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
8 essays
Framework · September 10, 2026
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.
Research Note · September 10, 2026
Rehearsal is where world models earn their keep — exploring possible futures inside a bounded scene before acting. But visual plausibility, controllability, physical executability, and downstream task utility are separate properties, and current systems succeed at some and struggle at others.
Research Note · August 25, 2026
A preregistered local deployment study of DeepSeek-V4-Flash-0731 on a dual-DGX-Spark cluster found a practical tie with Qwen, severe effective-context limits, and blocked frontier comparisons.
Field Report · August 19, 2026
Qwen3.8-27B can hold its native 262K context window on one RTX 5090. The reason is architectural, and the serving stack matters as much as the weights.
Field Report · August 16, 2026
A free 27B open model on a home RTX 5090 drove the car-wash trap 5/5 where GPT-5.2 walked. The lesson is not local-beats-cloud. It is that default posture is not capability.
Field Report · August 16, 2026
An offline 8-task workday, synthetic privacy drills, and six verified one-file browser demos. Same weights, better harness, and the honest economics of owning versus renting.
Technical Guide · April 27, 2026
One prompt in. One response out. Fourteen infrastructure layers in between. Reasoning models are still Chat Mode — they just rent the GPU for longer. Here is what actually happens, and why it is still one machine.
Technical Guide · January 26, 2026
What separates demos from deployable systems—SemanticStudio's quality evaluation, hallucination detection, and enterprise observability.
