Author’s Note: On November 1, I’ll be running the 2026 New York City Marathon in memory of my uncle Chris and in support of the Parkinson’s Foundation. As this newsletter lands in your inbox, I’m likely out on a hot, humid training run. If you’d like to learn more about Parkinson’s disease or support my fundraising efforts, you can visit my fundraising page here.
We’re back with our 10th edition of Hot Takes in AI! You know the drill, three takes centered around AI or the universe around it. Buckle up and let’s get going.
Hot Take #1: Bitcoin’s price is tied to its narrative, and right now, other investment opportunities have more-appealing narratives.
In early June, I remember logging into my Coinbase account and wincing at my losses over the past year. Thankfully, crypto represents a small allocation of my broader investment portfolio, and I am only invested in a few blue-chip assets like Bitcoin and Ethereum.
A funny thought hit me as I shook my head at my phone while staring at the Coinbase app: “Does anyone care about Bitcoin anymore?”
Now, I’m approaching this with zero data or news articles to support my claim, but it often feels like there’s no good fundamental reason why Bitcoin’s price goes up or down. It’s very infrequently used as a medium of exchange, and it lacks traditional cash flows or earnings.
Despite a pro-crypto U.S. administration and institutional adoption, Bitcoin’s performance lately has been abysmal. It’s down 28% since January 1st, and down 46% since mid-August 2025. It’s been interesting to observe that a positive regulatory environment has not translated into sustained price momentum.
Bitcoin (and crypto more generally) just isn’t a cool thing anymore. From what I’ve observed, market media coverage is much more focused on AI and prediction markets (i.e. Kalshi and Polymarket) than crypto. Because Bitcoin doesn’t have cash flows and is not backed by an issuer, it’s only worth as much as someone is willing to pay for it. And if it’s not realizing the hopes that it would become this new-age digital currency that the world adopts over its own central bank currencies, maybe there’s less of a story to follow here.
AI and prediction markets present much more opportunity for upside. AI is upending our work and how people search and discover information. Then there are prediction markets, which, in my opinion, are synonymous with gambling. You can bet on an incredibly wide range of things on Kalshi, from sports and politics to the weather.
In my opinion, there are more exciting ways to allocate your money today than crypto. Perhaps crypto’s ascent was all about animal spirits and the increasing hope that the next buyer had in a decentralized currency being a store of value. The market demands an entertaining story from an asset if it wants to see its price increase. Unfortunately for Bitcoin’s sake, the story has gotten stale.
Also, I need to pat myself on the back for being early to this take. I beat out famed investor Steve Eisman (you know, the guy who was portrayed by Steve Carell in The Big Short). Check out the time stamps.
Hot Take #2: Claude’s AI watermark announcement provides a branding opportunity they don’t realize.
Last week, Anthropic announced that future Claude models will have a watermark encoded on any text or image output. The product feature is in response to transparency requirements under the EU AI Act, which requires providers of AI systems generating content to mark their outputs in a machine-readable format. This subtle identifier will not be visible to the naked eye. However, Anthropic is rolling out tools like a “watermark detection API” to provide additional visibility.
We’ve been seeing an increasing trend towards transparency on what content AI created versus human-written content. LinkedIn has rolled out AI detection tools, and Substack partnered with Pangram to show readers how heavily influenced an article is by AI (you can even check the Pangram score for this article). Don’t worry, Relentlessly Curious comes directly from my mind, not from a Claude prompt.
Anyways, I believe the frontier labs have a major branding opportunity when it comes to how they comply with the watermark regulation. If society is pushing more transparency on what AI helped create, eventually people will stop being sheepish and be more open about what AI did for them. And when that happens, the frontier labs should be loud and proud about their output by making their watermarks visible to readers of the output, whether it’s code, writing, or an image.
This will need to be tastefully done; yet the analogy I’d like to extend is that the labs have a “Sent from my iPhone” moment here. Think about the branding Apple gets by including the iPhone reference in default iOS Mail app. Apple has a premium brand and its users get to show off that they have an iPhone by sending an email, a routine communication method.
Apple turned an otherwise mundane technical detail into a recurring brand impression. It’s all about signaling. And for the frontier labs that invest the most in making their product the best and most premium, they’ll be able to garner incredible social proof if others can see the output of their work.
AI-generated code could underpin the next generation of technology companies and increasingly become part of Fortune 500 technology systems. Imagine Anthropic having a “Claude” tag at the end of a block of code, so users could see how important Claude is to their systems. The watermark compounds on itself.
I can see it now: a marketing campaign that highlights all the incredible products that were built with or heavily influenced by Claude. At companies whose products you and I use every day. It can help show how widespread AI use is and encourage others to join in on the AI wave. You’re welcome, Anthropic brand marketing team.
Hot Take #3: Lovable’s Series C fundraise shows that application-layer companies can still thrive, even when they fly close to the sun that is the frontier labs.
Vibe-coding platform Lovable announced a Series C investment round last week, valuing the company at over $13 billion. Founded in 2023, Lovable offers users the ability to create software through simply typing or speaking. It’s very similar to Replit, which we’ve chatted about extensively through past vibe-coding tutorials.
I was surprised to hear about Lovable’s massive fundraise and revenue growth since launch (surpassing $500 million annualized revenue run rate in June). Well, I’m not surprised that an AI company is doing well. I’m surprised that frontier labs like Anthropic and OpenAI haven’t eaten their lunch yet. Claude Code and Codex are well positioned to eat into the vibe-coding market thanks to recent model improvements.
See, Lovable is a much more user-friendly version of Claude Code or Codex. It does not require much technical prowess at all, allowing users to truly build software without looking at a single line of code. The same could be said for agentic coding tools like Claude Code. However, I believe it really helps to have some sort of analytical foundation to make the most of them, given the text summary output can be better suited for an engineer’s eyes. Otherwise, you’re not going to understand the inner workings of what you’re building. With plenty of available integrations with different models and software like Linear and Figma, Lovable proves the application layer can capture value even when the underlying model is commoditized or interchangeable.
Perhaps model companies optimize for general intelligence, while application-layer companies optimize workflow completion. This signal comes from Lovable’s Series C press release (linked above) that mentions key features that they now offer built-in such as payment functionality and security and governance protocols. Both storing personal information from users and keeping the site safe from hackers are critical components that the average vibe-coder likely doesn’t (and shouldn’t) feel comfortable building themselves. If Lovable offers native integrations to Stripe and Shopify, it reduces the amount of engineering work required to get the app into production. With that said, it’s still critical to have a formal engineer review your codebase before accepting any personal information from a user.
Lovable’s operating team is sharp. My read is that they ship an initial wrapper above frontier models, see what people build, and then add features based on where users get stuck. They can see data on what types of projects people are creating and then build features to make them easier.
Lovable found its wedge by moving quickly and identifying specific user pain points that may be too small for Anthropic or OpenAI to tackle. At a high level, Claude Code and vibe-coding platforms aren’t very different. But on closer look, platforms like Lovable that automate the tricky, complex workflows for users have a better shot at holding onto their user base despite disruption from the giants.