a lot of Gen Z, socially native people on that team, as there should be. One of the best ways to have empathy for your customers is to have your customers on your team. Explore the full 2026 list of Fast Company’s Most Innovative Companies, 720 honorees that are reshaping industries and culture. We’ve selected the companies making the biggest impact across 59 categories, including advertising, applied AI, biotech, retail, sustainability, and more. View the full article

More than 50% of K-1 work now hits in a three-month crunch, By CPA Trendlines Go PRO for members-only access to more CPA Trendlines Research. View the full article

More than 50% of K-1 work now hits in a three-month crunch, By CPA Trendlines Go PRO for members-only access to more CPA Trendlines Research. View the full article

Get the scoop on monday.com with this comprehensive review. We'll take a look at its features, pricing and more to help you decide if it's the right tool for you. The post monday.com Review: Features, Pricing, Pros & Cons appeared first on project-management.com. View the full article

When FBI Director Kash Patel arrived at a joint training session with the mixed martial arts league UFC over the weekend at the FBI Academy in Virginia, he was wearing a custom pair of Nike sneakers that past directors wouldn’t have dared to step out in. Patel’s bespoke shoes were black, white, and yellow, and featured a number 9 on the side to signify that he is the bureau’s ninth director. A “K$H” logo on the tongue is Patel’s personal logo (FBI directors have personal logos now), and a skull from the Marvel character Punisher appeared across the back of the shoe, along with the FBI’s slogan “Fidelity, Bravery, Integrity,” according to images that a source sent to William Turton, a reporter for ProPublica who covers federal law enforcement. However, Nike didn’t design or produce the customized embellishments, Fast Company can confirm. A photo from a LinkedIn post that’s no longer public showed Patel color-coordinating his Nike shoes with a matching black-and-yellow hoodie and hat. The casual outfit was typical for Patel, who sold branded merch like hats and socks before taking his current job, and who showed up to the Winter Olympics in a team jersey, like one of the guys. It’s a stark departure from how his predecessors dressed, though. The FBI’s dress code, as set at the top of the organization, once symbolized strict professionalism. Now it screams podcaster-occupied government. A source sent me this photo of Kash Patel’s customized Nike’s. The shoes feature a number 9 (Patel is the 9th FBI director), a Punisher skull (a vigilante killer from Marvel Comics), and his personal logo (K$H). The backs of the shoes show the FBI motto: "Fidelity, Bravery,… pic.twitter.com/WWLXrLrP70 — William Turton (@WilliamTurton) March 16, 2026 When former FBI Director Robert Mueller served under former Presidents George W. Bush and Barack Obama, not only did he not stray from his uniform of dark suits, white shirts, and red or blue ties, but he would chide aides who ever wore shirts that were pink or blue, according to Garrett M. Graff, author of The Threat Matrix, about the FBI under Mueller. For Mueller, this conservative, professional dress was a matter of integrity, and it communicated continuity and tradition without drawing attention to itself. The only way you saw him was dressed for the job. Though Patel wore a white shirt, suit, and tie on Wednesday, when lawmakers questioned him and other national security officials, his accumulating fashion faux pas in other situations communicate another message entirely. It’s more MrBeast than Mueller—which is to say it’s flashy and done with an eye toward self-promotion and juvenile tastes. Everyone is 12. The tacky look of Nikes customized after-market with a personal logo and comic book character isn’t exactly what you’d expect from a 46-year-old in an important job overseeing a law enforcement agency that’s over a century old. (At least they’re not oversized Florsheims.) From an administration led by a president who has normalized casual, promotional branded dress in office, though, it’s really not that surprising. View the full article

Microsoft PowerToys feels like something that shouldn’t exist in Windows today. What started in 2019 as a couple of utilities for things like window and shortcut management has gradually expanded to nearly 30 useful tools, including a keyboard shortcut creator, an image-to-text extractor, and a better search bar than the one that’s built into Windows proper. PowerToys has become wildly popular among Windows power users, with more than 70 million downloads to date, but it’s also completely free, with no ads, Office upsells, or ham-fisted Copilot integrations. Instead of directly monetizing PowerToys, Microsoft sees it as a way to build goodwill among software developers and Windows enthusiasts while also incubating ideas for the future of Windows. It’s like a hippie commune within the Microsoft empire, building cool software mostly for its own sake. When I ask Principal Product Manager Clint Rutkas if a business model might ever emerge from all this, he seems almost taken aback by the question. “Nope,” he says. “Our goal is to empower power users to do more.” PowerToys 1.0 The history of PowerToys goes back a lot further than 2019, launching first as a free collection of utilities for Windows 95. Raymond Chen, an early Microsoft employee who is now a principal software engineer at the company, says those tools started out as a way for Microsoft’s engineers to experiment with new features. Windows 95 applications, for instance, could display their own options in File Explorer’s right-click menu, so Microsoft’s developers tested an option for viewing .CAB files. They also built a circular desktop clock to play with Windows 95’s non-rectangular window support and a way to switch display resolutions directly from the system tray. “They were ways of verifying the features that we were adding (to Windows 95) by actually using them,” Chen says. While PowerToys started off as just an internal experiment, Microsoft soon decided to throw the utilities on its website for download. The software came with no documentation and no tech support, but it quickly gained word of mouth through online user groups and became a hit with the PC press. “The important thing about the PowerToys is that they set you free to use Windows 95 the way you want to,” Paul Bonner wrote in the September 1996 issue of PC Magazine. After the initial release, PowerToys became less about releasing internal experiments and more about showcasing neat side projects, Chen says. Even if Microsoft didn’t deem a feature appropriate for Windows proper, a developer could still build it on their own and potentially get it into PowerToys. The bar for acceptance was low; Chen doesn’t remember ever rejecting anything that a developer submitted. Raymond Chen “Somebody would email me and say, ‘Hey, I got a cool PowerToy. Can you add it?’ And I’d be like, ‘Sure,’” he says. Over time, the PowerToys concept expanded within Microsoft. Chen himself spearheaded a set of PowerToys for the Windows Kernel, and Microsoft included a new set of PowerToys for Windows XP in 2001. Microsoft’s OneNote and Windows Media Player teams came up with their own PowerToys, and there was even a batch of PowerToys for Windows XP’s Tablet PC Edition. But in the early 2000s, a series of Windows security vulnerabilities brought the PowerToys party to an end. In response to computer worms such as SQL Slammer and Blaster, Microsoft decreed that it would no longer put unsupported software on its website. Chen recalls that any downloadable program needed a dedicated support person, an escalation path, and all sorts of burdensome onboarding. He couldn’t just round up a collection of .EXE files and slap them on Microsoft’s website as-is. PowerToys was effectively dead, and would stay that way for the next 15 years. “At that point, it’s just not fun anymore,” Chen says. “It didn’t discourage people from writing random side projects—everybody loves writing random side projects—it’s just that you lost a publishing model for them.” The comeback PowerToys went dormant until 2019, when Microsoft was looking to improve Windows’ credibility with software developers through things like Windows Subsystem for Linux and a modern command line terminal. Mike Harsh, Microsoft’s director of Windows developer experiences, had the idea to bring PowerToys back as part of that effort. “The mission statement was creating a bunch of really cool, super-powerful utilities and experiences for developers,” Rutkas says, the idea being that developers and power users would have overlapping needs. But this time around, Microsoft didn’t just solicit side projects from within. After announcing some potential ideas at its Build conference, it launched an open-source project on GitHub and began asking its community for feedback. Rutkas recalls an overwhelming response, both at Build and online. “We had no source code, and in under 24 hours, it had, I think 5,000 stars, which at the time was unheard of for a [GitHub] repository,” he says. Clint Rutkas Rutkas briefly left Microsoft in early 2019 for a job at Meta, but returned in the fall to spearhead PowerToys, just after its initial release for Windows 10. The first version included just a couple of utilities: One for arranging windows into preset layouts, and another for looking up keyboard shortcuts. Then it started piling on more, including a bulk file renaming tool, a batch image resizer, a keystroke remapper (for instance, to make caps lock do something else), and a way to search for open windows. Microsoft also began leaning on open-source developers for help. When the PowerToys team wanted to add a utility for extracting text from images, for instance, it turned to Joseph Finney, an independent developer who’d already built an open-source app for that purpose called TextGrab. Finney had a day job as a mechanical engineer and made apps in his spare time. When TextGrab came up in a discussion among PowerToys users on GitHub, Microsoft asked if he’d be willing to build a text extractor into PowerToys. Finney figured that if he didn’t do it, someone else would, and he saw it as a way to be part of a fun open-source project. “Ultimately, I’m like, ‘You know what? I’m getting my little goofy idea into the hands of more people. That seems like a big win,’” he says. Of the 28 utilities in PowerToys today, 12 of them credit the work of one or more open-source developers. Microsoft doesn’t pay for these contributions, but Finney says he’s benefitted in other ways, like earning a Microsoft MVP award and joining weekly calls with the PowerToys team. PowerToys is also one of the top referrers to his standalone TextGrab app, which has additional features and is available for free on GitHub or for $10 through the Microsoft Store. “Being an indie software developer who’s doing this nights and weekends, the big motivating thing is energy,” he says. “Being part of any community is where that energy comes from.” Future Windows ideas today Even if Microsoft doesn’t gain direct financial benefit from PowerToys, it’s at least succeeded in generating developer goodwill. On Microsoft’s GitHub page, it’s the second most-starred project behind only Visual Studio Code. But over the past few years, PowerToys has also become a proving ground for new Windows features. Joseph Finney’s Text Extractor utility, for instance, is still available within PowerToys, but its settings page now recommends using Windows 11’s built-in “Snipping Tool,” which includes its own text extractor inspired by the PowerToys version. PowerToys’ FancyZones tool, which lets users drag and drop windows into preset layouts, also helped inform the window tiling features in Windows 11. Rutkas says the Microsoft developer who originally built FancyTools worked on Windows 11’s tiling features as well. Why not just test these features through Microsoft’s preview versions of Windows? Rutkas says PowerToys lets the company try out new ideas faster, with rough prototypes that it refines through community feedback. And even if a feature does graduate to Windows proper, the PowerToys may still serve a narrower audience. “We’re helping out an extremely advanced user, so that lets us be a lot more free on the UI for certain things. But we can take those experiences and learnings and then bring them back into Windows,” Rutkas says. Some recent PowerToys developments seem more overtly aimed at becoming future Windows features. A tool called Advanced Paste, for instance, can use AI to rewrite or translate text in users’ clipboards, while the Command Palette tool is equivalent to the Spotlight search bar built into MacOS. Users can bring up Command Palette with a keyboard shortcut and use it to launch apps, locate files, search the web, and perform calculations. Users can even create and share extensions that add more features to the search bar. It’s by far the most ambitious tool that PowerToys offers. Rutkas won’t comment on whether tools like Command Palette will become core Windows features in the future, but it may not matter either way. What makes PowerToys great is that it exists on its own little island without overt pressure to become something bigger. Meanwhile, Windows proper has stretched out in so many directions that it’s lost sight of the basics, prompting Microsoft to acknowledge that it needs to rebuild trust again. Leaving PowerToys alone to do its own thing would be a start. “We’re testing, incubating, pushing the bleeding edge of a lot of these things,” Rutkas says. “We love developers on Windows, and this is one of the ways we help get very powerful experiences, very quickly, to our end users.” View the full article

