Day 1: Using AI to Plan My Year of AI Experiments
How I used AI tools like Notebook LM and Claude to Plan My Year of AI Experiments
TABLE OF CONTENTS
Why I'm Starting This Blog
I've spent my career at the intersection of curation, human resources, industrial-organisational psychology, and technology. Now I'm asking a question that feels urgent: What does human work look like when AI becomes our constant collaborator?
This blog is my daily experiment log. Each post will document a tangible output I've created using AI tools—not to prove AI can do things for us, but to demonstrate how humans with curiosity, lateral thinking, and domain expertise can use AI to scale their impact.
The thesis I'm testing: AI is a powerful amplifier, but it still requires human creativity, judgment, and taste to produce genuinely useful work.
Today's Experiment: Planning Goals Using AI and Podcast Insights
For my first entry, I wanted to do something meta—use AI to help me plan how I'll conduct AI experiments throughout the year. I started with a podcast episode with Mel Robbins featuring Professor Katie Milkman on strategies for lasting change.
My Process
Step 1: Extract actionable insights from the podcast
I uploaded the podcast to NotebookLM and used this prompt:
"Provide a concise and accurate list of all the recommendations covered in this podcast interview about strategies for lasting change in a way that the reader can easily adopt and apply in real life."
Step 2: Dig deeper into what intrigued me
The phrase "make a concrete plan" stood out from the summary, so I asked a follow-up question:
"Make a Concrete Plan - what is the professor's specific advice to making a plan that will be effective?"
NotebookLM returned a structured framework with five key components:
- Set a Concrete and Measurable Goal – Move from abstract desires to specific, measurable targets broken into daily actions
- Use Cue-Based Planning – Link desired actions to specific triggers (time or event-based)
- Engineer for Obstacles – Identify friction points before they arise and plan around them
- Layer in Social Support and Fun – Add accountability partners and temptation bundling
- Build in Emergency Reserves – Include flexibility days to prevent quitting after a single misstep
Step 3: Apply the framework to my specific goal
I brought these insights into Claude and asked:
"How can I use this advice to create a plan to conduct experiments using AI that I can post daily to the blog?"
My 2026 Daily AI Experiment Plan
Here's the plan Claude helped me develop by applying Professor Milkman's framework:
The Goal (Concrete and Measurable)
Publish one blog post daily for 365 days, each documenting a specific, replicable AI experiment with a tangible output.
Success criteria:
- Each post includes the problem, tools used, prompts applied, and the output
- Posts are useful enough that readers could replicate the experiment
- I maintain consistency across the full year
The Cue-Based System
Trigger | Action |
7:00 AM coffee | Review experiment queue and select today's topic (I’m using Notion and will share more about this in a future post) |
8:00 AM (blocked calendar) | Conduct the experiment using AI tools |
12:00 PM (lunch hour) | Draft the blog post |
6:00 PM | Edit, publish, and schedule promotion |
The specificity matters. "I'll blog about AI" becomes "At noon, I sit at my desk and draft today's post documenting what I made that morning."
Engineering for Obstacles
Obstacle | Pre-planned solution |
Runs out of experiment ideas | Maintain a running list of 30+ ideas, updated weekly |
Low energy or sick days | Pre-write 5 "buffer" posts for emergencies |
Travel | Schedule lighter "reflection" posts that don't require new experiments |
Perfectionism slows me down | Set a 45-minute timer for drafting—publish "good enough" |
Temptation Bundling
- AI experiments happen only during my morning focus block with a cup of coffee
- Post-publication reward: 15 minutes of guilt-free reading or podcast listening time
- Weekly "fun experiment Fridays" where I try something purely creative with no practical requirement
Social Accountability
- Share each post with a small accountability group
- Monthly check-ins with a friend who's also exploring AI tools
- Engage with blog comments and questions—the community becomes the accountability partner
Emergency Reserves
Instead of demanding 365 posts or nothing:
- Target: 365 posts
- Minimum: 300 posts (65 "emergency reserve" days)
- Recovery rule: If I miss a day, I don't spiral—I just continue the next day
This prevents the "what-the-hell effect" where one missed day derails everything.
What I Learned Today
This process demonstrated something important: AI didn't give me the plan. I had to:
- Choose the right source (the podcast)
- Ask the right questions (zeroing in on "make a concrete plan")
- Synthesize across tools (NotebookLM → Claude)
- Apply it to my specific context (my background, constraints, goals)
The AI accelerated what would have taken hours of note-taking and research. But the judgment calls—what to focus on, what resonates with my situation, how to adapt generic advice—those remained mine.
Try It Yourself
Tool 1: NotebookLM (or similar audio/document analysis tool)
Prompt 1:
"Provide a concise and accurate list of all the recommendations covered in this podcast interview about strategies for lasting change in a way that the reader can easily adopt and apply in real life."
Prompt 2 (follow-up on what interests you):
"[Topic that intrigued you] - what is the professor's specific advice to [doing that thing] effectively?"
Tool 2: Claude (or similar conversational AI tool like ChatGPT or Gemini)
Prompt:
"How can I use this advice to create a plan to [your specific goal]?"
Then iterate until you have a plan you'll actually follow.