Start Here: What Attention Heads Is About
AI, Attention and the Practice of Seeing Clearly
I have spent the last few years thinking in public about AI, mostly on X.
That has been valuable. X rewards speed, compression, and cleverness. It trains you to notice weak signals early, find the interesting part quickly, and say the thing before the moment has passed.
But a lot of the work I care about now needs more depth.
Model launches are not just product announcements. They are changes in what is possible for builders. They are changes in what is possible for humanity.
Benchmarks are more than just scores. They are signposts to what kinds of work models can and cannot reliably do.
Agent systems are more than shiny new software services. They are a new way of interacting with the realm of information.
And underneath all of this is a deeper question I have lived with my entire life:
What is attention?
Not just transformer attention. Human attention too. The thing that determines what we notice, what we ignore, what we optimize for, what we believe, what we practice, and what and who we care about.
That is what “Attention Heads” is all about.
Attention Heads is a place for writing about artificial attention, human attention, and the practices that help us see more clearly.
Because the fulcrum of existence hangs on attention.
Most of the early writing here will stay close to AI and agentic engineering, because that is where my public work already has the most momentum and where the changes are happening fastest.
I will write about:
new AI models and why they matter
AI agents, coding tools, evals, memory, context, and harness design
research papers that matter for people building real systems
the competitive dynamics between OpenAI, Anthropic, Google, Meta, xAI, Chinese open-weights, coding-agent companies, infra providers, and open source ecosystems
practical patterns from my own work with Codex, Claude Code, Linear, GitHub, Obsidian, local tools, and long-running agent workflows
But I do not want the publication to be trapped inside machine-like AI commentary.
The larger territory is attention, intelligence, reality-testing, contemplative practice and living with a dynamic mind: how minds and machines perceive, model, reason, fail, recover, and sometimes see with greater clarity.
So over time I also expect to write about meditation, neuroscience, psychology,
philosophy, philosophy of science, contemplative practice, spirituality, and the
question of what it means to build powerful systems wisely.
The through-line is not “AI news.”
The through-line is seeing.
What changed?
What matters?
What is hype?
What is real?
What should builders test?
What does this reveal about minds, machines, incentives, attention, or agency?
That is the kind of writing I want to do here.
Who This Is For
This is for people building with AI who want more than launch-day summaries.
Engineers, founders, researchers, product people, agentic engineering
practitioners, and technical operators who are trying to understand what new
models, papers, evals, and tools mean for actual work.
It is also for contemplative and philosophically minded technologists: people
who suspect that the AI story is not only about automation or productivity, but
also about cognition, attention, agency, truth-seeking, and human flourishing.
If you want maximal hype, this will probably feel too slow.
If you want detached cynicism, it will probably feel too earnest.
The goal is something else: calm, evidence-backed interpretation for people
trying to build and think clearly in a world that’s rapidly evolving.
What To Expect
My plan is to publish at least one anchor essay or briefing each week, plus shorter Notes throughout the week.
The weekly pieces will usually fall into a few recurring formats:
Weekly Briefs on model releases, company moves, and AI-builder signals.
Research Translations that turn papers into practical builder implications.
Agentic Engineering Field Notes from real workflows and tooling experiments.
Competitive Maps of the companies and platforms shaping the AI stack.
Reading Bench posts with a few things worth reading, testing, or carrying
into the next week.Occasional essays on human attention, world models, contemplative practice, and philosophy.
The Notes will be faster: insights from the essays, a paper quote with the
practical implication, a question for builders, a chart or benchmark that
deserves interpretation, or a small observation from the workbench.
X is not going away for me. It is still useful for discovery, conversation, and
testing ideas quickly.
But I want Substack to become the durable home: the place where the best ideas
are easier to find, revisit, forward, disagree with, and build on.
Why Now
AI is moving from chat interfaces into autonomous agentic systems that effect society.
The important questions are becoming less about whether models can produce a
good answer in isolation and more about whether they can participate in longer
loops:
Can they hold context?
Can they use tools?
Can they recover from mistakes?
Can they verify their work?
Can they coordinate with people and other agents?
Can they improve the system they are part of?
That shift makes the builder side of AI much more interesting.
It also makes the human side more important.
As more cognition gets routed through models, agents, feeds, assistants,
recommendation systems, and synthetic text, the quality of our attention starts
to matter much more. What we notice, what we trust, what we reward, and what we
practice will shape the systems we build and the people we become around them.
That is the reason for this publication.
Not just to follow AI.
To understand what it is doing to work, attention, judgment, and the way we see.
An Invitation
If that sounds like your kind of room, subscribe.
Reply and tell me what you are building, what you are watching, what you think I
am missing, or which papers, tools, models, practices, and questions deserve a
closer look.
I am especially interested in hearing from people working at the edge of AI
systems: coding agents, evals, memory, tool use, research translation,
human-in-the-loop workflows, contemplative practice, philosophy of science, and
the messy boundary between better tools and better attention.
This is the start of the archive I wish I already had:
AI, attention, consciousness, and the practice of living fully.