Figure comes ahead of Bank of England decision on interest ratesView the full article

Google's John Mueller implies that Googlebot crawling 404 pages is a positive sign about that site's content. The post Google: 404 Crawling Means Google Is Open To More Of Your Content appeared first on Search Engine Journal. View the full article

See how much competitors spend on ads and use the data to plan smarter budgets. View the full article

Is it even worth having a kid in the AI era? It’s the question at the heart of The AI Doc: Or How I Became an Apocaloptimist, a new documentary about the promise, peril, and uncertainty surrounding artificial intelligence. Codirected by Charlie Tyrell and Academy Award winner Daniel Roher, the film follows Roher, a soon-to-be father, as he tries to understand how AI works, what risks it may carry, and what kind of world he and his wife are bringing their son into. Along the way, he encounters both AI’s loudest skeptics and its most ardent utopians. The film features dozens of experts, including CEOs like OpenAI’s Sam Altman and Anthropic’s Dario Amodei, longtime researchers concerned about the future, and critics like Tristan Harris, who also appeared in the 2020 documentary The Social Dilemma about the harms of social media. Ahead of its theatrical release on March 27, the film screened at SXSW, where AI hype and anxiety have been everywhere. While in Austin, Fast Company sat down with Tyrell and producer Ted Tremper to talk about the film, their process, and why the movie resonates—why, for example, after screenings, when the lights come up, strangers start talking to each other. This interview has been edited for length and clarity. What inspired you to create this film? Tremper: The purpose of the film is we wanted to make something that would—regardless of who you are, where you are—meet you where you’re at and create the invitation to ask yourself, What do I value? What are the things I care about? What are the things I value about my work and life? How can I develop intuitions about how the technology is being built so I can look out for what I need to protect and also the ways that it can benefit me? We try to be very clear in the film that if anybody tells you there’s a “good AI” and a “bad AI,” and we can get one without the other, that’s not how it is. You interviewed so many experts, but did you also interview average people? Tyrell: It was a thing that we were really looking at and considering as a narrative backbone of the film in some ways. For one reason or another, we opted not to use them, mostly because that became the main focus and purpose of Daniel’s character and story in the film. It gave a proxy for the audience to have a person who asked a lot of questions that people wanted to ask. Were you intentional with the structure—about starting with the AI realists and later interviewing the AI startup experts at OpenAI? Tyrell: When you’re new to [AI] and you go and you read about it, you’re gonna find the doomer stuff first. And then you’re gonna find that there’s this counter to that—the accelerationists—and then there’s a whole counter to both of those, which is the realists who will look at what’s doing right now. No matter what you look at and in what order, it leaves you in the space of, What are the actual answers and what is the plan? That’s why in the film we go to the CEOs, because they’re the guys building this. So they should have the plan, right? . . . Surely there are adults in the room who have a plan. And then, as you know in the film, you go there and there is no plan. So that puts the onus on the users, the non-technologists, to ask what we do. Were you guys disappointed with the answers they gave? Tyrell: Absolutely. As a filmmaker, you want people to be demonstrative with their emotions. Because that’s just how we’re used to watching films, where things are kind of elevated. Theater takes it way up here. Film takes it here, but in real life if you see someone who just got in a car crash, or watch their house burn down, they’re usually pretty flat. That’s the reality. So filmmaking is a storytelling technique where you have to demonstrate that in a human space so the audience watching knows that person is feeling on the inside. That really comes through in Daniel’s reactions, where you see his disappointment after hearing people with influence over the pace and direction of AI steamrolling ahead [despite being] worried. Tremper: There’s a section of the film where people talk about present-day harms. To me, those are the sense-makers, because they are the ones who are actually talking about the impacts. These are people like [AI journalist] Karen Hao, [Mozilla fellow] Deborah Raji, and others. It was super important to have them as part of the conversation. . . . The challenge is that because by and large the conversations have become siloed and adversarial—because of the nature of social media—a lot of them don’t actually realize that they agree on things. And so the sort of landing point of the film is that so much of it is about coordination. Tyrell: Everyone believes in their own truth that they decided in this space. And it’s really tough for people when you believe in something and you discern it as fact, to understand there could be other truths. And that’s what this technology is: It’s going to be more than one thing at the same time, . . . and everyone needs to kind of regain that understanding. Because right now, especially when everything is broken down in such binaries—good, bad, left, right—we’re so acclimated to this right-or-wrong nature. But people are way more complicated than that, and the issues that we’re facing and the technologies that we’re using are way more complicated. It seems to be a pretty emotional film for such a heady topic. Tyrell: People keep saying they weren’t expecting a film about technology to make them emotional. But you have to be emotional to face this technology, to realize what we have that separates us from something that isn’t technology, that isn’t human, to figure out what it is that we value. We need to decide what is important, what makes us, and how we can make that machine. It’s been interesting to see how there’s a groundswell of AI backlash that’s been bipartisan. Tremper: What you just described is a thing that will really give me hope. Because at a certain point, no matter how good the promises are that people are making, whether they’re politicians or people in the Big Tech companies, when the realities begin to become so asymmetrically shitty, [people] don’t care about promises anymore. If you promise me the future of education is going to be bright, but all I’m seeing is my kid is using ChatGPT for his homework, and my kid’s teacher is using it to grade that homework, there’s no actual human interaction