After Prompt Engineering
May 09, 2026
Prompting is the visible tip of a much larger skill. The real frontier is orchestration: designing the conditions under which people, models, files, schemas, scripts, and standards can produce trustworthy work together.
Entity-Neutral Skills and the One-Horse Race
May 09, 2026
What if skill belongs less to individuals than to configured systems? Human-machine capability now emerges across people, models, scripts, and institutions, raising a sharper question: can humans adapt fast enough?
Externalization as the New Expert Skill
May 09, 2026
Machines have learned to speak like people; now experts must learn to make judgment machine-operable. Externalization becomes the quiet craft of turning tacit standards into prompts, schemas, protocols, and reusable workflows.
The Attribution Problem After Human-Only Collaboration
May 08, 2026
The finished output no longer tells us who, or what, actually shaped the work. Attribution must move beyond authorship toward the functions of origin, transformation, control, validation, and stewardship.
The Hidden Labour of Externalizing Expertise
Expert machine use often looks like a simple prompt, but the decisive labour happens underneath. The hidden contribution is translating tacit judgment into constraints, examples, schemas, and correction loops a machine can follow.
Toward a Functional Attribution Matrix
“AI was used” tells us almost nothing. A functional attribution matrix would show who originated, structured, transformed, validated, enabled, and accepted responsibility for human-machine work.
Agential Turn in Human-LLM Activity
Chat was only the first public form of human-LLM activity. The real agential turn begins when models, tools, files, and people form durable systems capable of acting beyond a single conversation.
Adversarial Orchestration in Human-LLM Systems
LLMs tend to settle into agreeable, statistically central answers. Adversarial orchestration treats friction as a design principle, using constructive tension to pull human-LLM systems back toward adaptive intelligence.
From Parsing to Reading with LLMs
A research pipeline can become beautifully structured and still fail to read. This piece exposes the trap of parsing-as-progress and argues for LLM systems that treat structure as scaffolding for interpretation.
Toward a Functionalist Activity Theory
Activity theory was built for human tools, culture, and collective work. A functionalist revision asks how the theory must change when intelligent systems become active participants in adaptive activity.
Restructuring PDF Ideology
The PDF made scholarship look stable, but it also trapped knowledge inside page geometry. Restructuring PDF Ideology asks what scholarly texts become when rebuilt as structured, computable artifacts for human-LLM reading.
Intelligence Under Constraint
Freedom is not the absence of limits; it is competence within them. Intelligence Under Constraint argues that boundaries, pressures, and adversarial friction are the very conditions that make adaptation possible.
Orchestrating Closure with Conviction
Human-LLM work can drift forever unless someone decides what counts as enough. Conviction appears here as a system function: the force that stabilizes closure while keeping its risks in view.