Posts Tagged creativity
From Spoken Thoughts to Connected Notes: My Voice Journaling Workflow
Posted by claudiolassala in Personal Growth on December 15, 2025
Most of my thinking doesn’t start at a keyboard. It starts while I’m driving, walking, or stepping away from a meeting—talking things through out loud, one imperfect sentence at a time. Over the years, I’ve learned that if I don’t capture those moments right then, they disappear. This post is a walkthrough of the voice journaling process I use today—from recording quick audio notes on my phone to turning them into connected, searchable thoughts in Obsidian, with a bit of help from automation and AI along the way.
Long story short, here’s my current voice journaling process.
Step 1: I voice out my thoughts and record them using the Voice Record Pro app on my iPhone.

I often do that multiple times during the day: driving, walking, in between meetings, taking a quick break…
Step 2: I “Save to Google Drive” either as soon as I get to my computer, or at least later in the day…

Step 3: I use my Process Journal workflow in Alfred on my Mac when I’m ready to work on my transcripts…

At this point, I may proceed with Step 4, Step 5, or both.
Step 4: I open the transcript in Obsidian and use its Local Graph tool to view additional connections to my daily note.

Step 5: I open the transcript in either Cursor or Windsurf and use AI to analyze, summarize, extract content, or perform other tasks as needed.

How this all works
This is how this all works as of this writing. I continually evolve my system, so I’ll provide an update if there are any essential changes.
When I “Save to Google Drive” a file from Voice Record Pro, it goes to a “Voice Record Pro” folder. I added that folder to the “Offline files” in the Google Drive app on my Mac.

I have set that folder on my local file system as a “Watched Folder” in MacWhisper…

…so it automatically transcribes into a Markdown file.

The original .m4a audio file and its .md file stay in the Voice Record Pro folder…

…until I run my Process Journal Alfred workflow:

That workflow…
- cleans up the markdown, removing timestamps that I don’t need, adding the date to the top of the file as a link to my daily note (e.g., 2025-12-15),
- moves the files to a “voice journal processed” folder
- copies the .md file to my Obsidian Vault (to the “_inbox/voice journal” folder)
I have a “Voice Journaling.code-workspace” file, which I open in Cursor or Windsurf. That workspace includes the “Voice Record Pro” folder in Google Drive and the “voice journal” folder in the Obsidian Vault. I have other “code-workspace” files that include my “voice journal” folder as the source to specific projects where I leverage that content.