happening. There are going to be tens of thousands of benefits and tens of thousands of trespasses against every part of our lives. If there’s one thing people take away from this film, [we hope] it’s that [AI] is not going to be either good or bad, it’s going to be both. The way you navigate this territory is just by looking at your life right now and asking What do I care about? Who do I care about? And how is this technology affecting me? After the Pentagon and Anthropic thing happened, 1.5 million people unsubscribed to ChatGPT. Five years ago, The Social Dilemma arrived when change felt almost too late. Is this meant to be more proactive? Tremper: That was actually one of the major challenges of starting the film, because we started it before ChatGPT 3.5 came out. I’m from Seattle; the joke I make is that a lot of this felt like we started making a documentary about Nirvana six months before Nevermind came out. Because it was just like nobody knows this is happening, this thing is coming, and now it’s become more ubiquitous. Tyrell: Even with the feeling [of being] too late after The Social Dilemma, you get to things when you get to them, and sometimes that means that you can’t lament how late you are when there’s still work that needs to be done, right? So The Social Dilemma was able to activate quite a lot of people and reorient a lot of people’s thinking towards social media, including my own. And I grew up as a digital native. Instagram was a cool thing once upon time. Now it’s just a mall. I can’t stand it. But that awareness of what was actually going on there [helped]. Was it too late? It would have been nice if it was earlier, but it’s not too late. View the full article

“The purpose of computers is human freedom.” – Ted Nelson, Computer Lib/Dream Machines (1974) The computer is as emblematic of the American dream as the automobile. Perhaps it’s only natural that Apple, HP, Adobe, Google, and Amazon were each launched out of a garage. It was inside the garage that the modern era of personal computers was born, where anyone could own the power to calculate millions, and then billions of processes per second. PCs are a tool designed to move us faster, with a hood you can pop open to soup up. We insist that our computers speed up every year if only because it’s proof of progress. The very term “personal computer” promises liberty and autonomy; this isn’t the bus, but a transistor-powered rocket carrying a payload of rare earth minerals and rainbow hued headlights. The PC shrunk whole industries of work to our desktops, driving our ambitions anywhere they wanted to go. Whether you were publishing without a publisher, creating art without a studio, balancing books without an accountant, or mailing without a post office, the computer offered an all-in-one device for self-starters—a business in a box. Like cars, we invest in new computers because they are more expensive to fix than keep. And they enable us to pursue the two most important American ideals: self-expression and capitalism. But half a century since the idea of the PC went mainstream, the personal computer as both a product and an ideal has never been more at risk. In the age of AI, companies are acquiring unprecedented amounts of hardware, driving up prices, and affecting the entire PC market along the way. It’s affecting everyone from Dell dudes to kids dreaming about a Playstation 6. You can call the PC endangered, or on the precipice of anthropogenic evolution. Either way, we’re currently shifting toward a world of consolidated processing, where the PC is trending toward a luxury item. Meanwhile, computation itself is becoming a utility, priced and positioned as intelligence that we rent on demand. Buying a computer today Computers of all types are generally more expensive to acquire today than they were a year ago. As companies including OpenAI, Google, Meta, and Amazon plan unprecedentedly massive data centers to process AI, they’ve gobbled up the available stock of chips—all while tariffs add an extra dollop of pain to one’s wallet. DRAM in particualr—the semiconductor inside computers that holds information used by the CPU—is the culprit, with prices ballooning by 172% in 2025. Then they grew another 90% in Q1 of 2026 alone. On top of that, the NAND flash memory powering most solid state hard drives has also been on the rise, up by 50% in Nov 2025 and projected to keep growing. In practical terms, this means a midrange gaming PC will cost hundreds more this year than last, as computer component prices have become one of the richest sources of memefodder on the internet. (Wedding gift, anyone?) Major OEMs like Dell and Acer are warning that 20% price increases are coming later this year. One analyst expects a 12% drop in desktop and laptop shipments. On one hand, 262 million PCs still sell every year, and sales were up 9% last year (though some of that was due to defensive purchasing as prices skyrocketed.) On the other, the PC hardly dominates mainstream computing these days. Smartphones already outsell PCs by 5 to 1. Hit first and hardest will be the low end of the PC market, where margins are tightest. Chromebooks shipments could drop by 28% due to component shortages. Meanwhile, our cheapest, most specialized proxy for a PC—game consoles—are also feeling the sting. Nintendo, Sony, and Microsoft all raised prices on their products in the last year, while Sony and Microsoft in particular need to plan how they’ll build their next generation of Playstation and Xbox. The next Xbox is rumored to cost $1,000 (almost doubling the price). Sony may delay the PS6, anticipated for 2027, until 2029 in hopes that hardware gets cheaper. PCs as we know them seem like they’ll be forced to evolve—they may offer you a familiar mouse and keyboard, but the insides will be a little bit different (with less power and customization). There may be no better sign of the times than the Macbook Neo. Apple’s latest laptop uses the guts of an iPhone to stay cheap, and it limits RAM to a mere 8GB that’s soldered right onto the motherboard. For a majority of people, the Neo has plenty of power, much like a 4-cylinder sedan can get you onto the same highway as a Ferrari. But as a “new” approach, its single core architecture is inherently limited for the most compute-heavy tasks—tasks like advanced media production and running local AI—even compared to Apple’s other budget machines like the Macbook Air or Mac Mini. Apple seems to be tacitly stating the obvious while it camped outside Samsung to negotiate lower RAM prices: People can’t afford PCs anymore. We need something neo. Intelligence is the new utility At the same time that PC ownership is costing us more, modern AI providers are stepping in with a rent-to-never-own alternative. They are structuring computers as a utility rather than a product. The PC is becoming less something that