TutorialsFrom Writing an AI SOP to Building Your Own Workbench
A six-element AI SOP formula, 3 hands-on scenarios and a five-step workbench method — write your experience into an SOP, verify it with real work, then let repeated workflows live in a workbench.
Before, every time you asked AI to write a daily report, run a retrospective or break down a post, you had to re-explain the requirements; and your plans and reviews were scattered across different places. This course walks one complete path: write down how you actually work as an SOP, then connect goals, projects, actions and reviews into a workbench.
What you take home
| 1 SOP card | 3 scenario prompts | 1 workbench blueprint | 3 deliverables |
|---|---|---|---|
| Six elements, fill in and use | Daily report / retrospective / post breakdown | The full loop from goal to feedback | A template pack + something you built + a workflow of your own |
Every session delivers three things: hands-on practice, notes and a workbench prototype, and homework.
What you have probably run into
- You give AI the same kind of task three times and get three different formats, plus progress you never supplied;
- The daily report AI writes looks complete but cannot be handed to your manager;
- A new set of materials means explaining everything from scratch again;
- Plans and reviews sit in different places, so every morning you re-decide what matters.
The problem is not that AI is not smart enough — it is that you never stated the goal, the inputs, the decision rules or the completion criteria, and those live only in your head.
What you will learn
What it is + why: an SOP for AI
Write down the goal, inputs, steps, decision rules, output format and checking method for a repeated task so AI can run it again and again while a human can verify the result. The six-element formula — role + goal and boundaries + input spec + steps + decision constraints + output and acceptance — broken down element by element with a daily-report example, plus the four common problems and what each one means the SOP must fill in.
How to use it: three hands-on scenarios
Daily report (from scattered notes to a fixed briefing), project retrospective (from experience to next-round actions), and social post breakdown (from observation to an original test) — the full prompts for all three, each with the specific error to hunt for and the rule to add.
Workbench: from SOP to a daily workflow
Why a finished SOP still needs a workbench; the six-stage loop (OKR → Gantt → action list → today's three things → review → feedback into actions) with its key fields; the five-step build method; the copy-paste workbench prompt; and the cross-role reuse formula with a four-role comparison table.
Who this is for
Course structure
This course has 3 lessons and 1 assignment, moving from understanding the concept to running three scenarios to building your own workbench.
What it is + why: an SOP for AI
Start from the problem worth solving; clarify the concept by comparing three levels (one-off question / AI SOP / workbench); break down the six-element formula (role, goal and boundaries, input spec, steps, decision constraints, output and acceptance) with a daily-report example for each; map four common problems to what the SOP must fill in; and land the most important line — a good SOP is never finished in one pass.
How to use it: three hands-on scenarios
Full prompts and observation points for all three scenarios: A daily report, B project retrospective, C social post breakdown. Each gives demo material, steps, rules and output format, plus the v1 to v2 method of catching one specific error, adding one rule, and verifying with a second set of materials.
Workbench: from SOP to a daily workflow
Why a finished SOP still needs a workbench (the SOP for one task is not the priority for one day); the six-stage loop and its key fields; the five-step build method; the copy-paste workbench prompt (flow and field tables first, generate the prototype only after confirmation); the cross-role reuse formula and a four-role comparison table.
Course materials
This course comes with two downloadable files:
- Lecture notes (HTML): all eight sections in their original form, including the six-element formula, three scenario prompts, the workbench build prompt, blank templates and quality red lines. Open it directly in a browser.
- AI education PM workbench (HTML prototype): the finished workbench the instructor actually built, with OKR, Gantt, action list, today's three things, review and archive modules running on local storage. Try the full loop in your browser.
Direct downloads:
- AI-SOP与产品经理工作台-讲义.html (lecture notes)
- AI教育产品经理工作台-原型.html (workbench prototype)
Core principle
In one sentence: what you take home today is not a universal prompt but a method — write your experience into an SOP, verify it with real work, then put repeated workflows into a workbench.
Plus three red lines from the lesson:
- Take facts, numbers, dates and names back to the source material; desensitize or get permission for demo materials;
- AI output is a draft — publication and scheduling commitments are confirmed by a human;
- You can learn the method from someone else's content, but never copy their wording or experience.
Get one thing running first, and the workbench will truly belong to you.
Assignment: Find where you waste the most tokens, then fix it
Answer one question — where do you currently waste the most tokens — then install a tool from the course and fix it, with a screenshot.
What It Is + Why: An SOP for AI
Write down the goal, inputs, steps, decision rules, output format and checking method for a repeated task — the six-element formula, taught through a daily-report example.