AI-First Workflow Design is designing processes from scratch around AI capability. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0028, within the Workflow family. The core principle: designing processes from scratch around AI capability. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
Scientific Definition
Designing processes from scratch around AI capability.
Plain-English Definition
Designing processes from scratch around AI capability.
Feynman Explanation
The right question is what we'd build if AI had always existed.
Core Principle
Designing processes from scratch around AI capability.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
The right question is what we'd build if AI had always existed.
Examples
- Greenfield deployments that out-perform retrofitted ones.
- Major strategic opportunity for incumbents.
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Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
This is one of the elements leaders describe as a values gap. It is a payoff gap. The mechanism underneath it operates in the Incentives dimension — what makes behavior more or less likely?. You can recognize it in the field by its signature: the right question is what we'd build if AI had always existed. Every element in the Incentives dimension changes the perceived payoff of an action before the action happens, which is exactly where incentive design has leverage.
How it gets exploited
Left undesigned, major strategic opportunity for incumbents. It is amplified whenever major strategic opportunity for incumbents. Inside organizations that shows up as major strategic opportunity for incumbents. The pattern is the same one Goodhart's Law describes: the measurable proxy attracts the effort, and the purpose behind it quietly loses funding.
How the Lab designs around it
The redesign move is to run parallel design exercises: existing-workflow + AI-first. Measure the behavior, not the sentiment. A survey will tell you how people feel about this; only observed action tells you whether it changed.
Famous Experiments
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Design Principles
- Run parallel design exercises: existing-workflow + AI-first.
Measurement Approaches
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Evidence
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The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Run parallel design exercises: existing-workflow + AI-first.
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Pending editorial review.
Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
AI system that takes actions to achieve goals, often across tools.
The relationship between inputs and outputs changes.
How much input the model can process at once.
Underlying data distribution changes over time.
Vector representation of content for similarity and search.
Evaluation suites that no longer reflect real-world conditions.
Systematic testing of model quality, safety, and capability.
Models learning from examples in the prompt.
How much delay the user experience tolerates.
Train a smaller model to imitate a larger one.
Performance degradation as real-world data shifts.
Multiple specialized agents coordinating on tasks.
Where AI-First Workflow Design is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- Field guideIncentives: definition, types, examples
The parent field guide for this element.
- ReferenceThe laws of incentives
Goodhart, Campbell, and the Cobra Effect.
- EssayAI Agents Inherit Your Incentives
How this element propagates into automated systems.
- ReferenceThe incentive glossary
Definitions for every mental model, bias, and fallacy in the corpus.
- CourseIncentives 101
The free ten-part primer on reading a payoff structure.
- ReferenceThe Periodic Table of Human Behavior
The full 1,267-element map this page belongs to.
Questions about AI-First Workflow Design
- What is AI-First Workflow Design?
- AI-First Workflow Design is designing processes from scratch around AI capability. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0028, within the Workflow family. The core principle: designing processes from scratch around AI capability. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
- What is an example of AI-First Workflow Design?
- Major strategic opportunity for incumbents. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-INC-0028).
- How is AI-First Workflow Design exploited?
- Major strategic opportunity for incumbents.
- How do you design around AI-First Workflow Design?
- Run parallel design exercises: existing-workflow + AI-first.
- Which behavioral dimension does AI-First Workflow Design belong to?
- AI-First Workflow Design is classified in the Incentives dimension (INC) of the Human Behavior Taxonomy™, family "Workflow", class "AI-Behavioral Coupling". Its permanent identifier is HBT-INC-0028 and its evidence grade is C.