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The Incentives Lab
AI Incentives · Economics

Prompt Caching

Cache common prompt prefixes to reduce cost and latency.

"Don't pay twice for the same setup."

Quick answer

What is Prompt Caching? Cache common prompt prefixes to reduce cost and latency. Cost optimization in production deployments.

In the wild

Common system prompts cached across calls.

Why it matters in the room

Cost optimization in production deployments.

Counter-move

Architect for cache reuse.

Visual · Reward gradient
REWARD ↑OPTIMIZER →
Prompt Caching shows where an optimizer climbs vs where we want it to go.
Live example · Train around Prompt Caching

Pick what to reward the model for.

Cache common prompt prefixes to reduce cost and latency. In the wild: Common system prompts cached across calls.

● Live

Pick a lever. There are no neutral ones — every incentive funds a behavior somewhere.

How does this land?

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Human Behavior Element™ · HBE Spec

The full taxonomy entry

Every concept in the Atlas uses the same structure — so Prompt Caching can be compared, recombined, and cited like an element on a periodic table.

About the standard →
A
PC
HBT-A5102
Official name
Prompt Caching
AI Incentives · Economics
Identity
HBT ID
HBT-A5102
Symbol
PC
Official name
Prompt Caching
Synonyms
Economics
Keywords
AI Incentives, Economics, human behavior, incentive design
Version
v1.0
Last updated
Maintained by The Incentives Lab
Classification
Kingdom
Systems
Domain
Machine Behavior
Family
AI Alignment & Incentives
Class
Economics
Element
Prompt Caching
Definition
Scientific
Cache common prompt prefixes to reduce cost and latency.
Plain-English
Cache common prompt prefixes to reduce cost and latency.
Feynman
Don't pay twice for the same setup.
Core principle
Cache common prompt prefixes to reduce cost and latency.
One-sentence summary
Cost optimization in production deployments.
Mechanisms
Psychological
Cache common prompt prefixes to reduce cost and latency.
Behavioral econ.
Cost optimization in production deployments.
Neurological
Reward, threat, and salience circuits bias attention toward the cue.
Evolutionary
Heuristics that paid off in ancestral environments now misfire in modern systems.
Sociological
Group norms and status incentives reinforce the pattern across a team.
Computational
Models trained on biased human signals will replicate and amplify the pattern.
Systems thinking
Feedback loops between metrics, incentives, and behavior lock the pattern in place.
Signals & signature
Inputs (activators)
Common system prompts cached across calls.
Outputs (observable)
Cost optimization in production deployments.
Behavioral signature
You see Prompt Caching when the explanation for a decision sounds reasonable but the outcome keeps repeating.
Behavioral molecules
Often combines with related Atlas entries — see the rail below.
Pathways · before
A goal, metric, or contract clause makes the behavior rational locally.
Pathways · after
Locally rational choices accumulate into a systemic distortion.
Domains where it shows up
  • Business
  • Leadership
  • Government
  • Healthcare
  • Education
  • Sales
  • Marketing
  • AI
  • Negotiation
  • Media
  • Public Policy
  • Relationships
Examples
Everyday
Common system prompts cached across calls.
Modern
Cost optimization in production deployments.
Historical
A pattern repeatedly documented since the foundational behavioral science literature on ai alignment & incentives.
Famous experiments
See the References block — primary papers in the Atlas link out to the original studies.
Design principles
How to leverage
Cost optimization in production deployments.
How to reduce
Architect for cache reuse.
How to redesign
Architect for cache reuse.
The Perverse Incentive Lens™
How it's exploited
Organizations weaponize prompt caching — sometimes deliberately, often by accident — when metrics reward the symptom rather than the outcome.
Common perverse incentives
Volume metrics, short review windows, bonus cliffs, and contracts that pay on activity rather than impact.
Failure modes
When Prompt Caching dominates, teams optimize for the dashboard while the real outcome quietly degrades.
Incentive redesign
Architect for cache reuse.
Ethical considerations
Don't engineer prompt caching into customers, employees, or citizens as a manipulation tactic — design for informed choice instead.
Diagnostic questions
  • Where in our org would Prompt Caching most often show up unnoticed?
  • Which metric, ritual, or contract clause quietly rewards Prompt Caching?
  • If we removed every payoff for Prompt Caching, what behavior would replace it?
  • Who benefits when Prompt Caching persists — and who pays the cost?
Organizational warning signs
Metrics
A KPI is hit while the underlying outcome stalls or worsens.
Behaviors
People route around the rule rather than challenge it.
Language
'That's just how we do it here.' / 'The system requires it.'
Culture
Naming the pattern is treated as disloyalty.
Red flags
  • People defend the status quo using the language of prompt caching.
  • Decisions cluster around the easiest narrative rather than the strongest evidence.
  • New data changes the slide deck but not the decision.
  • Anyone naming the pattern is treated as the problem.
Intervention playbook
Immediate
Make the perverse payoff visible to the people creating it.
30-day
Run a small pilot that pays for the outcome, not the proxy.
Long-term
Rewrite the comp plan, contract, or ritual so the right behavior becomes the easy behavior.
AI considerations
Detect
Audit training data and reward signals for the same pattern this element describes.
Avoid amplifying
Don't optimize models on metrics that already encode the perverse incentive.
Counteract
Use the model to surface where the pattern is most active, then redesign the incentive — not the model.
Measurement
Metrics
Outcome-to-proxy ratio over time.
Assessment
The Incentives Lab III Diagnostic.
Survey
Calibrated pulse questions on rules vs. outcomes.
Behavioral signals
Where people work around the system.
Observational
Where the dashboard and the lived experience disagree.
Scientific evidence
Evidence grade
Synthesized from the behavioral science literature; see Atlas references.
Replication
Tracked in the Atlas as primary, replicated, or contested.
Intervention confidence
Moderate — patterns generalize, mechanisms vary by context.
Research consensus
Broad agreement on the pattern; ongoing debate on boundary conditions.
Known limitations
Local context, culture, and incentive structure all change the strength of the effect.
Open questions
How does Prompt Caching interact with AI-mediated decisions at scale?
References
Meta-analyses
Tracked in the Atlas registry.
Seminal authors
Kahneman, Tversky, Thaler, Ariely, Cialdini, Ostrom, Simon — and the field they built.
Cross references

Every Atlas entry is a node in a knowledge graph. See the related rail below to follow the connections.

Disciplinary layers

See Prompt Caching through 2 lenses

Each layer of the Incentives OS reframes this concept with its own thinkers, vocabulary, and diagnostic question.

Test yourself · 60 seconds

Do you actually know Prompt Caching?

Three quick questions. Result is saved into your review streak — come back when the term is due to lock it in.

Question 1 of 3Score: 0/3

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Go deeper

Worked example, counter-example & concept map

On-demand AI analysis grounded in the Lab's research. Cached on your device after first run.

How this lands in you

Your nervous system has a region for this.

Primary region
Prefrontal Cortex

When you encounter Prompt Caching, your prefrontal cortex has to do extra work to override the automatic response — and that override budget is finite.

Executive control, planning, impulse override, working memory, System 2. First thing to go offline under stress, fatigue, or low blood sugar. Why your 4pm decisions are worse than your 9am ones.

See Prefrontal in the Brain Atlas →
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