@BharukaShraddha: 90% of AI engineers are using these 4 concepts interchangeably. They're not. And that's exactly why so many AI agents b…

90% of AI engineers are using these 4 concepts interchangeably. They're not. And that's exactly why so many AI agents become slow, expensive, and impossible to debug. The 4 concepts: • Skills • Subagents • MCP • Hooks Each solves a completely different problem. Here's the simplest way to think about them: SKILLS = What the agent KNOWS Need reusable expertise? A coding standard. A file format. A workflow. Use a Skill. Load it only when needed. Not every task deserves permanent context. SUBAGENTS = Where the agent THINKS Need deep research? Parallel analysis? Messy exploration? Use a Subagent. Give the task its own workspace. Keep the main conversation clean. MCP = What the agent can REACH Need access to: • APIs • Databases • SaaS tools • Internal systems Use MCP. If the agent must interact with something outside itself, MCP is usually the answer. HOOKS = What the agent MUST OBEY Need: • Validation • Security checks • Formatting rules • Logging Use Hooks. Don't trust the model to remember. Enforce it. The mental model: Skills → Knowledge Subagents → Thinking MCP → Access Hooks → Rules Most people build AI systems like this: "Can MCP solve it?" The better question is: "Does this even need MCP?" Hot take: A huge percentage of MCP servers should have been Skills. People create integrations when all they needed was reusable knowledge. The result? More latency. More auth headaches. More maintenance. Better AI systems aren't built by adding more pieces. They're built by knowing which piece NOT to add. What's your rule for deciding between a Skill and an MCP?