Sleep, Time, and AI: Rethinking How We Work
Posted by claudiolassala in Reflective Practice Radio on December 5, 2025
I’ve been thinking a lot about the space between friction and flow—how the tiniest constraints can either drain our energy or create just enough structure to help us stay grounded. In this week’s conversation with Matthew, that theme kept showing up in different forms: time windows, sleep patterns, journaling, old ideas that suddenly feel new again, and the role AI now plays in clearing space for the work that actually matters.
Episode 8 of our podcast (now renamed as Reflective Practice Radio) is one of those conversations where we didn’t plan a theme, but one emerged anyway. And it feels essential right now.
This episode is one of the most honest and wide-ranging conversations we’ve had so far. If you’ve ever wrestled with:
- the tension between creativity and rest,
- the challenge of keeping track of your inner life,
- or the question of how to use AI without losing yourself in the process—
—You’ll probably find something useful here.
Small Windows, Real Progress
Both of us have been feeling how dramatically the creative landscape has shifted. You don’t need a whole weekend to move a project forward anymore.
You need a focused hour.
Maybe even less.
For Matthew, that window opens after he puts his daughter to bed. For me, it happens first thing in the morning—before the world pulls me into meetings, pings, or whatever crisis is unfolding that day. What struck us is how differently those windows feel when AI removes the grunt work that used to fill them.
It’s not that we magically have more time.
It’s that our existing time is finally usable.
And that changes motivation. Side projects that used to die from friction suddenly feel possible again.
The Cost of Pushing Too Hard
But there’s a shadow side to this new speed. The tools move fast, but our bodies don’t.
In the episode, Matthew shared how he recently stayed up working until 2 a.m.—excited, productive, flowing—and woke up with a sleep score of 52. I’ve been there. Most of us have. You think you’re squeezing in “one more hour,” but what you’re actually doing is borrowing energy from tomorrow.
The tricky part?
Your mind doesn’t always tell you the truth in the moment.
It tells you you’re fine.
It tells you you’re just “a little tired.”
It definitely doesn’t remind you that your Tuesday dinner was a massive plate of Brazilian food at 9 p.m., and maybe that’s why you slept terribly.
Without tracking, these patterns evaporate.
With tracking, they become visible—and changeable.
You Can’t Rest With an Open Loop in Your Head
One idea we kept returning to was how hard it is to fall asleep when your brain is holding too many open loops. It doesn’t matter if you turned off the lights and closed the laptop. If you were working on something exciting right up until bedtime, your brain is still sprinting long after your body has given up.
So I’ve learned to do something simple:
Get the thoughts out.
Sometimes that means journaling before bed.
Sometimes it means a few bullet points on my phone.
Sometimes it means capturing the very first thought I have when I wake up—before it gets swallowed by the day.
It’s amazing how often those little fragments become the seeds of a future idea.
Journaling as a Daily Stand-Up with Yourself
A big part of this episode is about journaling—not as a performative habit or a trendy productivity hack, but as a form of self-maintenance.
We track the health of our software projects better than we track the health of our own lives.
And that’s a problem.
If you ask anyone what their team committed on Tuesday, they can pull up Git logs, sprint boards, and meeting notes. Ask them what they felt on Tuesday, and they have nothing to say. No data. No breadcrumbs. Just vibes.
This is why a few of us at Improving are building an AI-assisted journaling workflow right into our IDEs.
Not to automate reflection, but to support it:
- Ask a few good questions
- Capture the raw thoughts
- Summarize them
- Surface patterns over time
It doesn’t replace awareness—but it gives awareness something to hold onto.
Old Ideas Become New When You’re Ready
One of my favorite parts of the episode is when we talk about old ideas clicking at the right moment. Stoicism, SOLID principles, timeless patterns—none of these are new. But your relationship with them changes as you change.
No one steps into the same river twice.
No one reads the same idea twice, either.
Sometimes the explanation someone else gives is the one that finally lands. Sometimes you become the person whose explanation unlocks it for others. That’s the beauty of sharing your experience: the theory isn’t new, but the expression is uniquely yours.
What Do We Actually Want to Make Easier?
We ended the conversation with a subtle but essential question:
What should be made easier, and what shouldn’t?
AI can make everything frictionless if we let it—but that’s not always good.
In fact, effort is often the point.
Removing the wrong kind of friction frees us up.
Removing the correct type of friction robs us of growth.
A game with no difficulty isn’t a game.
A life with no resistance isn’t a life.
So what we want isn’t “easy.”
What we want is clear space to do the hard things well.