you buy a couple times a decade, and more a phenomenon that you pay for through the wires in perpetuity. That means your Gemini, Anthropic, or OpenAI subscription probably cost you about $20 a month today. NVIDIA, knowing its GPUs are in high demand to train AI, even lets you rent a GPU in the cloud through its GeForce Now service (also about $20/month). The tech industry has dreamed about this sticky subscription revenue for decades—consider how everything from the Adobe Suite to Spotify are now a monthly line item. Steve Ballmer promoted the future of the “cloud” back in 2009, as tech companies framed the consolidation of computing power from individuals to corporations as an event every bit as natural as the weather. As Sam Altman himself recently put it: “We see a future where intelligence is a utility, like electricity or water, and people buy it from us on a meter.” The true cost of this seemingly efficient setup isn’t just directly out of our pockets, though. These cost scale when you realize that modern LLMs are the very engine behind modern software and services. Apps, instead of running on their own servers (their own PCs hooked up to the internet, if you will) or even using servers from Amazon’s AWS, need to pay the meter every time their AI tools pick the brain of ChatGPT. Their expenses grow with your queries. You might pay for your own ChatGPT subscription, then pay for an app that’s paying for its ChatGPT subscription. In Silicon Valley, we can get an early peek at how this adds up. I’ve heard of one popular AI assistant that was paying $150/user per month, eating a majority of that cost to build market share. Meanwhile, the coders who are pushing AI to its limits discover just how quickly those Claude Code credits can go. A single employee can easily spend four to five figures a month on AI coding. The value of that expenditure is proving worth it since AI can effectively amplify their workforce (or in Amazon’s recent case, effectively reduce their workforce). But companies don’t own this power. They rent it. This trendline isn’t without pushback. As AI positions itself as a utility, we are seeing a countertrend from vibecoders fighting for autonomy. As AIs get better, they also get more efficient. These AIs can theoretically be run locally. But in current practice, they’re actually hybrids, running some things locally, and some in the cloud. OpenClaw arrived in 2026 as something of a Model T for personal AI…an AI for the PC era, if you will. All you need is a Mac Mini and an openness to risk to build your own customized assistant. (Oh, but you still need to connect to a subscription LLM to really put it to work—and Claude is a popular choice.) Perplexity created its own version of OpenClaw with what they call, wait for it, “Personal Computer.” Also built for a Mac Mini, it’s a Perplexity agent that can access your files and coordinate tasks for you. (Oh, but there’s a catch again: The AI processing still happens on Perplexity’s servers.) I get the desire people have to operate our own AIs. It’s the lingering promise of the PC: computational autonomy, or homesteading in the digital age. Especially in the long term, it feels like these homesteaders could use hyper processing efficient, open source AI models so well that the Anthropics and OpenAIs can’t compete on a majority of daily tasks. But in the nearer term, while the most technically proficient will certainly keep experimenting with local AIs with increasing capability, anything short of an AI crash seems to ensure that building these PC systems will only get more cost prohibitive. Because none of the frontier model providers has any incentive to ween you off its drip. The rise of the collective computer Later this year, we’ll be getting a look at OpenAI’s first piece of consumer hardware, something spiritually akin to the iPhone for the AI age. While we know close to nothing about it, it does seem part of a larger suite of AI devices from Meta, and likely Google and Apple, that are designed less like self-reliant PCs than they are sensors. Ever listening, seeing, and recording, they promise to bring AI’s brain to every part of your life. In this scenario, we’ve more or less abandoned the PC completely, as we’ve abstracted the computer from PC (ours), to smartphone (half ours, half a company’s), to something new (and theirs). Such AI hardware as we’ve imagined it is little more than a data collector—a nerve ending—for a greater, centralized machine. Our many AI computers distributed around the world would be like a massive, receptive body for corporate brains like Gemini and ChatGPT. That grand computer will not be a personal computer. It would be a collective computer, technically owned by the many but controlled by the few—the equivalent of installing a Nest thermostat but letting the power company set your home’s temperature. And while I’m not arguing that such a computer could be more capable than anything we’ve yet realized in the age of silicon, it is one we would own even less than the systems and services filled with strange terms and conditions today. That collective computer is not a hot rod you wax in front of the neighborhood, nor is it a sensible sedan that quietly ferries your children to school. It’s a train that will go only as fast and as far as you can shovel the coal. Unless it all goes off the rails, first. View the full article

Is Benjamin Netanyahu dead? According to this video posted on March 15 by the Israeli prime minister’s office, he’s alive and thriving. You may have seen it online, along with a rabid debate between the crowd who claims it is fake (it is not) and the people who say it is real (which is correct, as determined by fact checkers and independent intelligence analysts). But we are not here to debate about what is true or not. What matters is the debate itself. It’s another point of proof in our new normal: Since AI can make up believable new realities, people now doubt reality itself, using that claim to support their beliefs and push their agendas. The rumors of Netanyahu’s demise caught fire after the U.S. and Israel executed strikes on Iran on February 28. Following those attacks, the prime minister’s public appearances at military bases and targeted towns were heavily restricted, creating an information vacuum that Iranian state broadcasters eagerly filled with claims of his death. To squash the noise, his office dropped a casual clip on Telegram and X showing him grabbing a drink with an aide at The Sataf café on the outskirts of Jerusalem. To mock the assassination conspiracists, as Reuters pointed out later, he leaned into a Hebrew linguistic pun where the slang for “dead” translates to being “crazy about” something. Referencing a past video in which bad compression made him look like he had six digits, he tells his aide: “I’m crazy about coffee. I’m crazy about my people. They