六步拆解公式＋3 个实操提示词＋5 套模板——把一句话的模糊流程，15 分钟拆成能跑的 SOP。
鸿鸿蒙全
18年IT全栈 曾任某500强企业IT架构师 FDE布道师
The workflow in your head is always fuzzy: "A customer reports a fault in the group chat, we send someone to look at it, they write up a plan, the customer confirms and we fix it." It sounds clear, but the moment you try to make it runnable you find holes everywhere — who triggers it and when, where each step's conclusion is stored, what happens when two people confirm at the same time. This lesson walks one complete path: use a six-step formula to break a one-sentence fuzzy workflow into a runnable SOP.
| 1 six-step formula | 3 hands-on prompts | 5 templates | 1 SOP of your own workflow |
|---|---|---|---|
| Trigger → states → step table → data flow → boundary questions → automation levels | Break down / find gaps / assign roles | A full timeline from entry to review | A process document validated on a real case |
The three deliverables: live hands-on practice + template files (prompt pack) + homework.
The problem is not that you cannot draw a flowchart. It is that the trigger, the states, the data flow, the decision branches and the automation boundary were never written down item by item — and all of it was already in your head.
Four core concepts in plain language — state machine (what this object counts as right now), data flow (what is read, written and stored where), routing rules (which branch it should take), automation boundary (what AI can take over); a table of six common scenarios; then the heart of the lesson, unrolled step by step: trigger → states → step table → data flow → boundary questions → automation levels, each with its output.
Using a customer repair ticket as the main case, you run three prompts live — Prompt A for the first pass (state machine + step table + data flow), Prompt B for a QA review across six classes of boundary gaps, Prompt C to label every step fully automated / semi-automated / manual and rank what to automate first. Each prompt comes with its full text and the one thing to watch for.
Five copy-ready templates ordered by when you use them (capturing a new process / one sentence into a state machine / probing boundaries / automation assignment table / post-launch review); two blank tables you can use immediately (one-page workflow breakdown, state transition log); plus three general red lines and two specific to this lesson.
This course has 3 lessons and 1 assignment: from understanding the four concepts and the six-step formula, to running a real process through three prompts, to moving it into your own role with the templates.
State machine, data flow, routing rules and automation boundary explained in plain language, each with a concrete example; a look at how AI helps across six common scenarios; then a step-by-step unrolling of the six-step formula — what each step does and what it produces; plus the general prompt formula (role + task + context + format + constraints) and the single most valuable advanced tip.
Around the main case — a customer repair ticket process — starting from one spoken sentence: Prompt A yields the state machine, step table and data flow; Prompt B has AI act as a QA engineer and surface six classes of gaps (concurrent edits, abnormal interruption, timeout, missing values, state rollback, permission isolation); Prompt C labels each step with its automation level and ranks the changes.
Five copy-ready templates along the timeline of "capture a new process → structure it → complete the boundaries → assign automation → review after launch", each marked with when to use it; two blank tables you can fill in by hand; and finally the red lines, especially the two specific to this lesson.
In one sentence: AI produces the first draft and hunts for gaps; you judge and decide. The process in your head is always incomplete — the greatest value of AI is not "execution", it is "questioning".
Five red lines:
