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Essays, profiles, and reading notes on AI products, AI systems, adoption, agents, and company strategy.
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Start with the control layer for agents, context, tools, permissions, and human review.
Series Index AI Adoption That Actually Changes the CompanyUse the index instead of dropping into a middle chapter of the series.
Series Index Seven Powers in the AI EraRead the strategic power series from the table of contents.
AI The AI Builder’s Edge: 23 Patterns Across 264 ProfilesAcross 264 ai & machine learning profiles and 18,726 lessons, 23 patterns recur often enough to matter. They are not universal rules; recurrence indicates breadth within this collection, not agreement across an entire field.
Research Explainers When Do AI Agents Actually Need Blockchains?Jeremy Allaire argues that AI agents need economic infrastructure for payments, identity, and coordination. This explainer separates the functions that genuinely benefit from blockchains from those better handled by conventional systems, clarifying where onchain architecture earns its complexity.
Research Explainers AI Traffic Is Becoming Workflow TrafficOpenRouter's 100 trillion token usage study suggests AI demand is shifting from simple text generation toward reasoning, tools, code, and context-heavy workflows. This explainer maps what that change means for model providers, infrastructure, and the economics of serving AI.
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Mira Murati, a pivotal figure in artificial intelligence, has advanced a human-centric and responsible approach through OpenAI and Thinking Machines Lab. Her perspective keeps AI’s transformative potential tied to the question of how technology should serve society.
Jack Clark, co-founder of Anthropic and author of Import AI, connects journalism, policy, and AI research. His perspective examines the promise and risks of systems, including the technical and political work required to make them safe and reliable.
Andrej Karpathy, an AI researcher, builder, and educator, bridges pure research with practical execution. His idea of Software 2.0 captures a fundamental shift: technology moving from explicit human-written instructions toward programs produced by optimizers learning from data.
Jesse Zhang, co-founder and CEO of Decagon, focuses on applying artificial intelligence to customer support. Drawing on experience as a second-time founder, he offers a candid, practical view of what it takes to build a high-growth AI company.
Xiao Hong, founder and CEO of Manus AI, brings pragmatic product focus to artificial intelligence. His vision moves beyond chatbots toward agents that act, pairing “less structure, more intelligence” with open-source collaboration and turning thought into execution.
Yang Zhilin, founder and CEO of Moonshot AI, combines rigor with a long-term focus on AGI. His work on Transformer-XL and XLNet, followed by Kimi’s long-context capabilities, reflects a conviction that technological excellence should make AI more useful.
Arthur Mensch, co-founder and CEO of Mistral, brings scientific rigor and a European perspective to artificial intelligence. Drawing on DeepMind experience, he advocates an open, competitive, and decentralized ecosystem in which open-source principles can shape AI’s future.
Liang Wenfeng, founder of DeepSeek and co-founder of High-Flyer, moved from quantitative finance into AI. His strategy combines efficient open-source models, fundamental research, and young talent with a larger ambition: making China a contributor to global technological innovation.