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Vibe Coding · Lección

Automatización de tareas en varios pasos

Encadene pasos en un flujo de trabajo

Automatización de tareas en varios pasos es una lección gratuita de Vibe Coding en CoddyKit. Esta es la lección 3 de 4. Puedes leer la lección completa abajo gratuitamente — luego la practicas en el navegador con un editor de código integrado y un tutor de IA 24/7. Forma parte de la ruta de aprendizaje de Vibe Coding, y tu progreso se sincroniza en la web y la app de CoddyKit. El curso de Vibe Coding incluye 4 lecciones en total.

Partes de esta lección aún no han sido traducidas y se muestran en inglés.

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: 42

Describe 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.

Preguntas frecuentes

¿La lección «Automatización de tareas en varios pasos» es gratis?

Sí — el texto completo de «Automatización de tareas en varios pasos» es gratis para leer aquí en la web. Para practicarla de forma interactiva (editor de código integrado y tutor de IA 24/7) y desbloquear el resto del curso de Vibe Coding, actualiza a CoddyKit PRO. El curso de Vibe Coding incluye 4 lecciones en total.

¿Qué aprenderé en «Automatización de tareas en varios pasos»?

Encadene pasos en un flujo de trabajo Practicas Vibe Coding con código real que ejecutas directamente en el navegador, y un tutor de IA 24/7 responde tus preguntas mientras trabajas en la lección.

¿Necesito experiencia previa para empezar Vibe Coding?

No se requiere experiencia previa. Vibe Coding en CoddyKit está estructurado para principiantes hasta estudiantes avanzados, así que puedes empezar aquí o desde el inicio y avanzar a tu ritmo. Esta es la lección 3 de 4.

¿Cuánto tiempo toma la lección «Automatización de tareas en varios pasos»?

La mayoría de las lecciones de CoddyKit toman alrededor de 5–10 minutos. Cada una es compacta e interactiva, así que avanzas constantemente y retomas exactamente por donde dejaste en la web y la app.

¿Puedo escribir y ejecutar código en esta lección de Vibe Coding?

Sí. Cada lección de Vibe Coding incluye un editor de código integrado, así que escribes y ejecutas código real directamente en tu navegador y obtienes retroalimentación instantánea de IA — sin configuración local necesaria.

Todas las lecciones de este curso

  1. De asistente a agente
  2. Cómo proporcionar herramientas a un agente
  3. Automatización de tareas en varios pasos
  4. Cómo mantener seguros a los agentes
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