多步骤任务自动化
将多个步骤串联成工作流
多步骤任务自动化 是 CoddyKit 上的免费 Vibe Coding 课时。 这是第 3 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Vibe Coding 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Vibe Coding 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
Chaining Steps Into a Workflow
One tool call is handy. The magic of agents is chaining many steps into a single flow that runs on its own.
"Fetch the data, clean it, save it, and email me a summary" is four steps — but to you it's one request. The agent walks the chain, passing the result of each step into the next.
This lesson is about thinking in workflows, not single commands.
What Is an Automation
An automation is a workflow that runs without you babysitting each step. You define it once; it repeats reliably.
Examples a beginner can build with AI:
- Every morning, fetch news headlines and post a summary
- When a form is submitted, save it and send a thank-you email
- Resize and rename every image in a folder
The agent strings the steps together; you just describe the end-to-end flow.
Steps Pass Results Forward
The key idea: each step feeds the next. Step 1's output becomes step 2's input.
Here's a tiny chain in JavaScript — fetch a number, double it, then label it. Each line uses the previous result:
function step1() { return 21; } // get data
function step2(n) { return n * 2; } // transform it
function step3(n) { return "Result: " + n; } // format it
const a = step1();
const b = step2(a);
const c = step3(b);
console.log(c); // Result: 42Describe the Whole Flow
To get a good automation, write the steps in order, like a recipe. The clearer the chain, the better the agent builds it.
Notice how this prompt lists each step and what connects them:
Workflow prompt (Claude Code):
"Build a script that does this in order:
1. Read all .txt files in the ./notes folder
2. Combine them into one document
3. Ask the AI to summarize that document in 5 bullets
4. Save the summary to summary.md
Test it on the sample files and show me the output."Handling 'What If a Step Fails?'
Real workflows hit snags: a file is missing, an API is down, the internet drops. A good automation handles failures instead of crashing silently.
When you ask an agent to build a flow, tell it what to do on errors: retry, skip, or stop and warn you. This one sentence saves you hours of mystery bugs.
Add this to any workflow prompt:
"If any step fails, don't crash silently — print a clear message
saying which step failed and why, then stop. For the API call,
retry up to 3 times before giving up."Loops: Repeat Over Many Items
Lots of automations do the same step to many items: every file, every user, every row. That's a loop.
Here a loop greets a whole list — the agent writes patterns like this when you say "do X for each":
const users = ["Ada", "Linus", "Grace"];
for (const name of users) {
console.log("Sending welcome email to " + name);
}
console.log("Done — " + users.length + " emails sent.");Letting the Agent Run the Whole Chain
With an agentic tool, you don't just generate the script — you let the agent run it, watch the output, and fix what breaks, all in one go.
It might fetch real data, see an empty result, realize the URL was wrong, fix it, and re-run. That self-correcting loop is what makes agents feel like automation, not just code generation.
Scheduling: Run It on a Timer
Many automations should run on a schedule — every hour, every morning, every Monday. That's where automations earn their keep while you sleep.
Beginner-friendly options: a cron job, a tool like Zapier or Make, or a scheduled function on Vercel. Ask AI to set the timer for you.
Prompt to add a schedule:
"Set up this script to run automatically every day at 8am.
I'm deploying on Vercel — use a Vercel Cron Job. Show me the
config file and explain where it goes."Connecting Real Services
The most useful automations connect the apps you already use: Gmail, Slack, Notion, Google Sheets, a database.
Two paths: (1) no-code tools like Zapier/Make drag steps together, or (2) ask an agent to write code that calls each service's API. For your first automations, no-code is fast; code gives you full control later.
Test on Small, Then Scale Up
Before unleashing an automation on 10,000 rows or your real inbox, test on a tiny sample. One file. One fake email. A dry run that prints what it would do instead of doing it.
Automations repeat fast — including mistakes. Catching a bug on 3 items is cheap; catching it after it emailed your whole list is not.
Safe-testing prompt:
"First run this in 'dry run' mode: print what each step would do
without actually sending emails or deleting files. Let me confirm
the output looks right, THEN add a flag to run it for real."Think in Flows, Not Commands
The shift this lesson asks for: stop thinking "what command do I run?" and start thinking "what's the flow from start to finish?"
List the steps, name what passes between them, decide what happens on failure, and choose when it runs. Hand that to an agent and you've automated real work — the indie builder's superpower.
Quick Check
Let's lock in the safest way to launch a new automation.
Recap: Workflows That Run Themselves
You now think in automations:
- An automation chains steps; each step's output feeds the next.
- Describe the whole flow in order, like a recipe.
- Say what happens on failure (retry / skip / stop).
- Use loops to repeat over many items, and schedules to run on a timer.
- Always test small or dry-run before going live.
Next, the crucial finale: keeping these powerful agents safe.
常见问题解答
「多步骤任务自动化」课时是免费的吗？
是的 — 「多步骤任务自动化」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Vibe Coding 课程的其余内容，请升级到 CoddyKit PRO。 Vibe Coding 课程共包含 4 节课。
「多步骤任务自动化」这节课中我会学到什么？
将多个步骤串联成工作流 你通过在浏览器中直接运行的动手代码来练习 Vibe Coding，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 Vibe Coding 需要有经验吗？
无需任何先前经验。CoddyKit 上的 Vibe Coding 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 3 节课，共 4 节。
「多步骤任务自动化」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 Vibe Coding 课中编写并运行代码吗？
能。每节 Vibe Coding 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。