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How to Get from AI-Assisted to AI Native

When considering the history of AI, Richard Sutton observed that brute force and compute scale has always trumped human expertise, and when you look for it, you can see this “bitter lesson” play out throughout tech history. In his keynote at Ai4 2026, Tim O’Reilly explains why grappling with the bitter lesson is the forge […]

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Software Factories, Light and Dark

The following article originally appeared on Addy Osmani’s blog and is being republished here with the author’s permission. A software factory harnesses loops at scale. You can run the loop with humans in it (light factory), trading judgment and concentration against speed and breakage. Or you can ignore the humans (dark factory) and let those

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Navigating the Modern Data Lexicon: A Working Vocabulary for the Semantic Era

The way we talk about data is changing faster than the way we build it. Every quarter a vendor ships a new approach, coins a new term for it, or quietly adopts a term someone else has been using and redefines it to fit the shape of their product. None of this is malicious. Every

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Architecting for the Knowledge You Can’t Capture

Every knowledge program seems to begin with the same request. A senior engineer is leaving in six weeks, and someone asks her to document the process she’s carried for years. She returns a clean flowchart of the happy path. The drawing is accurate and may even be elegant. It leaves out the thresholds she watches,

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Beyond Navier–Stokes: Who Controls Scientific Discovery?

Is the current furore in mathematics the canary in the coalmine for experimental science and knowledge work? This post was originally published in Vanishing Gradients on September 11, 2026. It’s been updated to address the subsequent declaration by 25 Fields Medalists and the debate about AI, mathematical progress, and research incentives. Science without understanding? “For

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Beyond Navier–Stokes: Who Controls Scientific Discovery?

Is the current furore in mathematics the canary in the coalmine for experimental science and knowledge work? This post was originally published in Vanishing Gradients on September 11, 2026. It’s been updated to address the subsequent declaration by 25 Fields Medalists and the debate about AI, mathematical progress, and research incentives. Science without understanding? “For

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Enterprise Analytics Beyond Dashboards: Intelligent Data Orchestration with LLMs

In 17 years of building enterprise data platforms, I’ve watched every organization eventually ask the same question: “Can I ask one question and get one answer across everything my company knows?” A finance analyst wants actual revenue from the warehouse, pipeline data from the CRM, commentary from planning documents, and market signals from external providers.

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The Interfaces Are Arriving

The most consequential AI news of the past year came from a standards body. In December 2025, Anthropic donated the Model Context Protocol to the newly formed Agentic AI Foundation, a directed fund under the Linux Foundation cofounded by Anthropic, Block, and OpenAI, with support from Google, Microsoft, AWS, Cloudflare, and Bloomberg. Six months earlier,

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Operating Mode as Runtime State: A Contract for Enterprise

During a service incident, a customer-remediation workflow is moved onto an emergency route because the situation is critical and the team needs a fast resolution. Approvals are shortened, a priority queue is opened, and an on-call agent is cleared to use an alternate procedure until the service recovers. The incident ends, but the route stays

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