Our thinking on the System of Intelligence.
Talks, essays, and field notes from the practice — plus the outside reading that shapes how we work.
An introduction to Baser Potential.
A short overview of the thesis, the practice, and why the operating layer above your systems of record is where value now compounds.
The AI-Native Operating Model
Part three of three. The method we use to turn the six moves into a running system — one governed workflow, a factory, and an evidence record in ninety days.
Where the Agent Workforce Goes From Here for the Enterprise
Part two of three. Six moves that carry the discipline of a 34-agent company of one into enterprise infrastructure — policy, authority, evidence, and liability.
The Company of One, Running Thirty-Four Agents
Part one of three. What Allie K. Miller's AI workforce actually looks like — an AI chief of staff, six directors, thirty-four agents — and the discipline underneath it.
The AI Impedance Mismatch
Different cycles. Different speeds. Uneven absorption. Why intelligence is no longer the binding constraint on what AI delivers — absorption is — and the matching discipline required to bridge the gap.
You're Renting Your Company Back
The most convenient feature your AI vendor ships is the one that quietly becomes your System of Record — and why the Evidence Plane is the only real exit.
Awareness Is All You Need
On attention, awareness, and the inner posture required to build intelligent systems well. Tobias Yergin reflects on what the Transformer's central insight asks of the humans who deploy it.
The outside work that shapes our view.
A curated set of references — foundations, operating models, governance, and architecture — we return to often.
Systems of intelligence
The thesis that value is migrating from systems of record to a coordinating layer above them.
From System of Record to System of Intelligence
a16z · 2026Argues the next platform shift is a coordinating intelligence layer that sits above today's systems of record.
From Hierarchy to Intelligence
Block · 2026How Block is restructuring around intelligence as the organizing principle of the company rather than reporting lines.
Systems of Intelligence
Jerry Chen · Greylock · 2016Original framing of the layer above record/engagement systems and why it becomes the durable moat.
On the future of company-building with AI
Y Combinator · 2026YC's short note on how AI-native startups are being built with radically smaller teams and faster compounding loops.
Software 2.0
Andrej Karpathy · Medium · 2017The foundational essay reframing software as learned weights rather than hand-written code.
The State of AI Report
Nathan Benaich · Air Street Capital · 2024Annual industry survey covering research, industry, politics, and safety — the field's de facto yearbook.
OODA, sense-making, and decision velocity
Why an organization's loop — observe, orient, decide, act, verify — is the actual unit of competitive advantage.
Destruction and Creation
John Boyd · Defense and the National Interest · 1976Boyd's epistemological essay on how analysis and synthesis drive adaptive thinking under uncertainty.
The Essence of Winning and Losing
John Boyd · Boyd Archive · 1996Boyd's distilled briefing on the OODA loop as a contest of orientation and tempo, not mere speed.
Team of Teams
Stanley McChrystal · Portfolio · 2015How JSOC redesigned itself around shared consciousness and empowered execution to outpace a networked adversary.
Evaluation, evals, and trust
How serious teams measure whether an AI system is actually doing the work — and improving.
A Framework for AI System Evaluation
Anthropic · 2024Anthropic's working approach to evaluating model behavior across capability, safety, and real-world deployment.
NIST AI Risk Management Framework
NIST · 2023The US government's voluntary framework for governing, mapping, measuring, and managing AI risk in production.
Constitutional AI
Anthropic · 2022The original paper on training models to critique and revise their own outputs against a written set of principles.
Agents, gateways, and the runtime layer
Reference material on the orchestration patterns that make agentic systems operable.
The Rise of the AI Engineer
Shawn Wang · Latent Space · 2023Names the emerging discipline that sits between ML research and product engineering — and why it's a distinct role.
Patterns for Building LLM-based Systems
Eugene Yan · eugeneyan.com · 2023A practical taxonomy of evals, RAG, fine-tuning, caching, guardrails, and UX patterns for shipping LLM products.
Agents
Chip Huyen · Chip Huyen · 2025A clear, end-to-end primer on agent architectures, tool use, planning, and the failure modes that actually matter.
How to evaluate AI agents
Ben Hylak · howtoeval.com · 2026From code-aware evals to self-healing loops — what actually works for evaluating agents in production.