San Francisco's AI startups are pushing workers to grind endlessly, hinting at pressures soon hitting other sectors Not long after the terms "996" and "grindcore" entered the popular lexicon, people started telling me stories about what was happening at startups in San Francisco, ground zero for the artificial intelligence economy. There was the one about the founder who hadn't taken a weekend off in more than six months. The woman who joked that she'd given up her social life to work at a prestigious AI company. Or the employees who had started taking their shoes off in the office because, well, if you were going to be there for at least 12 hours a day, six days a week, wouldn't you rather be wearing slippers? "If you go to a cafe on a Sunday, everyone is working," says Sanju Lokuhitige, the co-founder of Mythril, a pre-seed-stage AI startup, who moved to San Francisco in November to be closer to the action.

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WIRED spoke with Boris Cherny, head of Claude Code, about how the viral coding tool is changing the way Anthropic works. Engineers in Silicon Valley have been raving about Anthropic's AI coding tool, Claude Code, for months. But recently, the buzz feels as if it's reached a fever pitch. Earlier this week, I sat down with Boris Cherny, head of Claude Code, to try to understand how the company is meeting this moment. "We built the simplest possible thing," said Cherny. "The craziest thing was learning three months ago that half of the sales team at Anthropic uses Claude Code every week."

Hume AI's CEO, Alan Cowen, will join Google DeepMind along with several top engineers as part of a major licensing deal. Google DeepMind is hiring the CEO and several top engineers from Hume AI, a startup working on emotionally intelligent voice interfaces, as part of a new licensing agreement, WIRED has learned. Financial details of the deal are confidential, but Hume AI says the company will continue to supply its technology to other frontier AI labs. The deal is the latest sign that AI companies expect voice mode to become an increasingly important interface for interacting with customers--and that understanding a user's emotions and mood based on their voice interactions is key. Hume AI expects to bring in $100 million in revenue in 2026 as it works with AI labs on tuning AI models to be more capable and useful voice helpers, says John Beadle, cofounder and managing partner of AEGIS Ventures, which invested in Hume AI.

You've Never Heard of China's Greatest Sci-Fi Novel Thousands of authors. is barely known outside China--but it contains the secret to the country's modernization and malaise. Ma Qianzhu was unsatisfied with Chinese progress. An engineer at a large state-owned enterprise, he belonged to a generation that grew up believing engineering is destiny, that China's future would be built, bolt by bolt, by people like him. Then Ma discovered something extraordinary: a wormhole to the late Ming Dynasty. With more than 500 peers, he commandeered a ship and traveled back in time 400 years, to a preindustrial China wracked by foreign invasion and internal decay. Their mission: trigger an industrial revolution in the past that would, in the future, make modern China great (again).

Initial participants in the new Apple Manufacturing Academy tell WIRED that the tech giant's surprising frankness and hands-on support are already benefiting their bottom lines. An instructor at the Apple Manufacturing Academy in Detroit demonstrates how an iPhone and optical inspection software can be used to photograph and automatically identify an issue with a part. About 10 Apple employees spent some of their valuable hours over recent months on a project that might seem unusual for the tech giant: customizing an open source AI tool for ImageTek, a small manufacturer in Springfield, Vermont whose lines of business include printing millions of labels for food packaging. The Apple engineers developed a computer vision system to automatically identify color errors, and on one run it picked up bacon labels with a far-too-pinkish beige before they got shipped, according to Marji Smith, ImageTek's president. She says the timely catch helped ImageTek from losing a crucial customer.

AI coding is now everywhere. But not everyone is convinced. Developers are navigating confusing gaps between expectation and reality. So are the rest of us. Depending who you ask, AI-powered coding is either giving software developers an unprecedented productivity boost or churning out masses of poorly designed code that saps their attention and sets software projects up for serious long term-maintenance problems. The problem is right now, it's not easy to know which is true. As tech giants pour billions into large language models (LLMs), coding has been touted as the technology's killer app. Both Microsoft CEO Satya Nadella and Google CEO Sundar Pichai have claimed that around a quarter of their companies' code is now AI-generated. And in March, Anthropic's CEO, Dario Amodei, predicted that within six months 90% of all code would be written by AI.

Abstract--We demonstrate the importance of persona-based multi-agents brainstorming for both diverse topics and subject matter ideation. Prior work has shown that generalized multi-agent collaboration often provides better reasoning than a single agent alone [1]. In this paper, we propose and develop a framework for persona-based agent selection, showing how persona domain curation can improve brainstorming outcomes. Using multiple experimental setups, we evaluate brainstorming outputs across different persona pairings (e.g., Doctor vs VR Engineer) and A2A (agent-to-agent) dynamics (separate, together, separate-then-together). Our results show that (1) persona choice shapes idea domains, (2) collaboration mode shifts diversity of idea generation, and (3) multi-agent persona-driven brainstorming produces idea depth and cross-domain coverage. Brainstorming has historically been a human-centered activity where diverse individuals bring unique knowledge and perspectives to generate novel ideas. Locke's theory of knowledge formation emphasizes that combining and abstracting experiences across multiple people leads to more complex ideas. Similarly, since the 1950s and '60s, design thinking frameworks emphasize the importance of multiple participants generating and refining ideas through structured exploration of brainstorming to generate ideas for a pre-defined question [2]. These design thinking frameworks use a set of cognitive, strategic, and practical procedures for ideation [2] and for this paper we focus on'brainstorming' as an area of exploration for multi-agent collaboration. Brainstorming is normally done with multiple and diverse humans standing at a whiteboard together brainstorming ideas against a topic area that is put on the whiteboard.

Large vision-language model (LVLM) based text-to-image (T2I) systems have become the dominant paradigm in image generation, yet whether they amplify social biases remains insufficiently understood. In this paper, we show that LVLM-based models produce markedly more socially biased images than non-LVLM-based models. We introduce a 1,024 prompt benchmark spanning four levels of linguistic complexity and evaluate demographic bias across multiple attributes in a systematic manner. Our analysis identifies system prompts, the predefined instructions guiding LVLMs, as a primary driver of biased behavior. Through decoded intermediate representations, token-probability diagnostics, and embedding-association analyses, we reveal how system prompts encode demographic priors that propagate into image synthesis. To this end, we propose FairPro, a training-free meta-prompting framework that enables LVLMs to self-audit and construct fairness-aware system prompts at test time. Experiments on two LVLM-based T2I models, SANA and Qwen-Image, show that FairPro substantially reduces demographic bias while preserving text-image alignment. We believe our findings provide deeper insight into the central role of system prompts in bias propagation and offer a practical, deployable approach for building more socially responsible T2I systems.