Lesson 16: What Rung Are You On
Three ladders of AI leverage, nine rungs, and how to name the one you are actually on.
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Section 1: The Core Idea
The role is drifting. Coordinating and aligning still matter, but more of the job is now building. Before you claim AI leverage, name the leverage you actually have. There are three ladders, three rungs each. The rung logic is identical on every ladder: Rung 1: AI assists your work. Rung 2: you hand the task over and review the result. Rung 3: AI completes a multi step task and checks its own results. You always apply a final review. Each rung is roughly an order of magnitude more leverage than the one below it. As you ascend each ladder rung, you get an order of magnitude more leverage. On the first rung, you use AI for assistance in your own work.
Section 2: The personal ladder
Start here, because most readers recognise themselves on rung 1. Rung 1. AI writes text: PRDs, tickets, emails. You copy and paste between tools. Useful, and still the most common place to sit. Rung 2. AI produces the artefact itself: slides, a model, a small prototype. Expect heavy revision. Rung 3. The model is wired to your real tools over MCP and runs a task you would otherwise have delegated. For example: "check whether users of social share features have higher 30 day retention, and cite sources so I can validate." Connect your frequently used products once, ask for cited sources so the output is verifiable, then save the working flow as a skill so you stop rebuilding it. You'll likely find the results disappointing at first... Continue iterating with the model until you have a good result, then lock in the workflow by creating a skill.
Section 3: The product ladder
This ladder closes the gap between what you want and what you can ship. Rung 1. Web prototypes. Good for communicating an idea. The code is disposable and disconnected from the real product. Rung 2. Code based prototypes that use your actual codebase as context, so the output inherits real components and patterns. Ask an engineer for a runnable UI only repo with a local mock data store, no backend and no env vars. Rung 3. The agent opens a pull request that an engineer reviews and merges. Best for copy changes, small UI tweaks, and views over existing backend code.
Section 4: The judgement point
The right rung fits the task. The top rung is not always it. It does not make sense to spend your time being a worse engineer than the rest of your team. Knowing when to write a doc, when to prototype and when to open a pull request matters as much as the technical ability to do any of them. Not every task, workflow, or company demands that you move up to the highest rung to get the most out of AI. > KEY POINT: Claiming leverage is not the same as having it. Name the ladder and the rung for a real piece of work you did this week.
Section 5: Systems leverage is the rung that compounds
The third ladder is systems: repeatable skills, evals and connected pipelines that outsource work at a quality bar you trust. This is the answer to "the first drafts are not good enough yet". A good one off output disappears the moment you close the tab. A system turns that same output into work you can delegate, again and again. Source: Colin Matthews, "How top PMs increase their leverage with AI", guest post in Lenny's Newsletter (Jun 2026). **Apply It:** List your last five deliverables. For each one, write down the ladder it sits on and the rung you used. Which ladder: personal, product, or systems? Which rung: assist, hand over, or full task? Where would moving up one rung save the most time this month? Pick that one and do it this week. buildContent= );