The Drift of Memory, the Speed of Tools, and the Value of Story
Posted by claudiolassala in Reflective Practice Radio on November 21, 2025
Every week, when Matthew and I sit down to record The Blank Page Podcast, I never know exactly where the conversation will go. I only know one thing for sure: if we follow our curiosity, we’ll end up somewhere worth exploring. Episode 7 was no exception.
The Week AI Moved Fast Again
This week brought another wave of AI releases—Google’s Gemini 3, a new AI-powered IDE called Anti-Gravity, and a model with the ridiculous-yet-fantastic name “Nano Banana Pro.” Matthew lit up, describing the new image‑editing capabilities, especially its ability to blend multiple source images into a cohesive composite. It’s the kind of feature that would’ve required specialized tools and hours of effort not that long ago.
Meanwhile, I spent part of the week experimenting with book‑cover concepts. I moved between ChatGPT, Gemini, SnagIt, and back again—nudging, refining, iterating. The early results weren’t great. But then, suddenly, they were. The shift wasn’t dramatic; it was subtle. A little more polish here, a little better structure there. I enjoy those small steps forward. It’s the feeling of “Ah, now we’re getting somewhere.”
Tools Are Only Interesting When They Solve a Problem
As Matthew explained why he loves new tools, I was reminded again of something I’ve been repeating for years: it’s not about the tool—it’s about the problem (with that said, I’ve seen some great ways Matthew puts the shiny toys to good use!)
New IDEs are fun to try, but if the one I already use gets the job done, that’s where I stay, at least until a real need emerges or when I set time to experiment with them.
That’s why I don’t chase every shiny thing. Instead, I keep a catalog of problems I want to solve. If a new tool gives me leverage, I’m ready.
Sometimes the tool doesn’t even need to be the perfect one—it just needs to work well enough.
When “Good Enough” Means “Go”
A great example came this week. I wanted a quick survey for an internal session—not a full-blown form, not a polished UI, just a place to capture answers. Instead of opening yet another form builder, I gave Gemini a markdown list of questions and said, “Create an app for these.” One minute later, I had a working, shareable mini‑app.
No friction. No overhead. Just done.
Moments like that still surprise me. They shouldn’t, not after everything we’ve seen in the last two years—but they do.
Prototypes in Minutes, Not Weeks
The part of the conversation that resonated most with me was the discussion of how AI accelerated a recent User Acceptance Testing effort. All the sessions were recorded. I knew I’d be able to revisit the transcript later, reflect on the discussions, and dig deeper into the wording, reactions, and sentiment.
By the time the meeting ended, I had several ideas to explore. I dumped the transcripts and codebase context into Cursor and asked it to create a plan. I expected it would take half an hour to build the prototype.
Cursor did it in five minutes.
Not a perfect solution. Not even a final one. But a tangible proof‑of‑concept—something I could run, test, and refine.
Within a few hours, I had a working prototype to show the stakeholders. They validated it right away. And only then did I begin thinking about implementation details.
The speed of that loop—idea → plan → prototype → validation—still blows me away.
Diverge, Converge, Repeat
We talked about design thinking, and how AI is becoming a natural partner in the diverge–converge cycle:
- Diverge into possibilities.
- Converge into a clear direction.
- Diverge into solutions.
- Converge into the next step.
It’s the same idea I use with humans: get multiple perspectives, compare them, merge the best parts, and refine again. AI makes the loops faster.
And the comparison with humans matters. Matthew doesn’t ask a single model for an answer. He asks multiple models for their perspectives, then has them read each other’s plans, poke holes in them, and incorporate improvements. It’s the closest thing we have to creative collaboration in software.
The Strange, Useful Imperfection of Memory
Somewhere along the way, our conversation drifted—beautifully—into the nature of memory. Human memory. Machine memory. The drift that happens over time.
Models remember things across conversations, sometimes helping and sometimes confusing. Humans do the same. We reconstruct memories from fragments, fill gaps with stories, and treat the stitched‑together narrative as fact.
But as I’ve been revisiting my own 20 years of blog posts, I’ve been reminded how important it is to:
- Capture snapshots of what we believed.
- Revisit those snapshots with new knowledge.
- Notice the drift.
- Update the beliefs.
That’s the heart of my weekly Back to the Spiral newsletter. Past → Present → Future. What I’m doing now, what I’ve done before, and where I think I’m headed—a self‑reflection loop powered by notes, transcripts, old talks, journals, and weekly pause points.
AI accelerates our thinking. But reflection anchors it.
Language, Culture, and the Drift of Meaning
From AI memory, we drifted into human language—how words evolve, how meanings shift, how culture shapes our vocabulary.
We laughed about Portuguese speakers using English loanwords for things that already have perfect Portuguese equivalents. But underneath the humor was a deeper point: nothing stays fixed. Language drifts. Beliefs drift. Cultures drift.
Even our memories drift.
Which is why capturing our thoughts matters. Because the moment will not come back. At least not in its original shape.
What Endures
As always, we closed with a discussion of storytelling. Effects fade. Tools become obsolete. Features get replaced.
But stories carry forward.
It’s why a book like Fahrenheit 451 still hits hard today. And why, when Matthew and I record these episodes, I’m reminded again and again how meaningful it is to sit down, hit record, and talk.
Because somewhere between curiosity, reflection, and conversation, we stumble into the insights we didn’t know we were looking for.
If this episode sparked a thought, question, or tangent you want us to explore, let us know. The Blank Page is always open.

