Key Learnings
- AI Doesn’t Replace Your Thinking — It Reveals It: Discover why integrating AI into your workflow won’t automatically make you faster or smarter. Instead, it amplifies your existing habits, exposes blind spots, and shows you where your thinking lacks clarity — a critical insight for anyone experimenting with AI adoption in the workplace.
- Creativity Grows When You Partner With AI, Not Outsource to It: Learn how AI can enhance creative flow, help you break through mental blocks, and generate new angles — as long as you stay present in the process. This takeaway reframes AI as a catalyst for deeper creativity rather than a threat to originality.
- Personalizing AI Is the Key to Real Productivity Gains: Find out why the real power of AI lies in tailoring tools like ChatGPT and Copilot to your goals, workflows, and communication style. When you customize AI intentionally, it reduces friction, strengthens judgment, and helps you focus on the high-value work only humans can do.
This post closes out my four-part Learning By Doing series. In the first three pieces, I explored why self-directed learning is such an essential growth skill, how the mental model the map is not the territory reshapes the way we interpret our experiences, and why intentional experimentation helps us learn faster than planning ever will.
In exploring those themes, I kept coming back to one idea that connected them all: real growth comes from exposure to feedback. Not just the external kind, but the internal cues we notice when we try something new — the shifts in clarity, confidence, resistance, or momentum.
Feedback is always available — around us and within us — and our willingness to seek it out determines how quickly we evolve. Small experiments accelerate that evolution because they force us to learn quickly, let go of assumptions, and adapt in real time. My own experiments in this series followed that pattern: curiosity-driven, self-directed, and structured enough to surface meaningful insight without overwhelming the process.
This final experiment — a 10-day deep dive into using AI in my daily work — ended up revealing as much about my thinking as it did about the tools themselves.
The Hypothesis I Wanted to Test
Before diving in, I needed a simple but clear hypothesis to anchor the experiment:
If I intentionally integrate AI into my daily workflow for 10 days — not as a shortcut, but as a thinking partner — then my focus, creativity, and judgment will strengthen rather than weaken, because I’ll learn when to rely on AI, when to override it, and how to shape it to my working style without losing my voice or agency.
This wasn’t a test of productivity or efficiency alone. It was a test of the human side of AI adoption:
- How would AI affect my mental flow and focus?
- Would it help me think more deeply or encourage shortcuts?
- Would it fuel creativity or flatten it?
- Could I trust its output — and know when not to?
- And could I use AI in a way that supported, rather than diluted, my voice?
Those questions shaped everything that followed.
Designing the Experiment
To explore those questions honestly, I grounded the 10 days in five guiding prompts:
- Did AI make me think faster or lazier?
- Did it enhance or dilute creativity?
- How did I learn to trust (or verify) AI outputs?
- How could I maintain my voice while using AI-generated text?
- How could I personalize AI so it reduced friction without taking control?
Then I structured each day around real work scenarios:
- Day 1 — Define My AI Intention
I identified three high-value use cases: 1) communication, 2) information synthesis, and 3) administrative load. I also explored the roles AI might play — assistant, analyst, advisor, strategist — and which ones aligned with my workflow. - Day 2 — ChatGPT as a Thinking Partner
I focused on prompting and developing mental models for more productive conversations. - Day 3 — Copilot in Word & Outlook
I tested whether AI could accelerate writing and communication without flattening my tone. - Day 4 — Email Automation
I automated parts of my inbox and watched how much mental noise it eliminated. - Day 6 — Business Case Analysis
I pushed AI into structured problem-solving to test accuracy, depth, and blind spots. - Day 7 — Systems Thinking with AI
I zoomed out to see how the tools could support one another and where they created friction points. - Days 8–10 — Integration Sprint
I built and refined an actionable plan rooted in the three high-value use cases.
This structure gave me enough direction to stay focused while keeping the experiment flexible and exploratory.
What I Learned About Focus, Creativity, and Judgment
AI doesn't inherently make your thinking better — it magnifies whatever habits you already bring to the table.
When I approached a task with clarity, AI amplified it. When I came in scattered, the output mirrored my confusion. I had to sharpen the ‘what’ and ‘why’ of my objectives in order to accomplish the goals I’d set out. AI rewards clear thinking; it doesn’t create it for you. In fact, if you’re not careful, it can take you down rabbit holes, far away from your initial objectives.
Creativity didn’t disappear — it shifted.
AI didn’t replace my creative process; it changed its shape. Instead of wrestling with blank pages, I spent more time refining ideas, exploring possibilities, and sharpening the narrative. The creativity became more about direction and judgment than initial generation — and that felt surprisingly energizing.
Trust is earned through verification, not assumption.
AI was excellent at synthesizing straightforward information, but it stumbled with data sources and occasionally with logic. I learned to treat it like a well-meaning collaborator: valuable, but not infallible. Cross-checking became a natural part of the process — and strengthened my critical thinking.
My voice stayed intact when I stayed present.
The danger wasn’t that AI would overwrite my voice. It was that I might let it. When I wrote first and used AI to refine or extend, the outcome sounded like me. When I handed too much over too early, the tone drifted. The key was simple: stay engaged.
Personalization is where AI becomes transformative.
AI responds to input, feedback, and iteration. The more I shaped AI to my workflows — vocabulary, templates, goals, tone — the more helpful it became. But personalization also revealed the real purpose: AI isn’t there to do everything for you, but to remove friction so you can focus on the work only you can do.
The Unexpected Lessons
A few discoveries stood out:
- AI exposed where my thinking lacked clarity.
When I struggled to articulate what I wanted, the issue wasn’t the tool — it was my vision. - Reflection became easier and more structured.
Asking AI to summarize, contrast, or challenge my ideas helped me understand how I think, not just what I think. - Not all friction is bad.
Some of the deeper insights came from slowing down — rewriting, rethinking, or revisiting prompts.
How This Experiment Changes My Work Going Forward
I didn’t walk away with a perfect system — but I did leave with clarity about where AI genuinely enhances my work and where it doesn’t.
AI is most valuable when it helps me:
- clarify complex thoughts
- structure ideas
- remove administrative noise
- explore new angles
- strengthen reasoning
- stay focused on high-value work
In the end, this experiment reaffirmed something important: AI is a leverage tool, not a substitute for judgment. The more I used it intentionally, the sharper my thinking became.
And that, in many ways, is the whole point of learning by doing.
Final Thoughts on Learning By Doing
As I close out this series, I’m reminded that Learning By Doing isn’t a method — it’s a posture toward life. Each experiment, whether personal or professional, expands our understanding of what we’re capable of and reveals blind spots we wouldn’t catch from the sidelines.
This AI experiment was simply the latest chapter: a way to test my assumptions, stretch my thinking, and build a partnership with a technology that’s evolving as quickly as we are. If there’s one lesson that runs through all four posts, it’s that growth doesn’t come from certainty or perfect plans. It comes from the willingness to try, observe, adjust, and keep going — even when the path isn’t fully mapped. My hope is that this series encourages you to run your own experiments, not to chase efficiency alone, but to discover more about how you think, what you value, and how you want to show up in the world as it changes.
