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Treat the Agent Like an Employee · Hanh D. Brown

AI Agent Governance: Treat the Agent Like an Employee. An AI agent without identity, role, access, audit, performance, and a manager is not autonomous. It is unsupervised. The fix is six primitives and a kill switch. ai-governance ai-and-work ai-strategy An enterprise would never let a human employee through the door without an identification badge, an …

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Python Data Classes Beyond the Boilerplate

ContentsIntroductionBuilding a Baseline ClassControlling Fields With field()Creating Immutable DataclassesReducing Memory Usage With slots=TruePutting Everything TogetherWhat To Explore Next Introduction Most developers see Python dataclasses as a shortcut for avoiding repetitive dunder methods like __init__ and __repr__. So at first look, it seems like a simple way to write less code and move faster. In practice, …

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My Mother and Higher-Value Care · Hanh D. Brown

The Work AI Cannot Replace: My Mother and Higher-Value Care. AI abundance forecasts assume labor scales. Care work does not. A daughter’s hours are the hours the forecast does not see. The wall is closer than they say. caregiving aging-and-care ai-economics ai-careers Artificial Intelligence (AI) abundance forecasts share a sentence. The sentence promises automation will …

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Speculative Decoding on CPUs: Nearly 4x Faster Token Generation with DFlash

addresses the fundamental challenge of slow, sequential token generation in language model inference. DFlash speculative decoding support for CPUs was recently enabled in vLLM v0.25.0. In our testing with Qwen3.5-9B on an r8i AWS instance, powered by Intel® Xeon® 6 processors with Performance-cores, DFlash increased average token generation throughput to 3.92x that of the autoregressive …

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Sized for Fifteen Winners a Year · Hanh D. Brown

Venture Capital and AI: Sized for Fifteen Winners a Year. Old venture capital was a basketball team sized for fifteen winners a year. The redesign that scaled: share economics, centralize control, and grow sideways. ai-markets ai-strategy ai-economics For thirty years, every venture firm in the country was sized for the same number. About fifteen technology …

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Run Muse Glimmer for Local Vibe Coding with llama.cpp, DFlash, and Pi

Muse Glimmer is gaining attention in the local AI community and is being compared with Qwen’s 27B-class models. In many cases, it is performing better, especially for local coding and agentic workflows. Meta looks strong in the open-model space, and with a few more iterations, models like this could start competing closely with proprietary systems. …

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Distribution Decides Whose Values Win · Hanh D. Brown

Open Weights AI: Distribution Decides Whose Values Win. Open Artificial Intelligence models win distribution because they ship cheaper and modifiable. Distribution decides the global default. Values ride along with the winner. ai-policy ai-markets ai-safety Powerful countries are not picking the smartest Artificial Intelligence (AI). They are picking the cheapest one to deploy and the easiest …

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Why We Fine-Tuned SigLip (And Why That’s Not Always the Right Call)

This post was co-authored with Max Silfverberg (Data Scientist, AI Solutions Lead), Antti Hallavo (Lead AI Software Engineer), and Pontus Huotari (Lead Data Scientist). We work at Alma Media, a Finnish digital services, marketplaces and media company. One of our focus areas is developing AI/ML solutions for real estate listing services, where understanding image content plays an important role.  services handle hundreds of thousands of listings a year. Most of those come with …

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Three Layers, One Sentence Skipped · Hanh D. Brown

How to Read AI News: Three Layers, One Sentence Skipped. AI news conflates three different capabilities. The most important sentence is usually the one the announcement does not say. Here is the method for reading it. reading-ai-news ai-and-work ai-strategy Notice the word Artificial Intelligence (AI) in any news story you read this morning. The word …

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5 Real-World Use Cases for AI Agents Transforming Industries

  Agentic AI has officially moved from the research lab into enterprise production. In 2026, the AI narrative has shifted dramatically from conversational chatbots — systems that wait for human prompts to generate text — to autonomous AI agents. These systems can plan, execute, and adapt multi-step tasks across external tools, databases, and APIs without …

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