Looking Ahead While Moving Faster: Lessons from AI, Mentoring, and Motorcycles
Posted by claudiolassala in Reflective Practice Radio on November 14, 2025
Six episodes in, The Blank Page Podcast keeps doing what we set out to do: show up with half‑formed thoughts and leave with clearer language, better questions, and a few ideas worth trying this week. This conversation moved from public‑speaking jitters to journaling, from transcript workflows to AI‑powered facilitation, and landed on an unexpected (but valuable) metaphor: what racetracks can teach software teams about speed, safety, and where to look next.
🎥 Watch the full episode of The Blank Page Podcast: Episode 6 for the complete conversation.
Practicing in Public (and Setting Expectations)
We opened with Matthew’s honest confession: public speaking is not his thing—so he’s leaning into it anyway. The key that unlocked progress wasn’t bravado; it was expectation‑setting. If you introduce yourself as the all‑knowing expert, expect hard questions. If you say, “Here’s what I’m learning; come learn with me,” the room leans in. That shift turns a performance into a practice.
Two habits reinforced the point:
- Say “I don’t know” early so you can move toward knowing.
- Ask better next questions, not perfect ones. Optimize for learning the very next thing.
Journaling as Time Travel
We revisited why journaling matters. Writing publicly for decades (and privately even more) creates a record you can return to. Old posts make you remember how it felt not to know so that you can teach from empathy, not hindsight bias. The longer you practice, the easier it is to forget the core—journaling helps you rebuild it.
AI Workflows That Feed Reflection (Not FOMO)
Instead of chasing every shiny tool, we shared two pragmatic loops:
- Newsletter triage → weekly AI summaries. Skim daily AI digests, route them to a label, then let an agent compile a weekly, personalized “what actually matters” brief.
- Talk transcripts → resonance analysis → treadmill review → blog. Grab YouTube transcripts of talks, analyze for themes that match (or challenge) our work, watch at speed, slow down at the “meaty” parts, voice fresh thoughts, then draft a post. The goal isn’t to consume more; it’s to convert input into insight you can use.
“AI Won’t Replace the Facilitator”
Meeting bots can capture words, action items, and tone. What they miss still matters: body language, politics, who is unusually quiet today, who leans in when a slide appears. That’s the facilitator’s work. On Scrum teams, we should carry those observations into retro—not just what we shipped, but how we presented the work and how stakeholders reacted. Poor sprint reviews can erase the value of great sprints.
From Cost‑Cutting to Capacity
Internally, we’ve started reframing how we talk about our work: don’t sell “cost‑cutting,” sell capacity. AI‑powered consultants don’t simply deliver cheaper—they deliver more: more validated experiments, more iterations, more value pulled forward in time.
Track Lessons for Tech Teams
My racetrack practice offered a map for teams moving faster with AI:
- Speed changes what matters. Go faster, and you must move your body sooner and change where you look sooner. In product work, that means changing the horizon—maybe tighter release cycles, more frequent alignment, or shifting from single stories to story maps.
- Safety scales with skill. “Vibe coding” can move in a straight line fast, but can it brake, turn, and protect users? AI‑powered consultants run with guardrails—security, data protection, and recovery—because other people are now in the car.
- Collapse the checklist. Where we once had many discrete tasks (design, stub, implement, validate), AI lets us collapse steps while keeping intent clear. Like driving: you don’t consciously run a 12‑step checklist to get into first gear anymore; you still do the essentials, just faster and safer.
- Lap after lap, adjust. Tracks don’t change shape, but laps are never identical. Likewise, sprints repeat but conditions vary—so instrument the work, observe deviations, and course‑correct without drama.
Humans in the Loop (Still Required)
We told a story where raw meeting audio was chaotic—overlapping voices, crosstalk—yet the AI‑cleaned transcript surfaced a clean, business‑ready summary. Powerful. And still: a human reviewing diarization, assigning voices, and clarifying intent made it truly useful. The pattern holds: AI accelerates, humans ensure accuracy, ethics, and meaning.
What We’re Trying Next
- Keep expectation‑setting at the top of every talk.
- Double down on weekly journaling—not for posterity, but to teach from empathy.
- Tighten release horizons so our “reference points” match the speed we can now build.
- Frame our work as capacity creation, not cost‑cutting.
Reflection and Wrap‑Up
We ended where we often do: with presence. The tech is exciting, but the real impact is how it shapes our days—more clarity, better questions, faster feedback, and enough margin to have dinner with the people we care about. That’s the work.