are behaving phenomenally. Do you want to count my fingers? You can. Here and here. See?” אומרים שאני מה? צפו >> pic.twitter.com/ijHPkM3ZHZ — Benjamin Netanyahu – בנימין נתניהו (@netanyahu) March 15, 2026 His bad puns and show-and-tell didn’t matter. Within minutes, the internet mobilized to declare the footage a forgery synthesized by artificial intelligence. Conspiracists pointed to the café’s cash register screen, falsely claiming it proved the footage was from 2024. “Got some serious questions about the validity of this blatantly obvious AI video…” one X user wrote. “Close up blur shot which looks more AI than the last one. Even the clothes look sketchy,” said another. “Credit where due though, they gave some good prompt this time.” Even Elon Musk’s Grok chatbot poured gasoline on the fire by confidently hallucinating and telling users the video was a “100% deepfake.” A labyrinth of mirrors But the Netanyahu footage is legitimate. Reuters confirmed that it was real by cross-referencing architectural details in the background with archival pictures of the establishment, as well as other photos and videos of the events. The verification team at Spanish national broadcaster RTVE ran the file itself through detection software like Google SynthID, Sightengine, and IVERES—all of which flagged the video as human-made. Furthermore, slow-motion playback clearly shows the café’s register displaying the time as “14:59” on March 15, 2026. The coffee shop itself uploaded photos corroborating his presence, and Netanyahu followed up the next day with another video of him chatting with locals on the exact same patio. As open-source intelligence analyst Tal Hagin pointed out to RTVE: “This is not AI.” He says that “the edits are quite normal, especially in a video recorded for a prime minister’s social media. Almost all the errors can be explained by the cuts and angles.” None of that evidence moves the needle anymore. This is like the case of the fake military influencer Jessica Foster, but reversed. With Foster, a million people willfully ignored obvious visual deformities because they desperately wanted her to exist. Here, people will instantly reject verified reality if it contradicts their ideological worldview. The perimeter of objective truth has been entirely vaporized by the computational power of silicon giants. We have essentially handed God-level reality-warping capabilities to any troll with a broadband connection and a few bucks to run the latest video-generation tools. Hagin summarized our current dystopia when those new models came out from China: “We are no longer at the stage where it’s six months away. We are already there: unable to identify what’s AI and what’s not.” As we predicted three years ago, this “fun” technological parlor trick will become the ultimate political weapon and bullying wrench, and a huge legal loophole, allowing defense attorneys to casually dismiss damning security footage in actual crimes. On the flip side, it will be weaponized to digitally frame the innocent and the weak. I’m beginning to think that not even an aggressive educational campaign about generative AI will change the course of society. Silicon Valley and its Chinese brothers have gotten us into a labyrinth made of mirrors that show a mix of dreamed-up and real stuff. One that is packed with the Minotaurs of misinformation, injustice, and desperation. And the worst thing is that I don’t think there’s an exit. It feels like a new infinite plane of reality that leads nowhere but to oblivion—unless governments force the technology companies to put a stop to it. Fat chance that is going to happen. View the full article

The more you use artificial intelligence, the less you fear it. At first, it’s easy to be intimidated by what it can do. The deeper you engage with it, the more the tool reveals its limits and, more importantly, the irreplaceable value of human judgment. I’ve worked with AI models and tools for more than a decade. From early machine learning applications in data analytics to the generative systems reshaping workflows today, I’m comfortable with the technology. Yet I’ll be the first to admit that I’ve felt the anxiety. I’ve lost sleep thinking about the pace of change, and what that might mean for the future. Like most parents, I worry about my child’s career prospects. Will the paths we once considered safe still exist when she enters the workforce? This is the time to look at history, which can offer us some perspective. You see, every major technological shift has triggered similar fears. What is different are the tools. What endures are the fundamentals of how organizations function and how people create value. Despite the headlines, we’re not moving toward a world where humans are subservient to machines. We are entering the era of the AI-augmented workforce. And in that era, the human element remains the most critical variable. The productivity ceiling has shifted At the organizational level, companies are experimenting. Leaders are trying to understand where AI creates value and where it introduces risk. But at the individual level, expectations are rising. AI can significantly increase output. Tasks that once required hours can now take minutes. It’s never been quicker to draft, research, code, and provide analysis. That shift can feel intimidating, but it doesn’t automatically mean longer hours or widespread irrelevance. It does, however, mean that the productivity ceiling has moved. If you’re not using AI tools, you might find yourself working harder to keep up. If you embrace them, you may find yourself producing more with greater efficiency. I’ve seen this firsthand in my own daily workflow. As with any transformative technology, there will be growing pains. You will make mistakes and waste resources. That process is part of how organizations learn what delivers real value and what doesn’t. The fundamentals have not changed Even with advanced AI systems, we still need people who understand how things work. We still need critical thinking. We still need the ability to define problems clearly before we attempt to solve them. Effective use of AI often comes down to asking the right questions. But asking the right questions requires foundational knowledge. Before we can prompt a system effectively, we need to understand the system we are trying to improve. AI can multiply output. It cannot replace the need to understand how systems function, how they fail, and how we respond when they do. In my classroom, I encounter students who struggle with basic digital organization. If they have weak foundational skills, layering sophisticated AI tools on top doesn’t create mastery. It creates fragility. Adoption lags behind innovation Technology almost always moves faster than institutions do. AI capabilities may advance rapidly, but corporate culture, governance structures, and