Evaluation Frameworks (Evals) is systematic testing of model quality, safety, and capability. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0114, within the Workflow family. The core principle: systematic testing of model quality, safety, and 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
Systematic testing of model quality, safety, and capability.
Plain-English Definition
Systematic testing of model quality, safety, and capability.
Feynman Explanation
If you don't have evals, you have vibes.
Core Principle
Systematic testing of model quality, safety, and capability.
Mechanisms
Pending editorial review.
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Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
If you don't have evals, you have vibes.
Examples
- Domain-specific eval suites for every production model.
- AI quality engineering.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
The mistake with this element is treating it as irrationality. It is almost always a rational response to a payoff nobody wrote down. 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: if you don't have evals, you have vibes. 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, aI quality engineering. It is amplified whenever aI quality engineering. Inside organizations that shows up as aI quality engineering. 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 treat evals as core engineering practice, not an afterthought. Treat it as infrastructure. Once you can see it in your own system, most of the argument about culture resolves itself.
Famous Experiments
Pending editorial review.
Design Principles
- Treat evals as core engineering practice, not an afterthought.
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
Pending editorial review.
The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Treat evals as core engineering practice, not an afterthought.
Pending editorial review.
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.
Designing processes from scratch around AI capability.
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.
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 Evaluation Frameworks (Evals) 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 Evaluation Frameworks (Evals)
- What is Evaluation Frameworks (Evals)?
- Evaluation Frameworks (Evals) is systematic testing of model quality, safety, and capability. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0114, within the Workflow family. The core principle: systematic testing of model quality, safety, and 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 Evaluation Frameworks (Evals)?
- AI quality engineering. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-INC-0114).
- How is Evaluation Frameworks (Evals) exploited?
- AI quality engineering.
- How do you design around Evaluation Frameworks (Evals)?
- Treat evals as core engineering practice, not an afterthought.
- Which behavioral dimension does Evaluation Frameworks (Evals) belong to?
- Evaluation Frameworks (Evals) is classified in the Incentives dimension (INC) of the Human Behavior Taxonomy™, family "Workflow", class "AI-Behavioral Coupling". Its permanent identifier is HBT-INC-0114 and its evidence grade is C.