Impact Technology: Rethinking Information and Wisdom
Posted by claudiolassala in Reflective Practice Radio on November 7, 2025
Real Conversations, Real Growth
Five episodes in, our discussions have evolved into something more profound than just tech or process. Each one has become a snapshot of how we’re learning, teaching, and experimenting with ideas together. This episode continues that thread—an honest, curious exploration of how I use AI, reflection, and collaboration to grow as a creator and thinker.
🎥 Watch the full episode of The Blank Page Podcast: Episode 5 to hear the complete conversation—from AI prompts and problem statements to the spiral of data, insight, and impact.
The AIR Experiment
Matthew kicked things off by mentioning our latest AIR meeting (AI Roundtable at Improving), where a teammate presented his latest AI experiments. He’s been training models using Python and Claude to solve math problems and perform reasoning tasks—starting from scratch and narrating his process in real time. It inspired us to revisit how we learn and teach with AI.
We discussed how each of us approaches these projects. I’ve been documenting my own AI-first experiments as videos, blog-style writeups, and full-length walkthroughs—letting colleagues “pick their poison.” Matthew suggested adding repos so others can follow along. I pushed back slightly: rather than copying prompts, people should learn how to think through them. “Don’t give the fish—teach how to fish.”
That insight connected naturally to how I communicate intent to AI tools. Voice dictation came up as a way to show that prompts are really just spoken thoughts—not code or syntax. As I said, “I wasn’t describing a feature; I was describing a problem statement. The prompt was whatever came out of my mouth as I was explaining the problem.”
Planning, Auditing, and AI Feedback Loops
From there, Matthew shared his method for developing plans with AI—creating a plan, then spinning up a second instance to audit it, like bringing in a fresh developer for a peer review. He treats each AI session as a separate collaborator, offering a second opinion. I shared how Cursor’s new plan mode now auto-generates clarifying questions, creating a similar back-and-forth that refines understanding rather than code.
Both of us agreed: the goal isn’t just writing code faster—it’s thinking better.
The Spiral: From Data to Impact
I then unveiled a framework I’ve been developing—the Data to Impact Spiral, as I ponder this quote:
We are drowning in information and starving for wisdom. – Tony Robbins
Here’s how I mapped it:
- Data becomes Information when structured.
- Information becomes Knowledge when understood.
- Knowledge becomes Insight when applied.
- Insights accumulate into Wisdom.
- Wisdom only matters when it creates Impact.
Then the spiral continues—impact leads us back to collecting new data, better information, deeper knowledge.
Matthew visualized it as a continuous forward spiral—not a loop but a progression powered by curiosity and action (which is precisely how I visualize it, too!). We explored how this applies to IT itself: perhaps “Information Technology” should evolve into Impact Technology.
Living Wisdom
The conversation deepened into what wisdom means. Is wisdom without application still wisdom? I argued that lived experience completes the cycle: “If you haven’t done anything with it, it’s not wisdom—it’s just knowledge.”
We explored how culture and language shape understanding. The English word insight has no perfect Portuguese equivalent, so Brazilians often use the English term. This led to a larger reflection on language accessibility, the limits of translation, and how communication gaps affect how people use AI.
Language, Accessibility, and AI
Matthew expanded this to accessibility in general—how not everyone, even native speakers, has the same command of language to express their intent clearly to AI. He connected it to his recent work on web accessibility and screen readers, showing how thoughtful design can open new worlds for people.
Together, we noted that clear intent and precise language lead to better AI outcomes.
From Data to Impact in Practice
The spiral came to life in a real-world example: I described how produce warehouse managers think in data terms—inventory, temperature, and shelf life—but what they really seek is impact: fewer losses, better margins, less waste. “If it ain’t selling, it’s smelling.” That visceral insight grounds the abstract spiral in something real.
I even used NotebookLM to generate user stories based on this produce scenario—covering business, user, customer, societal, and alignment value. The result: richer conversations that start with human pain points, not technical specs.
Pre-Mortems, Personas, and Better Conversations
As the episode wound down, we discussed using AI for pre-mortems (instead of post-mortems)—asking what could go wrong before starting a project. Combined with historical company data, these tools could forecast risks and refine decisions. Personas and AI debates (like NotebookLM’s “Critique” and “Debate” features) become a way to simulate diverse perspectives before real problems arise.
Rapid AI Prototyping: The 30-Second Wow
To end on something concrete, I shared a story: during a casual online conversation about scheduling Tech Fridays (a recurring internal presentation at Improving), I explained the problem to AI Studio—and within 15 minutes had a working app. I call it the 30-second wow: a demo that instantly captures attention by showing what’s possible when you articulate problems clearly.
The old reflex was to create a spreadsheet. Now we can just articulate the problem and let the tool create something real.
Reflection and Wrap-Up
We closed the episode on a human note—a reminder to slow down, have dinner, and be present. Because in the end, the real impact isn’t just in the technology; it’s in how it shapes our days, our habits, and our connections.

Capturing the Human Side of Software with AI Tools
Posted by claudiolassala in Reflective Practice Radio on October 24, 2025
In Episode 3 of The Blank Page Podcast, Matthew and I explored how AI can help us rediscover the human side of software—where empathy, curiosity, and collaboration matter as much as code. Through live experiments with tools like NotebookLM and MacWhisper, we showed how technology can amplify reflection, understanding, and creativity rather than replace them.
Key Takeaways:
- AI can amplify the human side of software.
- Record conversations and reflect on them intentionally.
- Use AI to analyze patterns and sentiment to uncover blind spots.
- Trust grows when insights are grounded in real context.
- The blank page was never truly blank—it’s full of human experience waiting to be seen.
🎥 Watch the full episode:
We began by loading transcripts from our previous meetings into NotebookLM and asking it to surface our top three “aha moments.” What came back was a perfect mirror of our philosophy:
- Escaping the blank page – realizing that creation doesn’t have to start from nothing.
- Capturing conversations to drive iteration – turning dialogue into a living source of insight.
- Using natural language to create solutions – bridging human intent and working software through plain English.
That last point led to a fascinating discussion about how far we’ve come—from early tools that promised no-code development to today’s reality of natural language interfaces that actually deliver. After thirty years in software, seeing a system translate a simple user story into working software feels less like automation and more like empathy—technology finally speaking our language.
From there, we explored how these same tools can deepen team communication. I shared that my team, on one project, records and transcribes our daily scrums, then uses AI to surface patterns, emotions, and blind spots. Matthew introduced ConvoMind, his prototype that pairs transcription with sentiment and entity analysis to reveal not only what was said, but also what was missed. Together, we called this blind spot detection—a way for AI to help teams listen to themselves more fully.
One of the most powerful moments came when we explored NotebookLM’s citation and mind-map features, which ground every AI-generated insight in a verifiable context. When the source of truth is visible, trust follows. Instead of fearing hallucination, we gain a clearer reflection of our own words and patterns.
We wrapped up by returning to a core idea: the blank page isn’t empty—it’s waiting to be rediscovered through the traces we already leave behind. Our voices, our meetings, our notes—all of it is raw material for growth. With the right tools, we can see the human side of our work more clearly than ever. It’s up to us to look for it.

