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Essays, profiles, and reading notes on AI products, AI systems, adoption, agents, and company strategy.
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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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Constraint decay explains why AI coding agents struggle when backend work carries real architectural and database rules. The paper traces how requirements fade across long trajectories and proposes stronger constraints, memory, and verification.
Yann LeCun is a Turing Award-winning computer scientist and architect of convolutional neural networks whose AI vision prioritizes world models, self-supervised learning, and open-source intelligence while questioning the industry’s reliance on scaling large language models and AGI hype.
Geoffrey Hinton is a pioneering neural-network researcher whose five-decade journey runs from early advocacy of connectionism to urgent warnings about existential risk, tracing a profound change in how he understands intelligence, computation, and humanity’s technological future.
Scott Stevenson, co-founder and CEO of Spellbook and a computer engineer by training, brings lean experimentation to legal technology, exploring how large language models can improve contract drafting through a philosophy of human-AI augmentation.
Dean W. Ball, a technology policy fellow at the Mercatus Center at George Mason University, examines AI, governance, and reindustrialization, advocating state support for technological diffusion and infrastructure instead of restrictive regulation aimed at individual models.
Richard Ngo, an AI researcher and philosopher with experience at OpenAI and DeepMind, brings technical and philosophical rigor to alignment and governance, asking how humanity can safely navigate the emergence of superintelligent autonomous agents.
Burkay Gur, co-founder and CEO of fal.ai, builds infrastructure for high-speed generative media, combining experience in high-throughput machine learning with insights on vertical integration, visual communication, and the rigor required to scale AI systems.
Michele Catasta, president and head of AI at Replit and a former Google Labs and Stanford researcher, works to narrow the gap between human intent and machine execution through autonomous agents and natural-language interfaces.