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Google Made the Web Worse and Is Now Making AI the Same Way
SEO ruined the web by making content optimize for algorithms rather than readers. AI is creating the same incentive structure — same cause, same outcome.
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AI Meeting Notes That Don't Embarrass You — The Local Setup
How to set up private AI meeting notes on a Mac with MacWhisper, whisper.cpp, BlackHole audio routing, and local LLM summarization. Includes a structured summary template, speaker diarization workarounds, and recording consent rules.
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Local LLMs with Ollama: When a local 7B beats a cloud 70B in latency-sensitive loops
A field-tested take on when a local 7B beats a cloud 70B in latency-sensitive loops with Local LLMs with Ollama: what it rewards, where it breaks, and how to keep the workflow honest.
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How the Meaning of Premium Product Is Changing in 2026
Explore how premium products are being redefined in 2026. Learn why longevity, sustainability, privacy, and invisible quality now matter more than.
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Why Benchmarks Are Lying to You About AI Progress
AI benchmarks are contaminated, over-optimized, and poor proxies for real capability. Why the numbers in every AI press release are less meaningful than they appear.
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The Multi-Mac AI Cluster — Insane Overkill or the Future?
Can you build an AI cluster from multiple Macs? A hands-on look at exo distributed inference on Apple Silicon, Thunderbolt bridge performance, real token-per-second numbers, and when a Mac cluster beats one big Mac Studio.
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Agentic coding: How to review a PR an agent opened in the middle of the night
A field-tested take on how to review a PR an agent opened in the middle of the night with Agentic coding: what it rewards, where it breaks, and how to keep the workflow honest.
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When Software Becomes Invisible: The Ideal State of Technology
Explore why the best software becomes invisible during use. Learn how technology achieves its ideal state when users focus on their goals rather than the.
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The Next Billion AI Users Won't Speak English. That's a Bigger Problem Than You Think.
AI's English-language bias is measurable, systematic, and being systematically deprioritized. What it means for global adoption and who's trying to fix it.
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Why I Downgraded From the Biggest AI Model — and Got Better Results
The contrarian case for small local LLMs on Apple Silicon. Why downgrading from a 70B to an 8-14B model improved real productivity through latency, iteration speed, and prompt discipline — plus the escalation rule for when big models still win.
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MCP servers: Composing agents over a catalogue of shared MCP tools
A field-tested take on composing agents over a catalogue of shared MCP tools with MCP servers: what it rewards, where it breaks, and how to keep the workflow honest.