Building Genius Mode: Behind the Scenes of Our AI Summer Camp Finale
Posted by claudiolassala in AI & Productivity on October 21, 2025
When an Improver first mentioned her son had gotten caught using ChatGPT for a school assignment, I didn’t think it would spark a whole summer camp. But it did. And a few months later, I was standing in front of a group of high schoolers teaching the final session — Genius Mode — where we explored how to learn faster, study smarter, and build confidence with AI.
This post is about how that class came together, what I shared with the students, and what I learned along the way.
🧭 Starting with the Bigger Picture
We built the camp around three sessions:
- Wake-Up Mode: What AI is (and isn’t)
- Power-Up Mode: How to use it responsibly and creatively
- Genius Mode: How to think better, learn better, and grow with AI
Each session built on the last. Daniel and Jessie led the first two — and I took tons of notes. Jessie showed students how to check sources and write with their own voice. Daniel talked with parents about cheating, motivation, and how tools change but human nature doesn’t. I wanted my class to tie it all together — skills, mindset, and confidence.
If you want the behind-the-scenes story of how the whole camp came together, I wrote about that over on the Improving blog: Improving the Future: Reflections on Our AI Summer Camp.
💡 Designing “Genius Mode”
My theme was simple: “You’re more capable than you think — AI just gives you leverage.”
I kicked things off with a quick demo — switching between English, Portuguese, Italian, and Spanish mid-sentence in a spoken conversation with ChatGPT. It was chaotic, fun, and the perfect example of AI as a learning companion.
Then I asked the students:
“What if you had to learn something you know nothing about?”
To make it concrete, I used American Football — a subject I barely understand — and showed how you could use AI Studio to build a little app that teaches it through something familiar and fun.
👋 Sharing My Own Path
I told them a bit about myself — oldest instructor in the room, born and raised in Brazil, started working at 14, never went to college, and still ended up building software for a living. I said that not to brag, but to make a point: there’s no single right way to learn. Different backgrounds mean different superpowers.
💬 What Does “Genius” Even Mean?
I asked who thought they were a genius. No hands went up. Then I asked who they thought was a genius. That got a few Einsteins, Teslas, and Musks.
I reframed it:
“A genius isn’t someone who knows everything. It’s someone who uses what they know to make an impact.”
We talked about cheating — why people do it, and how AI can tempt us into shortcuts. But when you understand how you learn, you start wanting to use AI for leverage, not replacement.
🧠 Learning How You Learn
We broke down six learning styles — visual, auditory, read/write, kinesthetic, social, and solitary — and I asked students to notice which ones fit them best. Then I showed how AI tools can adapt to those preferences. One example: NotebookLM, which turns your notes into summaries, diagrams, or even a mini podcast.
“Experiment. Observe what works for you. Then use AI to amplify that.”
🔍 Using the ROCC Framework
Daniel had introduced the ROCC framework (Role, Objective, Context, Constraints) in his class. I brought it back, showing how to fill in the blanks:
“If you don’t know the Role, ask AI for one. If you only know part of the Context, let it help you fill it in.”
It’s about thinking clearly over perfect prompting.
💻 Real AI Use Cases
To make it real, I shared a few ways I actually use AI in my life and work:
- Planning a track-day checklist for motorcycle racing
- Creating a video hub for client demos
- Using voice journaling to turn reflections into insights
- Analyzing my blog and talks to learn from past content
- Automating newsletter creation to save time
Each example showed how AI helps me think and create faster — without taking over the work.
🔑 What I Wanted Them to Take Away
“Doing the right thing, at the right time, in the right place.”
That’s the essence of mastery. Tools will change. AI will evolve. But the way we approach learning, creativity, and impact — that’s what defines a real genius.
🎉 Final Message
I wrapped up with this:
“Go be a genius. Be curious, courageous, and creative. Do not skip learning; use AI to amplify your thinking.”
The smiles and questions at the end told me they got it. Genius Mode went beyond just using AI, sharing with the studends some thoughts about learning how to learn, think, and communicate — and realizing that’s a lifelong superpower.

