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2 · Concept Model — 13 vendor-neutral concepts

CONCEPT 1: Standing Instruction

CONCEPT 4: Packaged Expertise

CONCEPT 5: Isolated Worker

CONCEPT 9: Composed Sequence

4 · Differences That Actually Matter

4.1 · Same word, different meaning — the dangerous seven

4.5 · Portability assessment — one tri-tool repo

7 · Applied Guidance

Decision tree — which primitive do I reach for?

7.1 · "I want to…" — 15 concrete intents

7.4 · Refresh procedure (keeping this reference current)

Quiz

PRIMITIVE 1 · CONTEXT LAYER: Standing instruction — "rules"

PRIMITIVE 4 · ACTION LAYER · THE 2026 CONVERGENCE POINT: Packaged expertise — "skills"

PRIMITIVE 5 · EXECUTION LAYER: Isolated worker — "subagents"

PRIMITIVE 9 · ORCHESTRATION LAYER: Composed sequence — "workflows"

Same word, different meaning

Survey

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Welcome to "Mastering Core Agent Primitives for Cross-Vendor AI Workflows," the definitive course designed to demystify the complex landscape of artificial intelligence agents. As AI tools proliferate, understanding the foundational building blocks—or "primitives"—is essential for building robust, scalable, and portable AI workflows.

Welcome to "Mastering Core Agent Primitives for Cross-Vendor AI Workflows," the definitive course designed to demystify the complex landscape of artificial intelligence agents. As AI tools proliferate, understanding the foundational building blocks—or "primitives"—is essential for building robust, scalable, and portable AI workflows. This course strips away vendor-specific jargon to focus on 13 vendor-neutral concepts that form the backbone of modern AI systems. You will dive deep into core primitives such as Standing Instructions, Packaged Expertise, Isolated Workers, and Composed Sequences. By understanding the difference between always-loaded facts and on-demand procedures, you will be equipped to design highly efficient AI architectures. Furthermore, we tackle the "dangerous seven"—commonly confused terminology across different AI vendors—ensuring you never get lost in translation between platforms. Beyond theory, this course offers highly practical applied guidance. You will learn how to use a strategic decision tree to select the right primitive based on cost, lifetime, and blast radius. We also cover 15 concrete intents for real-world scenarios and a crucial 15-minute refresh procedure to keep your knowledge current in a rapidly evolving industry. Whether you are an AI enthusiast, a developer, or a systems architect, this course will empower you to build cross-vendor compatible workspaces and future-proof your AI integrations.

Mastering Core Agent Primitives for Cross-Vendor AI Workflows

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            <p>Navigating the rapidly evolving landscape of artificial intelligence can be a daunting task, particularly when different platforms use conflicting terminology for similar functions. This course, "Mastering Core Agent Primitives for Cross-Vendor AI Workflows," is designed to provide a clear, foundational understanding of the essential building blocks—known as agent primitives—that power modern AI systems. By establishing a vendor-neutral conceptual model, learners will be equipped to understand how core elements like standing instructions, packaged expertise, isolated workers, and composed sequences operate across any platform. This standardized approach ensures that foundational knowledge remains applicable and easily transferable, regardless of which specific AI tool or provider is being utilized.</p>

<p>Throughout this comprehensive curriculum, the focus will extend beyond theoretical concepts to highly practical applications tailored for those just starting their journey in artificial intelligence. Participants will explore the critical differences in industry terminology, learning to identify the commonly confused terms that frequently cause misunderstandings across different vendors. Furthermore, the course provides structured, applied guidance through intuitive decision trees and concrete intent scenarios, enabling learners to confidently select the correct agent primitive for their specific tasks. By the conclusion of the material, which includes interactive knowledge checks and portability assessments, individuals will possess the clarity and strategic framework necessary to build, manage, and maintain effective AI workflows across multiple environments.</p>
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