If Your AI Keeps Ignoring Rules, Read This First

One of the biggest mistakes teams make with AI coding workflows is treating all context as the same thing.

The result? Rules get ignored, architecture becomes inconsistent, and generated code gets messier over time.

To get predictable, high-quality results, separate these five core primitives:

🧠 Agent (The Worker)

The execution engine that reads instructions, selects tools, and writes code.

🎯 Intent (The Goal)

The specific outcome you're trying to achieve. This answers the what and why of the task.

🗺️ Plan (The Roadmap)

The step-by-step approach created before any code is written. Good plans reduce rework and prevent AI from jumping to implementation too early.

🛠️ Skills (The Playbooks)

Reusable workflows and domain knowledge loaded only when needed. Instead of forcing the AI to remember everything, provide focused expertise when the task requires it.

🏛️ ADRs (The History)

Architecture Decision Records capture past trade-offs and decisions. They prevent teams from repeatedly debating or accidentally reversing established architecture choices.

The Golden Rule
Don't make your Agent guess your Intent.

Instead:

• Define the Intent clearly.
• Generate a Plan before execution.
• Convert recurring ADRs into reusable Skills.
• Let the Agent execute with the right context at the right time.

Teams that separate these concerns get more reliable outputs, cleaner code, and far fewer "why did the AI do that?" moments.

Which of these five is currently the weakest link in your team's workflow: Agent, Intent, Plan, Skills, or ADRs? 👇