Why We Never Face a Blank Page Again
Posted by claudiolassala in Reflective Practice Radio on October 15, 2025
Our second episode of The Blank Page Podcast is out now, and it dives into something every creator faces: the blank page. Or rather, how not to.
🎥 Watch the episode here:
In this conversation, Matthew and I explore the origins of the podcast itself — how it grew naturally out of our weekly meetings preparing for an Improving Tech Friday talk. Once the talk was over, we realized we missed those conversations. That time to think out loud, share ideas, and connect dots. So we decided to keep the conversation going — and The Blank Page Podcast was born.
The Power of Systems
We unpack what it really means to never face a blank page. For me, that comes from years of building systems — from Evernote to Obsidian — that let me capture ideas, connect them, and revisit them when the timing is right. Those ideas become a second brain, a personal knowledge base that keeps creative momentum flowing.
Matthew adds his perspective through his Substack writing journey and shares how starting with your voice can be the simplest way to break creative inertia. You don’t need a perfect outline to begin — just speak your thoughts, record them, and refine later.
Authenticity and AI
We also dig into authenticity in AI-assisted writing. Why do so many creators feel the need to hide that they use tools like ChatGPT or Claude? For us, AI isn’t about replacing your voice — it’s about refining it. Just as asking a friend to help you edit can teach us new ways to express ideas, learn new vocabulary, and improve clarity without losing our individuality, these tools can do the same.
Growth and Change
Another big theme is growth — how our voices evolve. We talk about the importance of giving ourselves (and others) permission to change. I’ve written over 500 blog posts in 20 years, and looking back, it’s clear how my views and writing style have evolved. That’s not inconsistency — it’s growth.
Poetry, Lyrics, and Feeling Something
We even take a detour into poetry and songwriting — exploring what makes words feel. Whether it’s a poem, a lyric, or a paragraph in a blog post, the power lies in evoking emotion and reflection. If it makes you pause and think, it’s doing its job.
Learning Through Failure
And of course, we touch on learning and failure — how our education system often conditions us to fear mistakes instead of learning from them. True creativity comes from iteration, curiosity, and play.
🎧 Whether you’re a writer, developer, or just someone trying to capture ideas before they fade — this episode is for you.
📺 Watch it here → https://youtu.be/n4PGFlXAgVQ?si=pD3WzjhyRCgNxb64
And remember: if you ever find yourself staring at a blank page, start with your voice.

Visual Thinking: Bridging Ideas, Words, and Images
Posted by claudiolassala in Personal Growth on September 9, 2025
Over the past few years, visual thinking has captured my attention in new ways. It’s a thread that has pulled me backward, revisiting old habits, and forward into new possibilities for learning and collaboration.
Drawing as a Bridge
Years ago, a colleague recommended The Back of the Napkin. At the time, I was frustrated: I often had a clear picture of an idea in my head but struggled to put it into words; sometimes because I couldn’t find the right words, sometimes because I couldn’t find the right English words. I could see in people’s faces when my explanations weren’t landing.
Drawing changed that. Even with crude sketches, I could put something concrete in front of people. It moved the conversation forward. That book provided me with tools to practice, and soon I was sketching ideas ahead of sprint planning, reviews, and backlog refinements. The results were clear: shared understanding came faster, and collaboration improved. People told me my drawings helped, so I kept going.

Books That Shaped My Journey
- The Back of the Napkin → a starting point for sketching ideas.
- See What I Mean → introduced comic strips and storyboards, a great companion for user stories.
- UZMO: Thinking With Your Pen → practical tools for capturing and creating content visually.
- Understanding Comics → deepened my appreciation of visual language.
- Graphic novels and comic-style nonfiction → proof that drawings can clarify complex ideas.
Here’s one of my experiments mixing techniques I learned in See What I Mean and UZMO: Given-When-Then: Past, Present, and Future.
A phrase I discussed with a coworker stuck with me: “We think in images, but we communicate in words.” Except that not all of us think in images.
Visual vs. Verbal Thinkers
Around 2019, I read Jordan Peterson’s 12 Rules for Life. My impression: dense, wordy. Later, I learned why. Peterson is a verbal thinker. He thinks in words. His wife, however, is a visual thinker. That contrast clicked for me.
Then came Temple Grandin. Her book Visual Thinking showed me that there are three main types of thinkers:
- Verbal Thinkers
- Object Visualizers (concrete images; this is me)
- Spatial Abstract Visualizers (patterns and relationships; this is my friend Daniel)
Daniel once presented design patterns “visually,” but what appeared were abstract diagrams rather than the concrete pictures I imagined. Grandin’s framework explained the difference.