workflow redesign take time. That lag can feel frustrating. It can also provide breathing room. The tools may be ready, but integration is gradual, not immediate. Workers who choose to engage and learn will be in a better position than those who wait for change to settle around them. How to use AI to your benefit A common fear is that AI will primarily be used to eliminate jobs. Some roles will evolve. Some may disappear. That is part of technological change. But in many small and midsize businesses, leaders aren’t focused on cutting staff. They’re focused on increasing capacity. Higher productivity creates room for growth, expansion, and improved service. They’re not thinking about doing more with less; they’re just thinking about doing more period. The challenge of abstraction AI introduces additional layers between human intent and the final output. As that distance grows, verification becomes more important. Expecting perfection from AI misunderstands what it is. AI systems training is based on human knowledge and behavior. They reflect our strengths and our blind spots. That’s why human oversight is not optional, but essential. As humans, our role is shifting from sole executor to orchestrator. It’s up to us to define the objective, review the output, and decide how we’ll use AI. Judgment remains central to it all. The importance of collaboration rather than replacement It is fundamentally human to create tools that extend our capabilities. The steam engine amplified physical strength. The computer amplified the calculation. AI amplifies pattern recognition and synthesis. But tools don’t replace the need for responsibility. They heighten it. The most successful professionals in the years ahead won’t be those who resist AI or rely on it blindly. There will be those who integrate human creativity, ethics, and contextual understanding with AI’s speed and scale. As humans, we tend to fear what we don’t understand. In business and technology, ignorance doesn’t create safety. It creates anxiety. The more you engage with AI systems, the clearer their limitations become. They’re powerful, but not omniscient. Currently, we’re in a period of technological exuberance where there will be disruption and missteps. That pattern has accompanied every major shift in how we work. What has endured through each transformation is the need for capable people. The fundamentals have not changed. We still need thinkers. We still need leaders. We still need the human touch. The workforce is not becoming obsolete. It is becoming augmented, and it’s a future that still needs you. View the full article

We’re excited to announce the judges of the 2026 Innovation by Design Awards. Innovation by Design honors the best projects and ideas across the design spectrum, as represented by our fantastic group of jurors, who come from some of the world’s most exciting design-led companies. You can read more about their expertise and backgrounds below. And remember to apply for the Innovation by Design Awards by April 11. Erik Carter, Designer Erik Carter is a designer, illustrator, art director, and writer whose work bridges commercial design and critical discourse. He has designed for Verso Books, The New York Times, MIT Technology Review, The New Yorker, and New Directions Publishing, and his essays explore the ethics, the contradictions, and the future of visual communication. Carter’s first book of essays, Design Harder, was published in 2025 by Book Ideas and is currently in its second printing. He has taught at the School of Visual Arts and the Pratt Institute, both in New York City, as well as the California College of the Arts, and he currently teaches at San Diego City College. Abidur Chowdhury, Head of Design, Hark Born and raised in London, Abidur Chowdhury has recently joined a new startup in California as its head of design. He’s interested in creating advanced intelligence with the goal of freeing people from the digital clutter of the technology we have today—in hopes of creating space for meaning, focus, and creativity. Prior to his current appointment, Chowdhury was a member of Apple’s industrial design team for seven years, helping craft a variety of Apple’s products used daily by hundreds of millions of people across the world. Prior to Apple, he had worked with many of London’s top design agencies. He graduated from Loughborough University with a Bachelor of Science degree in product design. Eames Demetrios, Director, Eames Office, and Chairman of the Board, Charles & Ray Eames Foundation Eames Demetrios is a multidisciplinary artist, storyteller, and filmmaker, and the leading global authority on his grandparents, the American designers and creative visionaries Charles and Ray Eames. As director of the Eames Office and chairman of the newly launched Charles & Ray Eames Foundation, he’s spearheaded efforts to preserve and expand their legacy for the past 35 years. His work has included curating exhibitions; overseeing authentic design reissues and collaborations with Herman Miller, Vitra, and Cassina; and restoring numerous Eames films. A prolific author, Demetrios has written several books—including An Eames Primer; Eames: Beautiful Details; Kcymaerxthaere: The Story so Far; and Essential Eames—which have been translated into more than 25 languages. His ongoing global art project, Kcymaerxthaere, reimagines storytelling through a parallel universe, with 159 installations in 30 countries across six continents—and counting. As a filmmaker, Demetrios has created more than 70 works of various lengths, and as a sought-after speaker, he has presented in 53 countries on subjects ranging from design and science to storytelling and scale, including the TED mainstage and many TEDx events. He lives in Los Angeles. Jay Kamath, Cofounder and Chief Creative Officer, Haymaker Jay Kamath founded the independent, Emmy-winning, L.A./NYC-based creative agency Haymaker in 2017. Since then, it’s grown a functioning couch-potato farm for Pluto TV, launched the Seattle Kraken, and let Ty Burrell teach kids what not to do with money through Greenlight. Before that, Kamath learned from the best at 72andSunny, R/GA, and Google, where he launched signature shoes for Kevin Durant and Kyrie Irving; brought an exclusive Jay-Z album to Samsung devices; and helped Kenny Powers complete a hostile corporate takeover of K-Swiss. In 2023, Haymaker became a certified minority-owned business. Kamath’s mom marked the occasion by feeding the whole company homemade Indian food. There were no leftovers. Originally from Augusta, Georgia, he lives in Culver City, California, with his wife, kids, and dog, and enjoys singing Enrique Iglesias songs poorly at karaoke. Arshiya Lal, Director of Corporate Development, Circ At Circ, Arshiya Lal is working alongside brands and the textile supply chain to bring the first blended textile-to-textile recycling