How to Automate your Tasks with AI
AI isn’t just for chat anymore, it can actually do work for you.
This post summarizes the “Out of the Box Developer” episode, that showed how to move from simple prompts to real automation pipelines, based on a practical walkthrough from Pedro.
Why AI Automation Matters for Developers #
As developers, we often ignore automation when it feels “too much work.”
Pedro explains this perfectly:
Pedro: We think, ‘I need to create a script for that.’ But sometimes it’s not easy, it takes time, and we end up not doing it.
That’s the gap AI fills.
Instead of building everything from scratch, AI helps you:
- Generate scripts
- Connect tools
- Handle repetitive work
- Focus on decisions, not execution
Step 1: Start Simple #
Most developers only use AI like Google search. That’s a missed opportunity.
Pedro: It’s important to understand that these tools can do a lot more than chat.
For example:
- Ask AI to research a topic → it gathers data from many sources
- Generate structured reports
- Summarize complex processes step-by-step
Step 2: Generate Small Tools Instantly #
AI can create working tools in seconds, no backend needed.
Pedro demonstrated generating a live unit converter:
Pedro: If I have a small problem, I can create a tool that runs right away.
Use cases:
- Unit converters (temperature, sizes)
- Personal calculators (tax, expenses)
- Quick dashboards
Step 3: Connect AI to Your Real Data #
This is where things get powerful.
AI can:
- Read your email
- Analyze purchases
- Generate reports
- Even run calculations with code
Pedro: It can go to my Gmail, get my purchases, and calculate values using JavaScript.
Step 4: Move From Prompts to Workflows #
The real upgrade is building repeatable workflows.
Pedro built a system that:
- Takes a YouTube video
- Extracts transcript
- Generates blog posts
- Creates images
- Publishes to WordPress
Pedro: I created a step-by-step process… I didn’t write it manually. I guided the AI to create the workflow.
This is the key idea:
- AI decides what to do
- Scripts handle how to do it
Step 5: Let AI Handle the “Thinking Work” #
Traditional automation struggles with decisions.
AI solves:
- What content is important
- Where to cut videos
- How to write posts
- What title to use
Example:
Pedro: It downloads subtitles, finds interesting topics, and creates cuts automatically.
Step 6: Automate Content Repurposing #
One of the most valuable use cases: reuse your content.
Turn:
- 1 video → 5 blog posts
- 1 podcast → 10 short clips
- 1 idea → multiple platforms
Pedro: You’re not creating content from nowhere, you’re repurposing your content.
Step 7: Improve Gradually (Not Perfectly) #
Your first version will not be great, and that’s fine.
Pedro: You never start perfect. You start with something that helps a little.
Even his system:
- Started with manual uploads
- Then added automation
- Then improved prompts
- Then added integrations
Step 8: Choose the Right Tools (Keep It Simple) #
You don’t need complex stacks.
Pedro chose Python because:
Pedro: It’s very easy to create a script that does one thing.
Key Mindset Shift: AI as Your Teammate #
This is the biggest takeaway:
Pedro: It’s a different way to write code now, the human is in the loop.
Instead of:
- Writing everything manually
You:
- Guide AI
- Review outputs
- Refine results
AI automation isn’t about replacing developers, it’s about removing repetitive work so you can focus on what matters.
Start small:
- Generate one tool
- Automate one task
- Build one workflow
Then grow from there.
Pedro: Get your hands dirty. If you don’t try, you’ll never know if it works for you.