🌱 What you’ll build

You’ll create a simple AI-assisted check-in that helps you:

✔ Pause and notice your current energy
✔ Clarify what matters most today
✔ Shape a gentle plan that flexes with you

This isn’t about making a perfect plan. It’s about building a small tool that helps you start where you are — and helps AI learn what serves you best.

🌱 How to build your prompt

👉 Step 1: Frame your prompt as an invitation, not an order

Here’s a starter you can adapt:

Act as a supportive, flexible planning partner. Before suggesting anything, help me check in on my current energy, mood, and focus. Ask questions to clarify my real priorities and friction points today. Once we map that, gently suggest a flexible plan. Keep tone [choose: gentle, collaborative, focused].

👉 Step 2: Feed the system useful context

The more you share, the more helpful AI can be.
Before running your prompt, offer clues like:

• Here’s what tends to throw me off in plans: [name a few]
• Here’s what usually helps me get momentum again: [name a few]
• Today I’m feeling: [brief energy check]

This begins to shape the pattern AI will use to better support you.

👉 Step 3: Run the flow — and stay in dialogue

Answer the check-in questions.
Notice what comes up.
Ask AI to refine or adjust if something feels off.

Each time you do this, you’re not just planning your day — you’re teaching the system what actually helps.

🌱 How this small system can grow

Each time you check in this way, the system (and you) learn a little more about what supports you.
Over time, these small systems can evolve into something that feels like it was designed for you from the start — because it was.

🌱 Mini reflection — what helps you today?

After trying your flow:

• What part helped ease friction?
• What part felt off or heavy?
• What could you share next time to help AI support you better?

Write this down in your tracker.

🌱 What’s next

In the next lesson, you’ll test and adjust this flow — strengthening it so AI begins learning how to serve your rhythm more naturally.
This is how small systems become the foundation of deeper tools over time.