Glossary¶
Comprehensive definitions of terms used in the Prompt Orchestration Governance (POG) framework.
Core Concepts¶
Prompt Orchestration Governance (POG)¶
A comprehensive framework for managing prompts as first-class software assets across the Software Development Life Cycle. POG provides systematic processes for discovering, normalizing, validating, versioning, and deploying prompts while maintaining governance and quality controls.
Prompt¶
A structured, versioned artifact that encodes intent, constraints, and context for model-driven execution. In POG, prompts are treated as first-class software assets that are discoverable, testable, and reusable across projects and teams.
First-Class Software Asset¶
A software artifact that receives the same level of rigor, management, and governance as source code. This includes version control, testing, documentation, review processes, and lifecycle management.
Prompt Types¶
Interaction Prompt¶
An ad-hoc, informal prompt used during exploration, chat interactions, or experimental work. These prompts are typically not governed and exist only in chat histories or personal notes.
Example: A one-off question asked in ChatGPT or Claude to solve an immediate problem.
Lifecycle Stage: Initial, ungoverned state.
Discovered Prompt¶
An interaction prompt that has been identified as valuable and worth capturing for reuse. Discovery happens when a prompt demonstrates effectiveness and potential value beyond its original context.
Example: A code review prompt that consistently produces high-quality feedback, identified during a retrospective.
Lifecycle Stage: Nominated for promotion to governed asset.
Normalized Prompt¶
A discovered prompt that has been transformed into a structured, parameterized, and generalized template. Normalization removes project-specific details and adds clear parameters.
Example:
Before: "Review this Python function for our auth service"
After: "Review the following {{LANGUAGE}} code for {{PURPOSE}}:\n{{CODE}}"
Lifecycle Stage: Structured but not yet validated.
Validated Prompt¶
A normalized prompt that has passed testing against evaluation cases. Validation ensures the prompt produces consistent, high-quality results across different inputs.
Example: A test case generator that has been validated against 20 different function types and consistently produces comprehensive test suites.
Lifecycle Stage: Quality-assured and ready for production.
Skill Prompt¶
A validated, production-ready, versioned, and governed prompt artifact. Skill prompts are the end goal of the POG lifecycle reusable assets managed as part of organizational knowledge.
Example: "Code Review Assistant v2.1" stored in the prompt repository with full metadata, versioning, and usage tracking.
Lifecycle Stage: Production-ready, governed asset.
POG Components¶
Prompt Warehouse Management¶
The first core function of POG. A systematic process to discover, normalize, validate, version, and store prompts as reusable assets. Acts as a "factory" that transforms interaction prompts into skill prompts.
Key Activities: - Discovery of valuable prompts - Normalization into templates - Validation against test cases - Version control and storage
SDLC Integration¶
The second core function of POG. Organization and deployment of phase-specific prompts to accelerate each stage of the Software Development Life Cycle.
Key Activities: - Organizing prompts by SDLC phase - Providing phase-appropriate prompts on demand - Collecting usage feedback - Continuous improvement
Prompt Repository¶
A centralized, versioned store of governed prompt artifacts. The repository serves as the single source of truth for all skill prompts in an organization.
Characteristics: - Version-controlled (typically Git-based) - Searchable and discoverable - Includes metadata (tags, usage stats, ratings) - Access-controlled with governance
Meta-Loop¶
The continuous improvement mechanism for the POG framework itself. The meta-loop collects usage data, feedback, and metrics to systematically improve the prompt library over time.
Process: 1. Teams use prompts from repository 2. Usage metrics and feedback collected 3. Performance evaluated 4. High-value prompts promoted 5. Low-value prompts deprecated 6. Gaps identified and filled
Lifecycle Stages¶
Discovery Phase¶
The process of identifying valuable interaction prompts worth capturing and formalizing. Discovery can be proactive (mining chat histories) or reactive (developers submitting prompts).
Activities: - Mining chat histories and logs - Developer submissions - Team retrospectives - Usage pattern analysis
Normalization Phase¶
Transformation of discovered prompts into structured, parameterized templates that can be reused across contexts. Removes project-specific details and adds clear parameters.
Activities: - Extract core intent - Identify parameters - Generalize constraints - Add metadata - Document usage
Validation Phase¶
Testing prompts against evaluation cases to ensure quality, consistency, and effectiveness. Validation prevents poor-quality prompts from entering the repository.
Activities: - Define test cases - Execute against multiple inputs - Measure quality metrics - Gather peer review - Approve or reject
Repository Management¶
Ongoing maintenance of the prompt repository including versioning, organization, search, access control, and deprecation.
Activities: - Version control - Metadata management - Search and discovery - Access permissions - Usage tracking - Deprecation of outdated prompts
SDLC Phases¶
Requirements Phase¶
The initial stage of software development focused on understanding and documenting what needs to be built.
