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.
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
Structurally Unstructured: The Paradoxical Framework That Accelerates Learning
How embracing the tension between structure and flexibility creates ideal learning environments, fosters personalization at scale, and prepares individuals for an increasingly unpredictable world
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.
Loop Engineering in 2026, Part 2: The Outer Loop, Shared Memory, and How Loops Compound
Part 1 built a single agent loop. Part 2 is the systems layer: the outer loop that decides what to work on next, and the shared artifact store that makes independent loops learn from each other and compound into an operating system for continuous improvement.
Loop Engineering in 2026, Part 1: What an Agent Loop Is and How to Build One
The practical version of loop engineering: what an agent loop actually is, the six parts every loop is assembled from, how Claude Code's /goal works, a PR-babysitter you can build today, why iterations not tokens are the real cost, and when not to loop at all.
Running Claude Agents in Parallel: A Practical Guide to Doing More Than One Thing at Once Without Creating Chaos
A detailed, practical guide to parallel agent work in Claude Code: when to use Agent View, Agent Teams, and Dynamic Workflows, how worktrees and /batch keep parallel edits from colliding, how to monitor and control running agents, and the operating rules that keep it all sane.
Prompting Is the Interface, Not the Job: How to Become a Full-Stack AI Engineer
Prompt engineering is not dead, but prompt-only thinking is. The real craft is the system around the prompt: context, retrieval, tools, workflows, evals, guardrails, logging, and improvement loops. Here is the full stack and the order to build it in.
Midjourney Medical: A 60-Second Body Scan, a Spa, and the Real Junction in Healthcare
Midjourney is building a 500,000-transducer full-body ultrasound scanner and putting it in a spa. Past the spectacle, it sits on the real inflection in healthcare: the shift from scarce, reactive imaging to cheap, continuous body data, and the hard problems that decide whether that helps.
Reinforcement Fine-Tuning in 2026: Train a Small Model to Beat a Giant One (GRPO, RULER, ART)
A technical guide to reinforcement fine-tuning in 2026: why a fine-tuned small open model beats a giant one, how GRPO and RULER let agents learn from experience with no reward functions or labels, and the open-source stack (ART, Unsloth, Tinker) to do it.
GLM-5.2: The Frontier Coding Model You Can Actually Download
A deep, builder-focused breakdown of Z.ai's GLM-5.2: a roughly 744B mixture-of-experts model with a 1M-token context, released open-weights under MIT. What it is, what the benchmarks say (and the asterisk nobody mentions), what it costs on an API versus your own hardware, and when to reach for the open model nobody can ban.
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.
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.
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.
One Million Prompters: What Dubai Gets That Most Cities Don't
UAE's Minister of AI Omar Sultan Al Olama and the real Dubai bet on AI workforce training — and what it says about where talent competition is headed.
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.
India's Startup Story Isn't Being Written in Mumbai
Nandan Nilekani's digital public infrastructure bet is paying off — and the dividends are flowing to Tier-2 founders, not just metros.
Loop Engineering in 2026, Part 2: The Outer Loop, Shared Memory, and How Loops Compound
Part 1 built a single agent loop. Part 2 is the systems layer: the outer loop that decides what to work on next, and the shared artifact store that makes independent loops learn from each other and compound into an operating system for continuous improvement.
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.