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Concepts that are easy to mix up, explained side by side, with a straight answer on which to reach for and when.

• AI Agent vs Automation — automation runs steps a person wrote in advance.
• Agent vs Agentic AI — an AI agent is one specific point on a scale — full autonomy.
• Agent vs Assistant — "Assistant" describes who a product is for.
• Agent vs Chatbot — a chatbot replies to your message and waits.
• Agent vs Subagent — an agent and a subagent are the same kind of system.
• Agent vs Workflow — use a workflow when you can write out the exact steps in advance.
• MCP Tools vs Resources — an MCP tool is a real action the AI can take.
• MCP vs A2A — they're not competitors.
• MCP vs API — MCP doesn't replace an API.
• MCP vs Function Calling — they're not alternatives.
• Prompt vs Context Engineering — prompt engineering is wording one instruction well.
• RAG vs Fine-Tuning — fine-tuning changes how a model behaves.
• RAG vs Long Context — a bigger context window shrinks the case for RAG on small knowledge bases.
• RAG vs Memory — RAG retrieves from a general document collection to answer a question.
• Single Agent vs Multi-Agent — a single agent handles a task alone.
• Skill vs Agent — a skill has no decision-making of its own — it's instructions an agent chooses to load.
• Skill vs Subagent — a skill is instructions loaded into the same agent's context.
• Skill vs Tool — a skill is instructions that tell an agent how to approach a task.
• Tool Calling vs Function Calling — same underlying mechanism, two names.
• Vector Search vs Keyword Search — vector search matches by meaning, even with different wording.