POG Prompts: User story generation, acceptance criteria, stakeholder interview guides, requirements validation.
Design Phase¶
The stage focused on planning the architecture, interfaces, and data models for the system.
POG Prompts: Architecture pattern advice, API design, data model generation, design review.
Development Phase¶
The stage focused on writing, reviewing, and documenting code.
POG Prompts: Code generation, code review, documentation generation, refactoring suggestions.
Testing Phase¶
The stage focused on verifying the system works correctly and meets requirements.
POG Prompts: Test case generation, test data creation, bug analysis, coverage analysis.
Deployment Phase¶
The stage focused on releasing the system to production environments.
POG Prompts: Release notes generation, configuration validation, deployment planning, rollback procedures.
Maintenance Phase¶
The ongoing stage focused on monitoring, debugging, and improving the system in production.
POG Prompts: Incident analysis, performance optimization, technical debt assessment, documentation updates.
Orchestration Concepts¶
Orchestration Layers¶
A hierarchical organization of prompts by scope and abstraction level. Layers compose from bottom (foundation) to top (runtime context).
Layers (bottom to top): 1. Foundation Layer: Core capabilities and constraints 2. Domain Layer: Business rules and domain knowledge 3. Task Layer: Specific intents and actions 4. Runtime Context Layer: Dynamic user input and environment
Foundation Layer¶
The base layer containing core system capabilities, safety constraints, and organizational policies that apply universally across all prompts.
Examples: Rate limits, content policies, security constraints, base model capabilities.
Domain Layer¶
Business-specific rules, terminology, and patterns relevant to particular domains or industries.
Examples: Financial regulations, healthcare protocols, e-commerce patterns, legal terminology.
Task Layer¶
Specific intents and actions that accomplish particular development tasks.
Examples: "Generate unit tests", "Review API design", "Create user story", "Analyze security vulnerabilities".
Runtime Context Layer¶
Dynamic context including user input, project state, environment variables, and session information injected at execution time.
Examples: Current file content, user role, project language, git branch, environment (dev/staging/prod).
Governance Concepts¶
Control Plane¶
The governance mechanisms that manage prompt lifecycle including versioning, access control, audit trails, quality gates, and compliance.
Components: - Versioning system - Access control (RBAC) - Audit logging - Quality gates - Compliance checks
Version Control¶
Systematic tracking of changes to prompts over time. Each version has a unique identifier, change log, and maintains backward compatibility where possible.
Approaches: - Git-based (tags, branches) - Semantic versioning (v1.2.3) - Timestamp-based - Hash-based
Access Control¶
Role-based permissions determining who can create, modify, approve, or use prompts.
Common Roles: - Contributor: Can submit prompts - Reviewer: Can approve/reject prompts - Maintainer: Can manage repository - User: Can consume prompts - Admin: Full administrative access
Audit Trail¶
Complete history of prompt usage including who used which prompt, when, for what purpose, and with what results.
Tracked Information: - User identity - Timestamp - Prompt version - Input/output (sanitized) - Success/failure - Feedback
Quality Gate¶
A checkpoint in the prompt lifecycle requiring validation before progression. Quality gates ensure only tested, approved prompts reach production.
Types: - Syntax validation - Evaluation test passage - Peer review approval - Security scan - Compliance check
Evaluation & Testing¶
Evaluation Case¶
A test case for a prompt consisting of an input scenario and expected output characteristics. Used to validate prompt quality and consistency.
Components: - Input example - Expected output pattern - Quality criteria - Pass/fail threshold
Example:
Input: "Review this code: function add(a,b) { return a+b }"
Expected: Contains "no error handling", "missing type hints"
Quality: Identifies at least 2 code quality issues
Regression Test¶
A test ensuring a prompt continues to perform well after modifications. Prevents quality degradation during prompt evolution.
A/B Test¶
Controlled comparison of two prompt variations to determine which performs better. Used for prompt optimization.
Metrics: Success rate, quality score, user preference, latency, cost.
Usage Metrics¶
Quantitative data about prompt usage patterns including frequency, success rate, user ratings, and performance metrics.
Collected Data: - Usage count - Unique users - Success/failure rate - Average latency - Cost per execution - User satisfaction scores
Implementation Approaches¶
GitOps-Based¶
An implementation approach where prompts are stored as code in Git repositories with PR-based review workflows.
Characteristics: - Prompts as markdown/YAML files - Git for version control - Pull requests for review - CI/CD for validation - Branch-based workflows
Platform-Based¶
An implementation approach using dedicated prompt management platforms with UI-driven workflows.
