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The Incentives Lab
HBT-INC-0154 · Dimension INC · Incentives

In-Context Learning

Models learning from examples in the prompt.

Workflow·AI-Behavioral Coupling·Grade C·draft· enriching…

Scientific Definition

Models learning from examples in the prompt.

Plain-English Definition

Models learning from examples in the prompt.

Feynman Explanation

Demonstration is faster than retraining.

Core Principle

Models learning from examples in the prompt.

Mechanisms

Psychological

Pending editorial review.

Behavioral Economic

Pending editorial review.

Neurological

Pending editorial review.

Evolutionary

Pending editorial review.

Sociological

Pending editorial review.

Computational

Pending editorial review.

Systems

Pending editorial review.

Inputs (Triggers)

Pending editorial review.

Outputs (Behaviors)

Pending editorial review.

Behavioral Signature

Demonstration is faster than retraining.

Examples

Everyday
  • Few-shot prompting.
Modern (Organizational)
  • Often the right answer before reaching for fine-tuning.
Historical

Pending editorial review.

Famous Experiments

Pending editorial review.

Design Principles

  • Master prompt engineering before investing in fine-tuning.

Measurement Approaches

Pending editorial review.

Evidence

Evidence Grade
C (A strongest → E speculative)
Replication
★★☆☆☆
Intervention Confidence
3 / 5
Consensus
Pending editorial review (HBT v1.0 auto-seed).
Limitations
Pending editorial review (HBT v1.0 auto-seed).
Open Research Questions

Pending editorial review.

Primary References

Pending editorial review.

Signature Section

The Perverse Incentive Lens™

How this behavior is exploited — and how to redesign around it.

Exploitation
Often the right answer before reaching for fine-tuning.
Amplifying Incentives
Often the right answer before reaching for fine-tuning.
Org Failure Modes
Often the right answer before reaching for fine-tuning.
Societal Failure Modes
Pending editorial review (HBT v1.0 auto-seed).
Ethical Considerations
Pending editorial review (HBT v1.0 auto-seed).
Redesign Strategies
Master prompt engineering before investing in fine-tuning.
Diagnostic Questions
  • Master prompt engineering before investing in fine-tuning.
Warning Signs

Pending editorial review.

Red Flags

Pending editorial review.

Intervention Playbook
Individual
Master prompt engineering before investing in fine-tuning.
Team
Pending editorial review (HBT v1.0 auto-seed).
Organization
Pending editorial review (HBT v1.0 auto-seed).
Policy
Pending editorial review (HBT v1.0 auto-seed).
AI Implications
Detection
Pending editorial review (HBT v1.0 auto-seed).
Measurement
Pending editorial review (HBT v1.0 auto-seed).
Mitigation
Pending editorial review (HBT v1.0 auto-seed).
Responsible Use
Pending editorial review (HBT v1.0 auto-seed).

Interactive Mini Network

Click any neighbor to re-center the graph and follow the threads of connection.

HBT-INC-0154 · INC
In-Context Learning
ILAgAgentAWAI-First Workflow De…CDConcept DriftCWContext WindowDDData DriftEmEmbeddingEDEval DriftEFEvaluation Framework…LBLatency BudgetMDModel Distillation

Knowledge Graph Neighbors

Version History

v1.1.0 · 2026-06-28Initial auto-seed from corpus.