Writing · Field notes from the operating layer
Essays, field reports, frameworks, and technical guides for the people responsible for making AI work.
Current essay · Models & Engineering
Chatbots continue and coordinate symbolic information. A different class of model represents how a bounded environment may change, often conditioned on action. Both are useful. Treating them as the same thing is why enterprise AI conversations keep talking past each other.
Start with the work closest to the decisions you make.
Six editorial lenses. Each starts from a point of view, not a topic label.
Multi-part arguments, ordered as published.
Series / world-models
A four-part guide to the models that represent state, action, and possible consequences, and how they will combine with language systems.
Series / qwen38-local-wow
A five-part investigation into how the harness and serving stack make Qwen3.8-27B useful: the reasoning dial, the harness delta (raw local 2/8 → harnessed 8/8), verified demos, portfolio economics, and native 262K context on 32 GB.
Series / agent-native-work
A four-part series on designing work for agents: why software got them first, every domain's AGENTS.md, the verification gap, and the practitioner-builder.
Series / llm-os-modes
A six-part series on the operating modes behind frontier AI: Chat, Agent, Deep Research, Cowork, and owned infrastructure.
Series / rent-vs-own
An executive series on the AI ownership ladder and the strategic shift from rented tokens to durable assets.
Series / token-economy
A strategy and architecture series on token economics, model portfolios, and AI factory operations.
Series / context-compilation
The missing systems layer between retrieval and reasoning, from benchmark blind spots to measured evidence.
Series / autonomous-stack
The architecture of intelligent systems, from the data substrate to agent runtimes and prescriptive intelligence.
Series / agent-societies
A field guide to what happens when agents interact at scale, from emergence to competence.
Series / semanticstudio
A production-oriented series on building an enterprise RAG and multi-agent system.
Series / ai-native-computer
A technical and operating-model series on what changes when AI becomes the computer, not just another app.
Complete index
16 essays
Field Report · August 17, 2026
An independent lab investigation. The same open-weight model, served two ways, produced either an empty afternoon or a daily driver. What changed was the harness, not the weights. A newcomer-friendly entry to a four-part series.
Field Report · July 27, 2026
A Sunday project to delete myself from twenty data brokers turned into the clearest argument I have for a design rule most enterprise agent architectures ignore: an agent needs the capability to act on a secret, not the secret itself.
Framework · July 10, 2026
Computer science has had rigorous definitions of 'agent' for 30 years. The industry took about two to break the word — and the cost isn't semantic. Agent-washing misprices risk in both directions: the safe systems get over-governed and the autonomous ones get under-governed. Here is the L0–L5 ladder I use to keep the term honest, and the governance that should follow each level.
Technical Guide · July 9, 2026
AGENTS.md is not a document. It is an interface stack — MCP tools, skill catalogs, policy packs, and audit streams — with a README on top. Five translations, one procurement boundary, and the difference between agent-legible and Potemkin agent-ready.
Framework · May 18, 2026
The difference between a chatbot and a coworker is state. Claude Code, Cursor, Operator, Codex, ChatGPT Projects. Persistent memory, skills, knowledge base, environment access. Session-long state — and the most dangerous un-governed surface in the enterprise today.
Technical Guide · May 11, 2026
Deep research is not a bigger chat. It is three sub-systems pretending to be one — a planner that decomposes the question, a swarm of agents that search in parallel, and a synthesizer that does a long-context reduce. 5 to 15 minutes. Hundreds of thousands of tokens. And the richest audit trail of any mode.
Technical Guide · May 4, 2026
Agents are not a model. They are a loop. One Agent turn equals 5–50 Chat-mode calls, plus tools, plus state, plus a kill switch. Here is what you actually pay for when Cursor writes a PR — and what enterprise governance must cover that Chat-mode governance does not.
Framework · March 29, 2026
Today's agents wait to be asked. Tomorrow's will tell you what you're missing. The shift from reactive to prescriptive is where agents become genuinely valuable.
Research Note · March 22, 2026
Agent runtimes have crossed from frameworks to operating systems. ZeroClaw, OpenFang, and OpenClaw represent three competing philosophies for giving agents a durable lifecycle.
Research Note · February 15, 2026
Societies generate priors. World models generate consequences. Verification generates truth. Here's the architecture that turns emergent behavior into emergent competence.
Research Note · February 8, 2026
Emergence isn't enough. Most agent societies will collapse into confident sludge. Here's what separates the ones that compound from the ones that collapse.
Research Note · February 1, 2026
I've been watching agents build a society. The emergent behaviors appearing when large numbers of agents interact without human orchestration point to something bigger than better chatbots.
Technical Guide · January 26, 2026
Why SemanticStudio uses specialized domain agents instead of one general-purpose assistant, and how to configure and manage them—from 12 to 50+ agents.
Technical Guide · January 3, 2026
RaaS isn't a pricing model—it's the commercialization of an execution loop. Here's what Result Contracts look like, how the Outcome Control Loop works, and what providers and consumers need to make outcome-based models real.
Technical Guide · December 31, 2025
A lot of agent talk still sounds like old SaaS talk. In production, the pattern that works is simple: the core is stochastic, the shell is deterministic. You don't trust the agent—you bound it.
Technical Guide · December 1, 2025
Design patterns for multi-agent AI systems that actually work in production environments.