Characteristics: - Web-based interface - Database-backed storage - Built-in search and analytics - Role-based access control - API for programmatic access
API-Driven¶
An implementation approach exposing RESTful APIs for programmatic prompt access and management.
Characteristics: - REST/GraphQL APIs - Programmatic access - Integration-friendly - Automation support - Headless architecture
Hybrid¶
A combination of approaches using multiple implementation strategies based on organizational needs.
Example: Git for version control + database for metadata + API for runtime access.
Related Methodologies¶
PDD (Prompt-Driven Development)¶
A development methodology where prompts are the primary drivers of the development process. Focuses on individual developer workflow and rapid iteration.
Relationship to POG: Complementary. PDD for development practices, POG for governance.
See: POG vs PDD
PDE (Prompt-Driven Engineering)¶
An engineering methodology treating prompts as first-class engineering artifacts requiring rigorous design, testing, and maintenance.
Relationship to POG: Complementary. PDE for engineering quality, POG for organizational management.
See: POG vs PDE
PromptOps¶
Operational practices for managing prompt deployment, monitoring, and maintenance in production environments.
Relationship to POG: POG provides the governance framework; PromptOps provides operational practices.
LLMOps¶
MLOps practices applied to Large Language Model lifecycle including model deployment, monitoring, and management.
Relationship to POG: POG focuses on prompts; LLMOps focuses on models. Both are complementary parts of AI operations.
Technical Terms¶
Parameterization¶
The process of identifying and extracting variable parts of a prompt into named parameters that can be filled at runtime.
Example:
Before: "Write Python tests for the authenticate function"
After: "Write {{LANGUAGE}} tests for the {{FUNCTION_NAME}} function"
Context Injection¶
The process of automatically inserting relevant information into a prompt at runtime based on current project state, user session, or environment.
Examples: - Current file content - Git branch name - Project dependencies - User preferences - Environment variables
Template¶
A reusable prompt structure with parameters that can be filled with specific values. Templates enable prompt reuse across different contexts.
Format Examples:
- Jinja2: {{ variable }}
- Handlebars: {{variable}}
- Mustache: {{variable}}
- Custom: $VARIABLE or {variable}
Metadata¶
Structured information about a prompt including tags, author, version, usage stats, ratings, and relationships.
Common Fields: - Name and description - Version and author - Created/modified dates - SDLC phase - Tags and categories - Usage statistics - Quality ratings - Related prompts
Semantic Search¶
Search capability that understands meaning and intent rather than just matching keywords. Enables finding relevant prompts even with different wording.
Technologies: Vector embeddings, similarity search, semantic indexing.
Metrics & Measurement¶
Adoption Rate¶
Percentage of developers or teams actively using prompts from the POG repository.
Calculation: (Active users / Total users) × 100
Reuse Rate¶
Frequency at which prompts are reused rather than created from scratch.
Calculation: (Prompts reused / Total prompt usage) × 100
Time-to-Value¶
Duration from prompt discovery to production deployment in the repository.
Target: Minimize while maintaining quality.
Coverage¶
Percentage of SDLC phases or development tasks that have available prompts.
Calculation: (Phases with prompts / Total phases) × 100
Quality Score¶
Aggregated measure of prompt effectiveness based on validation tests, user ratings, and success metrics.
Components: Test pass rate, user satisfaction, success rate, peer reviews.
ROI (Return on Investment)¶
Financial benefit gained from POG implementation compared to costs.
Calculation: (Time saved × Hourly rate - Operating costs) / Operating costs × 100
Organizational Terms¶
Prompt Champion¶
An enthusiastic advocate who promotes POG adoption, provides training, and supports users within a team or department.
Responsibilities: Evangelism, training, support, feedback collection.
Prompt Maintainer¶
Person or team responsible for managing the prompt repository, reviewing submissions, and ensuring quality standards.
Responsibilities: Repository management, review/approval, quality assurance, deprecation decisions.
Contributor¶
Any team member who creates and submits prompts to the repository.
Responsibilities: Create quality prompts, provide documentation, respond to feedback.
Governance Team¶
Group responsible for establishing policies, standards, and compliance requirements for prompt management.
Responsibilities: Policy setting, compliance monitoring, audit reviews, risk management.
Change Management¶
Pilot Team¶
A small group selected to test POG implementation before organization-wide rollout. Provides feedback and identifies issues.
Selection Criteria: Enthusiastic, representative of broader organization, willing to provide feedback.
Champions Network¶
A distributed group of prompt advocates across different teams who promote adoption and provide peer support.
Quick Win¶
An early, visible success that demonstrates POG value and builds momentum for broader adoption.
Examples: 50% time savings on common task, faster onboarding, improved code quality.
For complete framework documentation, see Main POG Documentation.