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Lift 1: Gear Check — The Delegator's Toolkit

Why a Gear Check?

Before you hit the slopes, you check your gear. You make sure your bindings are tight, your beacon has batteries, and your pack has everything you need. You might already know most of it — but you check anyway, because starting on the same page matters more than starting fast.

That's what this lift is. We're doing a quick recap of the foundational concepts from the Green Circle track — how AI behaves, how to communicate with it clearly, how to write prompts that produce reliable results, and how to give AI persistent project knowledge. Some of this will be familiar. Some of it might be new. Either way, this gear check ensures your whole team is starting from the same baseline.

Here's why this matters more than it used to: the bottleneck has shifted. AI can write the code — the hard part is getting clear about what you want built and how it should work. That means anyone who can define what needs to be built can ship it — designers, PMs, engineers, managers. We've seen designers go from producing Figma mockups to building testable prototypes in days, work that previously took weeks and required an engineer. Every concept in this lift — the Three Pillars, delegation contracts, standing instructions — exists to make your intent precise enough that AI can act on it reliably.

If some of this is new to you — that's completely fine. You're in the right place, and your teammates are your best resource. Lean on each other. The goal isn't to have all the answers walking in — it's to have them walking out.

If you already know this stuff — great. Use this as a chance to sharpen your mental models and help your teammates get up to speed. Teaching a concept is one of the fastest ways to deepen your own understanding of it.

By the end of this gear check, you'll have the shared vocabulary and toolkit your team needs to start delegating real work to AI — together.

What You'll Learn

  • How AI processes your requests — and the three behaviors that explain most of its surprises
  • A framework for making requests that consistently produce what you need
  • How to write delegation contracts (user stories with acceptance criteria) that define "done" before you start
  • How to give AI standing instructions so it knows your project without being told every time

Sections

  1. How AI Thinks — The three behaviors that explain most AI surprises
  2. Making Clear Requests — A framework for specific, effective prompts
  3. Stories as Delegation Contracts — User stories and acceptance criteria as your delegation format
  4. Standing Instructions — Project context files that make AI remember

By the End of This Lift

  • You can explain why the same prompt produces different results — and why that's fine
  • You can write a prompt using the Three Pillars (Scope, Intent, Structure)
  • You can write a user story with acceptance criteria that defines "done" for AI
  • You understand how project context files solve the "re-explaining every time" problem
  • You're ready to start Run 1 with a clear delegation strategy