The questions worth sitting with
How Not to Be Very Powerful Broken People
A tool amplifies whoever holds it. As we pick up the most powerful tools in history, the decisive variable is not the machine but the human. Why becoming fully human is the work of this age.
The Second Brain That Works While You Sleep
How I built a local agent swarm that processes raw notes overnight — scouts, catalogers, critics, editors — and leaves a morning briefing in plain Markdown.
Being Human in 2035
Elon University's Imagining the Digital Future Center canvassed nearly 300 global experts on what AI changes about being human. The answers were less reassuring than you'd hope.
The Seventeen Percent Problem
McKinsey's 2025 workplace AI report found a 3x gap between what leaders think employees are doing with AI and what employees are actually doing. That gap is the real crisis.
Seven of the Top Ten Skills Are Human
The WEF Future of Jobs Report 2025 said the quiet part loud: the skills that matter most in the AI era are the ones machines can't replicate.
Learn Anything Faster: The Science of Rapid Skill Acquisition
A practical playbook for rapid skill acquisition: deconstruct any skill, drill the high-leverage 20 percent, and reach useful proficiency in weeks.
The Teacher's Mindset: Education in the Age of AGI
In a world of super-intelligence, the most valuable skill isn't solving problems. It's defining them. We must all think like teachers.
The Personal Operating Layer: Your Digital Twin
Imagine an agent that knows your context, habits, and preferences. It's not just an assistant; it's your Personal Operating Layer.
Reliability in Chaos: The New Skill
In a fast-changing world, what you know matters less than what you can reliably do in a situation you've never seen before.
Talent Development Is Infrastructure
Why education needs to stop being a social service and start being treated like a power grid.
Systems Thinking: Why Understanding Connections Beats Analyzing Parts
How viewing challenges through relationships and patterns creates more effective solutions, deeper understanding, and better outcomes than traditional reductionist approaches
Build a Claude Code Agent Team That Loops Until the Work Is Actually Done
A builder+checker agent team in Claude Code that cycles through build → check → fix until all tests pass, with hard stop rules to prevent token burn.
Talking to Computers: The Shift from Typing to Agents That See, Click, and Speak
Computer-use agents that drive software and voice agents that speak back are colliding. Here's what that actually looks like to build and what's still broken.
How to Build Powerful Web-Search Agents That Actually Work
Nine concrete techniques for building web-research agents that are fast, cheap, and don't hallucinate — from query decomposition to adversarial cross-checking.
Cut Your Coding-Agent Bill, Part 1: Where the Money Actually Goes
Most of your coding-agent bill is grind, not genius. Part 1 of 3: how token pricing really works, why the loop bleeds you, and the plan-high, execute-cheap fix you can apply today.
Cut Your Coding-Agent Bill, Part 2: Route the Loop to a Cheaper Model
Part 2 of 3: point the coding agent you already use at a cheaper open-weight model with two environment variables. Which models hold up for execution, how to wire it, and the real economics.
Cut Your Coding-Agent Bill, Part 3: Run the Loop on Your Own Hardware
Part 3 of 3: take the agent loop fully local. Ollama, llama.cpp and vLLM, quantization and VRAM math explained, the OpenAI-compatible local endpoint, and exactly when owning the hardware beats renting tokens.
The Agent OS: How a Personal AI Agent Actually Works
A personal AI agent feels like it's thinking about you. It isn't. It's a cron job, a database, and a model. Here is the seven-layer architecture, layer by layer, with the underlying tech and the security trap.
You Grew a Mind. Now Read It: A Field Guide to Mechanistic Interpretability
A first-principles walkthrough of mechanistic interpretability: superposition, sparse autoencoders, and circuits, and how we are learning to read what a language model is actually doing.
How AI Changes Work: From Personal Tool to Org-Wide Teammate
AI at work is moving from a personal tool to a shared teammate. The three shifts rewiring how teams operate: single to multiplayer, sync to async, reactive to proactive.
Automated Development: Soon You Won't Write Code, You'll Build the Machine That Does
The job is shifting from writing code to building the pipeline that writes and ships it. A field guide to automated development: the history, the mechanism, and what comes next.
Build a Claude Code Agent Team That Loops Until the Work Is Actually Done
A builder+checker agent team in Claude Code that cycles through build → check → fix until all tests pass, with hard stop rules to prevent token burn.
The Second Brain That Works While You Sleep
How I built a local agent swarm that processes raw notes overnight — scouts, catalogers, critics, editors — and leaves a morning briefing in plain Markdown.
AI Is Becoming Society's Operating System. Nobody Voted for That.
Shannon Vallor argues AI mirrors our past back at us. My worry is something more structural: it's quietly becoming the infrastructure that decides who gets to participate.
Talking to Computers: The Shift from Typing to Agents That See, Click, and Speak
Computer-use agents that drive software and voice agents that speak back are colliding. Here's what that actually looks like to build and what's still broken.
How to Build Powerful Web-Search Agents That Actually Work
Nine concrete techniques for building web-research agents that are fast, cheap, and don't hallucinate — from query decomposition to adversarial cross-checking.
The Founder's Stack 2026: One Person, a Team Chart of Agents
The company you used to raise a seed round to build now fits on one laptop. The solo-founder stack of 2026, layer by layer: your engineer, your back office, your marketing, your face, and how to set each up.
We Have the Power. We Don't Have the Wisdom.
Dario Amodei's 'Adolescence of Technology' names something real: we are handing civilization-scale power to systems we don't fully understand yet.
Cut Your Coding-Agent Bill, Part 1: Where the Money Actually Goes
Most of your coding-agent bill is grind, not genius. Part 1 of 3: how token pricing really works, why the loop bleeds you, and the plan-high, execute-cheap fix you can apply today.
Cut Your Coding-Agent Bill, Part 2: Route the Loop to a Cheaper Model
Part 2 of 3: point the coding agent you already use at a cheaper open-weight model with two environment variables. Which models hold up for execution, how to wire it, and the real economics.
Cut Your Coding-Agent Bill, Part 3: Run the Loop on Your Own Hardware
Part 3 of 3: take the agent loop fully local. Ollama, llama.cpp and vLLM, quantization and VRAM math explained, the OpenAI-compatible local endpoint, and exactly when owning the hardware beats renting tokens.