I'm constantly experimenting with new ways to enhance how I share content. This weekend, I decided to play around with Googleās NotebookLM, and the results were pretty good.
It led me to launch "Code Quests", an AI-generated podcast based on my DEV.to articles, now available on Spotify! šļø
But how did this come about, and why use AI to turn written articles into podcast episodes? Letās dive in.
Why a Podcast?
Writing technical articles is a great way to share knowledge, but audio allows people to consume content on the go, whether theyāre commuting, exercising, or simply prefer listening over reading.
However, as much as I love the idea of podcasting, recording and editing episodes manually can be time-consuming. Thatās where AI came in. I thought, "What if I could use AI to automate this process?" And thatās when I stumbled upon Google's NotebookLM.
What is Googleās NotebookLM?
NotebookLM acts as a virtual assistant designed to analyze and summarize information. By leveraging the Gemini 1.5 Pro model, it can digest large volumes of content and then generate conversational insights.
In my case, I simply input my DEV.to articles, and it generates a conversation between two AI voices. These voices highlight the key points of my written content and package them into a podcast-friendly format. š¤š¬
For example, if one part of my article covers a complex concept, the AI voices can engage in a back-and-forth conversation, breaking down the idea and making it easier to digest for listeners. This approach mimics real-life discussions, making the podcast feel less like a monologue and more like an insightful conversation.
The process was surprisingly smooth, and I was impressed with how natural the conversation sounded. It didnāt feel like a robotic repetition of my text but more like two intelligent voices having a thoughtful discussion about the article.
That said, Iām treating this as a learning process. Every new episode teaches me something about how AI interprets my articles, and Iām constantly experimenting to improve the results.
Comparing the Written and Audio Experience
A big part of this experiment is seeing how the written and audio experiences differ. Reading an article allows for deep, focused engagement with the content, while listening offers convenience and accessibility. What Iāve noticed is that the AI podcast episodes provide a condensed version of the articles, which is great for getting the key takeaways quickly.
For those who prefer a more detailed exploration, I still recommend reading the original articles. But if youāre on the go or want a quick summary, the AI-generated podcast offers a handy alternative.
This experiment is about more than just showcasing AI technology, itās about finding out what works best for my audience. I encourage everyone to give the podcast a listen and share feedback. Did the AI capture the essence of the article? Was the conversation engaging? What could be improved?
AI in Content Creation: A Growing Trend
The use of AI in content creation is a growing trend, it is rapidly changing how we produce and consume content. I see tools like NotebookLM as part of a larger movement thatās making content creation more accessible, especially for solo creators or small teams who might not have the resources for full production processes.
As I continue this journey with "Code Quests", Iām excited to see how AI will further evolve and impact the way we share knowledge.
Conclusion
While this is still an experiment, itās clear that AI can help creators repurpose their content efficiently and reach broader audiences. The key is to embrace the technology while continuing to refine and improve the output.
So, whether youāre reading my articles on DEV.to or tuning into "Code Quests" on Spotify, I hope you find value in this exploration.
Oh, and here's where it gets a little meta... Iām pretty curious to see what the AI will generate for this article about the AI! š It's like AI-ception!
Once the podcast episode for this goes live, I'll drop the link in the comments so you can listen to the AI discussing itself. Should be interesting, right? Stay tuned! š§