The Glossary

The terms I use to reason about the economics of intelligence - each defined here at the source, each backed by a full analysis. Two frontiers anchor the vocabulary: Joule Wars on the generation side (who produces the most useful intelligence per joule) and Proof-Adjusted Autonomy on the deployment side (how much of it you can prove and accept). The rest hangs off them.

Scarcity MigrationLAW · THE SCARCITY LADDER

The law that technology never destroys value: it relocates scarcity, and value pools at the next binding constraint. AI industrializes execution; the price moves to judgment, verification and accountability. → founding essay: Scarcity Never Dies. It Climbs.

Human SignalCONCEPT · PROVENANCE FRONTIER

Provable origin plus staked accountability: a named person put their reputation at risk behind the work. Not "made without AI" - a property of the author's exposure, not of the text. A model can write; it cannot author. → full definition & FAQ

Tail PremiumECONOMICS

The rising relative value of outliers when technology compresses the middle of a capability distribution. Competence priced like infrastructure; returns run to the ends machines can't flatten. → full definition & FAQ

Originality PremiumMETRIC

The measurable price gap between verified-origin work and generated work in the same market - the falsifiable form of Human Signal, measured on populations with preregistered thresholds. → preregistered predictions

Joule WarsCORE CONCEPT · GENERATION FRONTIER

The transition of the AI industry from competing on model capability toward competing on energy efficiency - who produces the most useful intelligence per joule. Frames AI, semiconductors, cloud infrastructure, power generation and geopolitics as a single economic system. → full definition & FAQ

Proof-Adjusted AutonomyCORE CONCEPT · DEPLOYMENT FRONTIER

The share of an organization's completed work that an AI system executes without human intervention and supports with independent, reliable and timely evidence. PAA = autonomous × evidenced × validated × on time - the four gates multiply, so a 90% raw-autonomy agent is routinely a ~60% PAA agent. → full definition & FAQ

Intelligence per jouleMETRIC

The ratio of useful cognitive output - tokens, decisions, solved tasks - to the energy consumed producing it. More fundamental than performance-per-watt: FLOPS per watt is dimensionally FLOPs per joule (the seconds cancel). → why joules, not watts

Proof DebtLIABILITY

The accumulated stock of AI-generated work whose verification cost, uncertainty or liability hasn't been resolved yet. Unproven assumptions, missing artifacts, decisions nobody can replay - deferred liability the P&L doesn't show until an incident, audit or customer claim prices it. → Proof-Adjusted Autonomy

Agent-hourUNIT OF WORK

Work performed by an autonomous AI agent rather than a human. Agent-hours run in parallel and don't consume a human's sequential attention - one person can direct 60+ in a day, breaking the 24-hour ceiling on individual output. → The Unit of Work Is the Agent-Hour

Verification costBOTTLENECK

The cost of confirming machine-generated output is correct. Models collapse authoring cost toward zero; verification cost holds - so it becomes the binding constraint on software work, and the skill that stays scarce. → Verification Cost Is the New Bottleneck

Revocation ExposureSECURITY METRIC

The operational risk that remains after authority is revoked but before every covered execution path stops accepting it: Revocation Completion Time × accepted action rate × irreversible impact. → Token Revocation Is Not an Endpoint

The harnessMOAT

The orchestration layer above the model - the tooling that holds your context, reads your codebase, executes your workflows. Models are swappable; the harness owns the switching costs and the customer. → Who Owns Your Harness?

Clearance warsPOLICY

The phase of AI competition where frontier capability ships not when it is built but when it is permitted - government clearance granted customer by customer. The gate, not the model, becomes the story. → The Model Wars Are Over. The Clearance Wars Begin.

Language world modelARCHITECTURE

A model trained to simulate the environment itself - predicting what the world will do next - rather than to pick the next action. Imagination before action, so agents can test plans against a simulation instead of the real, irreversible world. → Language World Models: Predict Before You Act

Social permission to burn tokensLEGITIMACY

Society's conditional tolerance for AI's energy consumption: if tokens don't visibly improve real outcomes, the license to spend scarce energy generating them gets revoked. Capability doesn't protect you; outcomes do. → The Social Permission to Burn Tokens

The liability stackADOPTION

The layered structure of legal responsibility that decides where AI gets adopted: widely in paperwork, slowly in decisions where a wrong answer has no settled owner. → The Liability Stack: Why Healthcare AI Stalls

Michał Piszczek

CEO / CTO / FOUNDER

CTO of Archdesk; founder and former CEO of Robotero (acquired), Rejsomat.pl, Inclify and Lextron.ai. This vocabulary comes from the essays on the blog - read the full profile.