I’ve used Google’s NotebookLM to organize research, summarize interviews and even turn my family’s information into a useful “wiki.” But recently, I started wondering whether the AI notebook could do something much less obvious: could it help me understand myself? Turns out, it can.
NotebookLM is no longer just a project manager or research partner. And, now that it’s included in Workspace plans, and for many work and school accounts, it functions as a core service alongside tools like Gmail, Calendar and Docs.
Google has also started bringing NotebookLM into Workspace Studio, which means existing notebooks can be used as knowledge sources for automations. That’s probably why this experiment felt so natural. While I usually ask ChatGPT for help with my toughest mindset questions, leaning on NotebookLM to coach me like Jay Shetty, made me wonder why I hadn’t tried it sooner.
NotebookLM for real life
Jay Shetty, the author of “Think Like a Monk” and host of the On Purpose podcast, is known for making ideas around mindfulness, purpose, presence and emotional patterns feel practical. The goal here was not for NotebookLM to impersonate anyone, but instead, to see whether a Jay Shetty-inspired mindset could help the AI spot something I was too close to see.
To make this experiment work, I needed to give NotebookLM enough material to analyze me. It already knows Jay Shetty since he’s famous. But NotebookLM works best when it can pull from documents and notes you upload.
So, to start, I created a new notebook and added three sources. The first was my weekly schedule. I included work meetings and deadlines, kid logistics like soccer games and gymnastics practice, and I included errands, writing blocks, workouts and the small pockets of time I usually label as “free.”
The second was my to-do list. This was not a neat productivity list. It included story ideas, household tasks, emails I needed to answer, grocery lists, chores, appointments, follow-ups and the random mental clutter that seems to multiply when you have a job, a home and three kids.
The third was a short journal-style note. I wrote about how I felt “on top of things” but still exhausted by 8 p.m. most nights. I also admitted that even my downtime often felt scheduled, measured and slightly rushed.
Because this involved personal material, I kept the sources limited to notes I was comfortable uploading. I avoided sensitive financial information or deeply private family details. And while those elements could have made this even more useful, it’s important to draw the line. Using AI should not require handing over anything you would regret sharing.
The prompt I used
I really wanted to avoid asking NotebookLM for generic life advice. I really wanted it to analyze my life as if I were studying for a final exam about me. A bit meta, sure, but because I know how helpful NotebookLM is for studying, I knew it could handle the task. I knew it could spot the patterns that often hold me back.
Prompt: Using themes often associated with Jay Shetty’s work — mindfulness, purpose, presence, emotional friction, habit loops, gratitude and letting go — analyze my uploaded sources. Do not give me generic productivity advice. Look for patterns across my schedule, tasks and reflections. What am I doing on autopilot? Where do my actions appear misaligned with what I say matters to me? Identify my biggest blind spot and explain how it may be draining my energy. Then give me one small, realistic change I could make this week.
The response surprised me because it skipped the obvious advice. NotebookLM did not tell me my schedule was too full, even though it clearly was. It did not tell me to outsource more, meditate for 20 minutes or create a better morning routine. Instead, it pointed out a contradiction I had not noticed: I was treating downtime as another performance metric.
Based on my uploaded notes, NotebookLM observed that I was not only optimizing my work and parenting responsibilities. I was also optimizing the things that were supposed to help me recover. Essentially, I was using down time to work more.
The line that hit me hardest was this: “You are not recharging. You are completing the task of resting.”
That was the blind spot.
I also tried NotebookLM’s Audio Overview
To make the experiment more NotebookLM-specific, I also generated an Audio Overview from the notebook. This is like a custom podcast that feels surprisingly strange. I’ve generated hundreds of these and hearing your own sources shared back with you in this way never gets old for me. Because, reading the insight is one thing, but hearing AI hosts discuss my tendency to turn rest into another productivity metric made it land differently.
Google describes Audio Overviews as AI-generated discussions based on your sources, and that is exactly how this felt. It did not replace the written analysis, but it added another layer. The conversation format made the pattern easier to absorb because I was hearing it explained back to me instead of staring at another block of text.
That said, Audio Overviews are still generated by AI, so I would not treat them as flawless or deeply authoritative. For this experiment, they worked best as a reflection tool, not a final answer.
What I like about the Audio Overviews is you can interject with your own questions. Almost like a listener “calling” into a radio show. Using the AI hosts I asked :What would a Jay Shetty-style reframe of this pattern sound like?
As another added layer of NotebookLM, I even created a cinematic overview and was able to watch the AI’s response as a video.
How to try this yourself
If you want to try this with your own life, the most important step is choosing the right sources. Nothing needs to be neat or even finished, that’s another reason I enjoy using NotebookLM. You can upload anything, add links to your personal blog or social media account and just about anything else. Notebook just needs honest material to work.
Start with simple documents you already probably have on your phone. These could be:
- Your weekly schedule: Include work, family responsibilities, errands, workouts, appointments and downtime.
- Your current to-do list: Add everything from major work projects to tiny tasks you keep avoiding.
- A short brain dump: Write a few paragraphs about how you actually feel right now. Are you overwhelmed? Bored? Productive but drained? Restless? Stuck? Be honest.
I used Jay Shetty as a mindset coach, but you don’t have to. Try using a prompt such as: “Using themes often associated with [name of person]’s work — analyze my uploaded sources. Then give me one small, realistic change I could make this week.”
After NotebookLM answers, ask these follow-ups:
- What evidence from my sources supports this blind spot?
- What is one thing I should stop optimizing?
- What would a Jay Shetty-style reframe of this pattern sound like?
- Give me a five-minute reset based on this insight.
Those follow-ups are what make the experiment more useful. The first answer may be interesting, but the second and third prompts force NotebookLM to show its work and turn the insight into something you can actually use.
NotebookLM is not a therapist — but it can be a useful mirror
There are obvious limits here. NotebookLM is not Jay Shetty and it’s by no means a therapist and shouldn’t be treated as one. It does not know your full life, your relationships or the emotional context behind every item on your calendar. But it can act as a pattern-recognition tool. And when the sources are personal enough, those patterns can feel surprisingly revealing.
I’ve used prompts like this before on ChatGPT, but the visuals and audio “extras” from NotebookLM flesh out the response even more. Honestly, it’s what made this experiment work for me. No, this AI tool did not give me a brand-new life philosophy, but it did show me that I was applying the same pressure to rest that I apply to work.
Try using NotebookLM in this way and you may just discover a new favorite AI tool. Share in the comments if you experiment in this way.
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