How I automated my YouTube channel using Flow Engineering with Gumloop
A no-code simple and intuitive platform to automate complex workflow
Imagine being able to build AI agents, automate your workflows and processes, all without having to write a single line of code.
Sounds amazing, right?
Let me introduce you to an incredible tool that can do just that. It’s called Gum Loop, formerly known as Agent Hub.
What is Gumloop?
Gum Loop is a no-code platform that allows you to create powerful AI automations with a simple drag-and-drop interface. Backed by Y Combinator, they’ve been revolutionizing the automation landscape since last year.
What’s really exciting about Gum Loop is that it’s like flowcharts on steroids. You break down complex tasks into smaller, manageable chunks, solve them step by step, and build the best solution iteratively. Welcome to the world of Flow Engineering.
Developers might already be familiar with frameworks like Lang Chain, Lang Graph, and Crew AI. But what about those of us who are not coders? That’s where Gum Loop shines.
If you’ve ever used Zapier, you’ll know it’s great for basic automation. But Gum Loop is the next level — more flexible and more capable.
What you can accomplish with Gumloop!
Let’s dive into how you can use Gumloop to accomplish complex workflows easily.
The platform’s documentation is straightforward, ensuring a smooth learning curve. Within just 10 minutes, I was up and running, building my first automation flow.
There are three key terms you need to know:
- Nodes: nodes are the building blocks of any task you want to automate.
- Flows: stringing several nodes together creates a flow.
- subflows: subflows help keep more complex tasks modular and manageable.
Now, how does Gum Loop work?
The standard format of a flow — from Gumloop docs
Most flows follow a general pattern — Ingest data, prepare it for the AI, process it with AI and output a result.
- Data Loaders: Pipelines normally start off with the ingestion of some sort of data. The data being ingested can be thousands of links in a csv, an uploaded file, a scraped website etc. This data is the content
- Data Modifiers: These nodes are the backbone of our flows. They are the helper functions that make everything possible. They allow us to perform any number of data manipulation tasks like reformatting text, reading values from jsons, extracting columns from csv etc.
- Using AI: Nodes that use AI generally follow. These nodes are the source of reasoning in the flow and can ingest the loaded data and summarize, answer questions, categorize etc.
- Data Writers: These are almost always the very last step of our flows. They touch the outside world and turn the AI processed output into a tangible, valuable result. Nodes that generate files, raise GitHub PRs, post Tweets and more live in this category.
How I automated my YouTube channel
So, you’ve got an idea for a YouTube video. The first step?
- Research.
Say goodbye to hours of manually searching for relevant videos. With the power of AI, this can be done in minutes. Let me show you how.
Step 1: Collect Relevant YouTube Data
First, we need to lay the groundwork. We’ll start by collecting data on videos already out there on the topic we’re interested in. Using a tool like Gum Loop, you input your topic — let’s say “Langchain” — generate a formatted URL with the keyword, and let YouTube’s API do the rest.
The API response will provide you with a list of video titles, descriptions, publish dates, and URLs which are neatly stored in a Google Sheet for easy access. Believe me, this is just the beginning.
Step 2: Download Transcripts for In-Depth Analysis
Now, having URLs is good, but **text transcripts**? Even better. This is where it gets interesting. We read each YouTube video URL, download its transcript, and then collate all these transcripts into a single, long text. This single text is gold — it’s ripe for analysis by our AI.
Step 3: Generate Video Ideas and Outline with AI
With the transcript text ready, we unleash the AI. We prompt it to generate **video ideas** based on existing content. The AI will then help outline the structure of your video, saving countless hours of brainstorming and planning.
Imagine skipping the whole dilemma of coming up with a script! Your AI assistant drafts the plan, ensuring your video is structured, informative, and engaging.
Step 4: Generate a Catchy Thumbnail
What’s a great video without an eye-catching thumbnail? Using the previous script and outline, we prompt another AI model to generate a high-quality image for your video’s thumbnail. This image speaks directly to your audience, making your content irresistible to click on.
Step 5: Put It All Together Seamlessly
With Gum Loop, these steps become subflows of a larger YouTube automation workflow. Once you hit run, your chosen topic goes through data collection, transcript downloading, AI processing, and thumbnail generation, all seamlessly integrated.
How you should start — with templates
You don’t need to start from scratch. Gum Loop provides ready-to-use templates for countless workflows — from lead research to web scraping to software development.
The best part? It’s intuitive and user-friendly. Error messages are clear, and the platform guides you at every step, ensuring a smooth process.
And it doesn’t stop there. Gum Loop is continuously evolving. New integrations are just an email away, tailor-made for your specific needs.
So why wait? Dive into Gum Loop today and supercharge your workflows without writing a single line of code.
