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ARTICLE TITLE

A brief, neutral summary of what the topic is and why it matters.

Remembering (Knowledge / Recall)

🧠 At this level, list the definitions, core vocabulary, and factual components an expert would be able to name.

  • Core terminology & definitions
    • [EXTERNAL_LINK Term] – Short, precise definition.
    • [EXTERNAL_LINK Term] – What it refers to and its purpose.
    • [EXTERNAL_LINK Term] – Key acronym, protocol, object, role, etc.
  • Key components / actors / parts
    • [EXTERNAL_LINK Component] – What it is.
    • [EXTERNAL_LINK Component] – Where it belongs in the system.
  • Canonical tools & frameworks
    • [EXTERNAL_LINK Tool/Library/Standard]
  • Where this topic commonly appears
    • Industries, workflows, contexts, disciplines.
  • Typical recall-level facts
    • Year introduced, vendor, category, major versions, etc.

Understanding (Comprehension)

📖 Explain how the topic works conceptually and how it relates to similar concepts.

  • Conceptual relationships & contrasts
    • Topic vs. alternative – differences and trade-offs.
    • Topic within a broader ecosystem.
  • Core principles & paradigms
    • Guiding philosophy, architectural assumptions, learning model.
  • How it works
    • Inputs → processes → outputs (high level).
  • Roles & perspectives
    • Builder, user, operator, stakeholder.

Applying (Use / Application)

🛠️ Show how the topic is used in practice.

  • "Hello, World" or canonical examples
    • Minimal example of using the topic correctly.
  • Core task loops
    • Common workflows or usage patterns.
  • Frequently used commands / functions / actions
    • Short reference list.
  • Real-world use cases
    • Common jobs the topic solves.

Analyzing (Break Down / Analysis)

🔬 Break apart structure, diagnose issues, compare alternatives.

  • Comparative analysis
    • Topic vs. competing tools/approaches.
  • Failure modes & root causes
    • Typical mistakes, bottlenecks, misunderstandings.
  • Troubleshooting & observability techniques
    • Logs, metrics, debugging patterns.
  • Structural insights
    • Dependencies, boundaries, internal organization.

Creating (Synthesis / Create)

🏗️ Demonstrate expert-level design, composition, and optimization.

  • Design patterns & best practices
    • Proven approaches used by experts.
  • Security, governance, or ethical considerations
  • Lifecycle management strategies
    • Versioning, upgrades, migrations, refactors.
  • Scalability & optimization patterns

Evaluating (Judgment / Evaluation)

⚖️ Assess quality, effectiveness, readiness, and long-term fit.

  • Evaluation frameworks & tools
    • Ways to measure quality or success.
  • Maturity & adoption models
    • Indicators of ecosystem stability.
  • Key performance indicators
    • What should be measured and why.
  • Strategic decision criteria
    • When to choose this topic — or not.
  • Holistic impact analysis
    • Cost, risk, maintainability, learning curve.