A reference from Weave

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Understand the metrics, models, and methods behind modern engineering. Clear definitions, practical examples, and a closer look at what the numbers actually mean.

Terms beginning with E

99 terms

  • Early stopping

    Early stopping is a language-model concept about training behavior and measurement. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Early stopping generation

    Early stopping generation is a language-model concept about generation behavior and sampling. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Ecological fallacy

    Ecological fallacy is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation

  • Edge-case set

    Edge-case set is a defined lens for examining AI system behavior with a stated task, evidence, and interpretation rule.

    Evaluations and benchmarks

  • Effect size

    Effect size is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation

  • Effective AI rate

    Effective AI rate is the realized cost per unit after discounts, caching, and routing adjustments. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.

    Token costs and AI ROI

  • Effective capacity

    Effective capacity is a concept used in software delivery planning to describe a condition, relationship, estimate, or decision about engineering work.

    Flow and capacity planning

  • Effectiveness measure

    Effectiveness measure is a developer productivity concept that helps teams understand effectiveness measure in the context of software delivery.

    Developer productivity

  • Efferent coupling

    The number of dependencies that a component sends outward to other components.

    Code quality and technical debt

  • Efficiency versus effectiveness

    Efficiency versus effectiveness is a developer productivity concept that helps teams understand efficiency versus effectiveness in the context of software delivery.

    Developer productivity

  • Elo rating

    Elo rating is a defined lens for examining AI system behavior with a stated task, evidence, and interpretation rule.

    Evaluations and benchmarks

  • Embedding pooling

    Embedding pooling is a language-model concept about instruction design and control. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Embedding space

    Embedding space is a language-model concept about instruction design and control. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Embeddings

    An embedding is a numeric representation of content produced by a model so that items with related properties can be compared in a vector space. Embeddings are commonly used for semantic search, retrieval, clustering, and recommendation.

    LLM fundamentals

  • Emergency change

    Emergency change is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps

  • Emergency change rate

    Emergency change rate is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.

    DORA and DevOps

  • Enablement

    Enablement is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Enablement work

    Enablement work is a developer productivity concept that helps teams understand enablement work in the context of software delivery.

    Developer productivity

  • Enabling team

    Enabling team is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Encoder-decoder model

    Encoder-decoder model is a language-model concept about mechanism and information flow. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • End to end inference latency

    End to end inference latency is the serving concept concerned with end to end inference latency during AI inference.

    Inference performance

  • Endpoint discovery

    Endpoint discovery is a model-routing or gateway concept used to manage operational visibility for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.

    Model routing and gateways

  • Endpoint health

    Endpoint health is a model-routing or gateway concept used to manage reliable request governance for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.

    Model routing and gateways

  • Endpoint monitoring

    Endpoint monitoring is measurement of availability, latency, correctness, and errors for a particular API endpoint.

    Reliability and observability

  • Endpoint registry

    Endpoint registry is a model-routing or gateway concept used to manage operational visibility for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.

    Model routing and gateways

  • Engineering analytics

    Engineering analytics is the practice of using data about software development to understand how work moves, what teams deliver, and where quality or process problems arise. It combines measurements with the context needed to make engineering decisions.

    Engineering analytics

  • Engineering benchmark

    Engineering benchmark is an analytical concept for using reference values to understand engineering performance, variation, or capability.

    Engineering analytics

  • Engineering change classification

    Engineering change classification is the practice of assigning software changes to defined work categories such as feature, defect, maintenance, incident recovery, security, or enablement. It helps teams interpret flow, quality, capacity, and outcomes in the context of why the change was made.

    Engineering analytics

  • Engineering effectiveness

    Engineering effectiveness is the degree to which an engineering team turns time and resources into valuable, reliable outcomes. It considers delivery, quality, collaboration, and developer experience together rather than treating activity as the result.

    Developer productivity

  • Engineering handbook

    Engineering handbook is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Engineering metrics

    Engineering metrics are defined measurements used to understand software delivery, quality, reliability, and developer experience. A useful metric has a clear question, a stable definition, and enough context to support a decision.

    Engineering analytics

  • Engineering output

    Engineering output is a developer productivity concept that helps teams understand engineering output in the context of software delivery.

    Developer productivity

  • Engineering performance

    Engineering performance is a developer productivity concept that helps teams understand engineering performance in the context of software delivery.

    Developer productivity

  • Engineering planning

    Engineering planning is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Engineering work mix

    Engineering work mix is the distribution of engineering effort or completed work across categories such as features, maintenance, defects, incidents, security, and enablement. It makes competing demands on a software factory visible so capacity and delivery results can be interpreted together.

    Developer productivity

  • Engineering-product manager partnership

    Engineering-product manager partnership is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Ensemble programming

    Ensemble programming is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Environment configuration drift

    Environment configuration drift is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps

  • Environment equivalence

    Environment equivalence is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps

  • Environment parity

    Environment parity is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.

    DORA and DevOps

  • Environment promotion

    Environment promotion is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps

  • EOS token

    EOS token is a language-model concept about context selection and limits. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Ephemeral environment

    Ephemeral environment is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps

  • Epoch

    Epoch is a language-model concept about mechanism and information flow. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Equivalence partitioning

    Equivalence partitioning is a software testing or test-design practice used to gather evidence about a defined risk, behavior, boundary, or operating condition. It makes the question under test explicit, identifies the inputs and observations that matter, and gives a team a repeatable basis for deciding whether the result is acceptable.

    Code quality and technical debt

  • Error budget

    An error budget is the amount of unreliability permitted by a service level objective over its measurement window. If the objective is 99.9% availability, the budget is the remaining 0.1% of allowed unavailability under the defined measurement rules.

    Reliability and observability

  • Error budget alert

    Error budget alert is notification when the allowance for unsuccessful or slow service events reaches a threshold.

    Reliability and observability

  • Error budget burn rate

    Error budget burn rate is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.

    DORA and DevOps

  • Error budget consumption

    Error budget consumption is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.

    DORA and DevOps

  • Error budget exhaustion

    Error budget exhaustion is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.

    Reliability and observability