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The Lazy AI Automation That Accidentally Became a $1,000 Week

From JOHNWICK

Photo by Steve Johnson on Unsplash

1. It Started Because I Was Tired I wasn’t trying to launch a business.
I was just exhausted from rewriting endless blog intros and social media captions for freelance clients. One night, half annoyed and half curious, I thought: “Why am I doing this manually when AI could do it better and faster?” So I built a simple prompt to rewrite content in a viral, attention-grabbing style.
Two days later, that tiny idea turned into an automation that made over $1,000 in the first week.


2. The Prompt That Changed Everything This is the structure that became the heart of the system:

You are an expert content creator who writes engaging openings for social media posts.

Rewrite the text below to: - Capture attention in the first 10 words - Keep the tone human, friendly, and lightly playful - End with a question that encourages replies

Text: Template:User input

I tested it on a few examples.
The results were better than expected — and clients immediately noticed. They kept asking: “What are you doing differently?” That’s when it hit me:
This wasn’t just a productivity trick.
This was a product.


3. Turning a Prompt Into a Service I built the first version without writing a single line of code:

  • ChatGPT API to generate rewritten content
  • Google Sheets to organize client submissions
  • Zapier to automate everything

The workflow:

  • Client submits text through a Google Form
  • Zapier sends the content to the OpenAI API
  • The rewritten version is delivered automatically by email or Google Sheet entry

It was simple — but it worked flawlessly.


4. If You Prefer Code Here’s the lightweight Python setup using Flask: 

from flask import Flask, request, jsonify
import openai

app = Flask(__name__)
openai.api_key = "YOUR_API_KEY"

@app.route('/rewrite', methods=['POST'])
def rewrite():
    text = request.json.get("text")
    prompt = f"You are a content expert. Rewrite engagingly:\n{text}"

    response = openai.ChatCompletion.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": prompt}]
    )
    return jsonify({"rewritten": response.choices[0].message.content})

app.run(port=5000)

Host it on Render or Vercel, and you have an instantly usable rewriting API.


5. Full Automation = Zero Manual Work To avoid sending results manually, I connected the API to Zapier Webhooks so that every submission:

  • Sent text to the rewrite endpoint
  • Received the rewritten result
  • Automatically emailed it to the client

No waiting. No human involvement.


6. Monetization in 30 Minutes For payments, I used Gumroad and sold rewrite credits:

  • 10 rewrites for $9

When someone purchased:

  • Credits were added to their account
  • Each rewrite deducted one credit
  • At zero, an automated upsell email triggered

Sales started while I was asleep.


7. Optional Frontend (But Worth It) To make it feel like a “real tool,” I built a Streamlit interface: 

import streamlit as st
import requests

st.title("AI Social Caption Rewriter ✨")
text = st.text_area("Paste your post:")
if st.button("Rewrite"):
    r = requests.post("https://yourapi.com/rewrite", json={"text": text})
    st.write(r.json()["rewritten"])

Clients loved it — and started sharing it. Growth became organic.


8. The Real Differentiator: Personalization Everyone could access ChatGPT.
The reason they paid me was the ability to match their brand voice. I improved the system using few-shot examples:

Here are three examples written in this brand’s voice: 1. {ex1} 2. {ex2} 3. {ex3}

Rewrite the text below in the exact same tone: {text}

Outputs became hyper-personal and hard to replicate.
Clients happily paid recurring fees.


9. Scaling With an API Eventually, I packaged everything into a FastAPI endpoint and sold access to developers: 

from fastapi import FastAPI
from pydantic import BaseModel
import openai

app = FastAPI()

class Request(BaseModel):
    text: str

@app.post("/rewrite")
def rewrite(data: Request):
    response = openai.ChatCompletion.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": f"Rewrite: {data.text}"}]
    )
    return {"rewritten": response.choices[0].message.content}

People built Chrome extensions, automation tools, and internal workflows on top of it.


10. Smart Analytics Made It Better Using Supabase + Chart.js, I tracked:

  • Number of rewrites per user
  • Tone preference trends
  • Best-performing prompt variations

This helped increase quality — and retention skyrocketed.


11. The Automation Flywheel Everything connected: Input → Processing → Delivery → Payment → Tracking → Email Retention
All running automatically, with weekly prompt improvements.


12. The Lesson From one simple prompt, I built:

  • A micro-SaaS tool
  • A resellable API
  • A done-for-you rewriting service

All starting from pure laziness — finished in one weekend.

Read the full article here: https://ai.plainenglish.io/the-lazy-ai-automation-that-accidentally-became-a-1-000-week-d97352c92b0e

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