solution to market. It’s probably no surprise that she’s also a devoted secondhand shopper and clothing-swap host, or that her personal fashion projects have included 3D-printed and cognitive clothing. Before joining Circ, Lal was head of product at the biotech company Modern Meadow, launching the startup’s first lab-created leather products with global fashion brands. And prior to that, she led enterprise blockchain partnerships at IBM to bring transparency to fragmented supply chains. Lal graduated with high honors from the Georgia Institute of Technology, studying finance and industrial design, and in 2022, she was named to her alma mater’s “40 Under 40 Alumni” list. Katy O’Brien, Head of Sustainable Innovation, New Balance Katy O’Brien serves as head of sustainable innovation at New Balance, where she is a passionate leader who’s committed to driving positive impact in the global footwear and apparel industry. Under her leadership, New Balance has joined The Footwear Collective, a nonprofit focused on advancing circularity in the sector, reflecting her belief that brands must openly share knowledge and collaborate to create meaningful change. O’Brien has a background in engineering and holds a master’s degree from MIT in system design, which she applies to tackling sustainability challenges across the full supply chain. Her focus areas include decarbonization, materials reuse, and product end-of-life—with a firm conviction that true sustainability requires transparency and trust across the industry. Zac Posen, Executive Vice President and Creative Director, Gap Inc., and Chief Creative Officer, Old Navy Zac Posen is the executive vice president and creative director of Gap Inc., and the chief creative officer of Old Navy. As creative director of Gap Inc., he serves as a cultural curator and creative partner to CEO Richard Dickson, and as chief creative officer of Old Navy, he leads design, merchandising, and marketing for the second-largest apparel brand in the U.S., and Gap Inc.’s largest brand. Posen is an award-winning fashion designer and entrepreneur, celebrated for his technical excellence and body-positive designs. Over 25 years, his extensive career has included red-carpet couture, ready to wear, accessories, and costume design. He was invited to be a member of France’s Chambre Syndicale de la Haute Couture, and his work has received awards from the Council of Fashion Designers of America (CFDA) and many others. During his tenure at his namesake clothing line, Zac Posen, he also served as creative director for Brooks Brothers women’s wear, designed secondary lines at the House of Z LLC, and redesigned uniforms for Delta Air Lines. His work has also been featured in the 2022 film The Outfit, the Sex and the City franchise, and in Ryan Murphy’s TV series Feud. Born and raised in New York, Posen attended London’s Central Saint Martins University. Gullivar Shepard, Partner, Michael Van Valkenburgh Associates Gullivar Shepard is recognized for his skill in navigating programmatic requirements, regulatory and jurisdictional hurdles, and problematic site conditions to create rich public spaces. With a background in architecture, his expertise ranges from the fine details of building landscapes to planning and managing the firm’s large, complex urban projects. These qualities bring an expanded interdisciplinary perspective to MVVA’s leadership. Since Shepard joined the firm in 1999, he has applied his integrated design approach to challenges such as ecological restoration, flood control, transportation planning, and choreographing connections to parks and waterfronts. He always aims to tease out the most powerful design solutions within the constraints of budget and site. His projects and research are a laboratory for innovative building methods, communication tools, and project management. Kelly Wearstler, Designer Kelly Wearstler is a designer and creative director whose work has shaped contemporary design and culture worldwide. Her Los Angeles-based studio spans architecture and interiors, product and furniture design, creative direction, and curation, operating as a multidisciplinary laboratory for new ideas. Known for her fearless use of texture, color, and historical reference, she has redefined contemporary interiors through an expressive layering of art, furniture, and materials across eras. Wearstler’s global practice has produced hundreds of objects and collaborations with partners including Bergdorf Goodman, Christofle, Farrow & Ball, Dior, and Louis Vuitton. Beyond design, she is an influential cultural voice through books, media, and her newsletter, Wearstlerworld, championing emerging creatives and exploring the evolving relationship between craft, technology, and design. Juliane Wolf, Design Principal and Partner, Studio Gang Architect Juliane Wolf is a design principal and partner in Studio Gang’s Chicago office. She designs and advocates for built structures that simultaneously serve the community and the environment. Wolf brings expertise in the design of sustainable public spaces, complex visitor-serving organizations, towers, and large-scale international projects. For the firm’s institutional clients, she has led the design of many award-winning projects, including the Writers Theatre in Illinois, the Arkansas Museum of Fine Arts, the St. Regis Chicago, and the Beloit College Powerhouse in Wisconsin. She is also the deputy lead designer for the O’Hare Global Terminal at the Chicago airport. Wolf is a graduate of the Architectural Association (AA) in London, where she received a Master of Science degree in sustainable environmental design, and remained there following graduation to teach as unit master at the Diploma School. She holds a Bachelor of Architecture degree from the Illinois Institute of Technology. Wolf has served as a juror for the American Institute of Architects (AIA), participated in panel discussions at the American Society of Landscape Architects (ASLA) National Conference, and lectured at the Chicago Committee on High Rise Buildings (CCHRB) and the Chicago Building Congress (CBC). Jason Yuan, Founder and CEO, Future Lovers Jason Yuan is the founder and CEO of Future Lovers, a social intelligence company. Previously, he co-founded AI startup New Computer and built Dot, a personal companion with narrative memory, and designed intelligent operating systems on Apple’s Human Interface team. His earlier work includes Mercury OS, a speculative operating system that generated UI from intent, anticipating the shift toward language-driven computing. Yuan studied graphic design at the Rhode Island School of Design, and theater at Northwestern University, and he has worked as an art director and motion designer with clients including Inez and Vinoodh, Klim Type Foundry, and FKA Twigs. View the full article

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