Experimenting With Assessments
Grandin’s book includes an 18-question questionnaire to assess thinker types. Curious, I built a prototype tool in Google AI Studio:
- Users answer the 18 questions.
- Results are processed through Gemini.
- A chart shows where they fall on the spectrum.
The key word is spectrum. I may lean toward object visualization, but I also score in spatial and verbal thinking.
This made me reflect on my strengths. Grandin herself has said she struggles with algebra and programming. Musicians, she notes, often score high in spatial thinking. That gave me perspective on where I fit.

My Strengths in Practice
A colleague once told me my superpower is handling abstract thinking—being comfortable with “cloudy” areas while still seeing the big picture.
That plays out in coding:
- I spot code patterns visually (anti-patterns like “arrowhead” leap off the page).
- My instinct isn’t “this doesn’t read right.” It’s “this doesn’t look right.”
The same applies to music. When I write songs, I don’t go linearly. I build the structure, leave gaps, and circle back. I organize from above, like a map.
At the same time, I have verbal strengths. Years of writing blogs and articles have honed my ability to explain things clearly. That combination—visual, verbal, abstract—has become a toolkit I lean on daily.
Learning, Thinking, Communicating
During our AI Summer Camp (Genius Mode), I spoke about learning styles:
- Some learn by reading.
- Some by listening.
- Some by doing.
We all use a mix. Thinking works the same way: visual, verbal, abstract. And for collaboration, communication is the bridge:
- With visual thinkers, show images.
- With verbal thinkers, use words.
- When unsure, prepare for all types.
It’s a full loop: learning, thinking, communicating.
Looking Back, Looking Ahead
When I first studied Lean and Extreme Programming 20 years ago, I valued communication and collaboration, but I didn’t know about thinker types. With this awareness, I have better foresight.
Temple Grandin learned about thinker types in her mid-30s. I learned in my mid-40s. A colleague in his 20s already knows. The earlier we learn, the more we can leverage.
And yes, the HBO movie Temple Grandin is on my watchlist.
Future Possibilities
I’ve been imagining an app:
- Input information.
- Output different perspectives:
- Verbal: as words.
- Spatial: as abstract patterns.
- Object: as concrete images.
- Layer in cultural context—because a visual thinker from São Paulo may picture something different from one in Houston.
Maybe even extend this to VR experiences—immersing ourselves in how others perceive the world.
Food for thought.

Why I Never Face a Blank Page
Posted by claudiolassala in Personal Growth on July 31, 2025
I’m often asked how I come up with so many talks, posts, and ideas.
The truth is, I rarely start from scratch.
I’ve trained myself never to face a blank page—because long before I sit down to write, I’ve already been writing.
For years, I’ve been capturing thoughts as they come:
- in the middle of a meeting
- during a walk
- after a conversation
- or just a flash of insight while coding
Some go into my voice journal. Others land in Obsidian, in a file called “Blogging Ideas”. I jot down fragments—sometimes just a phrase, sometimes a full outline, sometimes a link or quote that sparked something.
That file is never empty. And that means I am never empty, either.
I may be tired. I may not feel ready. But I always have a thread to pull on.

In a recent meeting with my friend Matthew, I showed him that file. He asked if I had ever given a talk about it. Turns out, I had. Back in 2019, I gave an internal talk at Improving on how I come up with talks. That, too, had started as a note in that file.
Over time, this habit has become one of my most valuable creative tools. When I feel resistance to writing or creating, I return to something I planted months or even years ago. It might not bloom right away. But it gives me a place to start.
If you want to write more—or speak more, or reflect more—start capturing those seeds.
Don’t wait for the perfect idea or the perfect time. Just write down what stirred something in you.
One sentence is enough.
When it’s time to create, you won’t be starting from nothing. You’ll be picking up a thread you left for yourself.
Bonus Lessons from the Talk
That 2019 talk offered a few other key lessons that still hold up:
- Let the audience guide what to expand
Pay attention to the parts of a talk that get strong reactions or questions. They often deserve their own talks. - Don’t chase trends. Chase energy.
Your best talks come from topics you can’t shut up about—not what’s hot in a blog or magazine. - Start with ‘why’, not ‘what’
If you’re excited about why a topic matters, others will be too. If you’re not excited, wait. - Your past work is compost
Old blog posts, past talks, forum answers, even ideas that didn’t land—they all break down and feed new growth. - Record everything
Whether it’s journaling, audio, or video of talks, that record becomes raw material for future talks and writing.
No one ever really starts from zero.
You start from what you’ve lived, what you’ve noticed, what you’ve captured.
So start capturing.
