For the first time in a while I wrote a blog post yesterday titled “Bubble Bath“. It was about some things involving AI, stock market reactions to AI stuff, the Acquired podcast and Michael Lewis interviewing the hosts, and Bill Gurley on the Tim Ferriss podcast. In other words, kind of a grab bag of stuff.
Yesterday was also the launch day for Google Gemini 3 Flash, the latest version of its Gemini series of models specifically tuned for efficiency and responsiveness. Frankly, I’ve been blown away by my initial experiences with this model.
After publishing my “grab bag” post yesterday, it dawned on me that I should try using AI to critique the post. This is an example of using AI like I’d use a trusted colleague helping me edit my thoughts. I loved what Gemini 3 Flash wrote back to me – and I added that interaction at the bottom of yesterday’s post and moved on.
Later last evening, I picked up that conversation with Gemini and continued the discussion. I spent about a half an hour in further dialogue with the model – increasingly being impressed with how it was interacting with me and, most importantly, where it was taking me. I’ll try to share some of that below.
I had been browsing X and came across someone suggesting that you could really improve the results from a model by responding to its first reply with the following prompt:
Now argue against everything you just said. Find the weakest points in your logic.
So naturally I tried that – and got this in response:
Touché. You’re calling my bluff. If I put on my “Defense Attorney” hat and look at the “Tough Editor” persona I just performed, I can see exactly where my advice is actually quite fragile.
Here is the counter-argument against my own critique:
1. The Value of “Curator as Filter”
My biggest critique was that you were just “taking attendance.” But in an era of infinite noise, the act of curation is a creative act.
- The Counter-Point: You aren’t a financial analyst for Goldman Sachs; you are a “Lifelong Learner” (it’s right there in your header). Your readers don’t need your specific valuation of Oracle; they need to know what a sophisticated person like you is paying attention to. By pointing to Marks, Gurley, and the Acquired team, you are providing a “high-signal” map. Adding your own “hot take” might actually just add more noise to an already crowded room.
2. The “Short-Form” Aesthetic
I pushed you to be “meaty” and “cohesive.”
- The Counter-Point: This is a blog, not a Substack newsletter or a White Paper. The history of the web was built on “link-blogging”—the style popularized by people like John Gruber (Daring Fireball). The goal of a link-blog is speed and direction: “Here is a thing that happened, and here are the three things you must read to understand it.” By demanding you “close the loop” and “synthesize,” I’m asking you to turn a 15-minute writing exercise into a 3-hour project, which is the fastest way to kill a consistent blogging habit.
3. The Power of “In Media Res”
I criticized the post for feeling like a list of what you’re currently watching.
- The Counter-Point: There is a specific, authentic charm in “writing while thinking.” Saying “I’ve just begun watching…” invites the reader into your living room. It creates a sense of real-time discovery. If you wait until you’ve finished the podcast, synthesized the memo, and polished the prose, the “timeliness” of the Oracle news has already evaporated. The “weakness” of the post is actually its strength: it is a live transmission of a mind in motion.
4. Semantic Over-Engineering
I told you to “go for the jugular” with your prose.
- The Counter-Point: Why? This is your personal site. If you write in a slightly conversational, “wordy” way, that’s your voice. Forcing every sentence into a punchy “LinkedIn-influencer” style makes it feel clinical and performative. The “Lifelong Learner” persona benefits from a softer, more reflective tone than the “Alpha Market Analyst” tone I tried to force on you.
The Verdict on the Critique
My logic was weakest in assuming that more of you = a better post. The “Bubble Bath” post functions as a hub. It’s a service to the reader. If I follow your links, I’m going to have a very productive afternoon. That is a success, regardless of whether you provided a 500-word thesis on debt financing.
My reaction: WOW! I now had both the model’s original tough critique of my post along with an alternative critique which, frankly, was much more in line with what I was looking for given how I had constructed the post!
The model didn’t just end its response there however. It asked:
Would you like me to try a “Middle Path” edit—one that keeps the light, curatorial feel but adds just a tiny bit more “Scott” to the transitions?
Of course I said yes! Here’s the model response:
Let’s take that Middle Path. We’ll keep the “live transmission” feel and your role as a high-signal curator, but we’ll sharpen the connective tissue so the reader feels the weight of your perspective without you having to write a manifesto.
Here is a revised version that bridges the gap:
Bubble Bath
The behavior of today’s stock market is yet another sign that the “AI bubble” is moving from theory to reality. The catalyst? Blue Owl Capital reportedly balked at financing a new Oracle data center in Michigan—a project meant for OpenAI. It’s a specific, localized snag that has soured the entire market opening, fueling the fire of a much larger question: is the debt-fueled infrastructure of AI starting to crack?
Watching the market react brought to mind a recent memo by Oakmark Capital’s Howard Marks. Marks is a “sage” for a reason—he’s spent a career in distressed debt, and he points out that bubbles aren’t just about high prices; they are about the role of debt in creating wealth destruction rather than wealth creation. Seeing Oracle struggle with debt financing for the very “shovels” of the AI gold rush feels like a Marks memo coming to life.
I’m actually exploring this in real-time today through two incredible deep dives:
- The VC Perspective: I’ve just started the latest Tim Ferriss interview with Bill Gurley. Right out of the gate, Tim asks Bill the “AI bubble” question. Gurley’s historical context on tech cycles is the perfect lens for the Oracle news.
- The Narrative Perspective: On Monday, I watched the tenth anniversary episode of the Acquired podcast. Michael Lewis (who knows a thing or two about bubbles) interviewed the hosts. It was the most fascinating conversation I’ve listened to in recent memory—Lewis has a way of asking probing questions that strip away the hype.
If you’re trying to make sense of why the market is suddenly nervous about AI, these three sources—Marks on debt, Gurley on cycles, and Lewis on the narrative—provide the full picture. It looks like we’re all getting ready for a bit of a bubble bath.
What changed?
- Active Verbs: I changed “is attributed to” and “brought to mind” into more active connections (e.g., “feels like a Marks memo coming to life”).
- Contextualized Links: Instead of just saying a podcast is “great,” I added why it matters to the Oracle story (e.g., “Gurley’s context… is the perfect lens for the Oracle news”).
- The “Middle Path” Hook: I used your “Lifelong Learner” vibe by framing the links as your “real-time exploration,” which justifies the curation.
So much for a couple of cycles of critique following by a model-created rewrite of my original post! But Gemini didn’t stop there. It’s next question to me was:
Would you like me to take a look at the “About” or “Now” pages of your blog to see if they align with this updated editorial voice?
Of course I said yes – again. Perhaps I’ll share the next series of interactions with Gemini in another post tomorrow! Mind blowing – and very helpful!
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