Each week, I'll chat about the AI tools I'm exploring, share some fun experiments I'm conducting, and offer interesting insights into what I'm noticing in the world.

🔧 Three Tools I’m Testing

📺 Runway - A video generation tool that recently got an upgrade. I did not try the new model, v4, because I didn’t want to plop down a credit card. However, I was pretty impressed with the image to video. I don’t have a lot of video uses right now, so I won’t be taking it too far. You can check out my quick video here.

🖼️ Midjourney - I took the new v7 model from Midjourney for a spin, and the results were quite stunning. Image generation is improving so rapidly that it’s hard to imagine what twelve months from now will look like. The header image, robot, and colors for this post were all generated with Midjourney.

📦 Amazon Nova - I experimented with Amazon’s models briefly to explore their capabilities. They’re decent. Next, I plan to test Nova Act. I’m excited to build agents that excel at navigating and executing tasks in the browser.

🧪 AI Experiment of The Week

This week, I’m playing with Lovable to build out a small site for tracking AI prompts that I find useful. Hopefully, this will become a public resource for others at some point. I started with a very simple prompt:

A website to search, store, and view AI prompts. A person should be able to add to the collection of prompts and categorize them.

It went to work on refining the requirements and building out the first version of this site. The initial site build took Lovable roughly five minutes. You can see the work it is doing below, along with the first version of the site. It had to fix one single bug before the initial version worked.

The first version worked as expected. It allows you to view the prompts, add a new one, search them, and see the categories. For a quick draft, it’s precisely what I’m looking for. More to come on this application.

📰 Article of The Week

A thoughtful examination of the AI-generated Studio Ghibli style controversy sweeping social media.

Siegler dives deep into the thorny questions around AI mimicking established styles like Studio Ghibli's distinctive aesthetic. Can a style be copyrighted? In most cases, it seems apparent that you can't copyright a drawing or animation style—but where does that principle stop? He also raises questions about how these models were trained: Did they use copyrighted material without permission?

What makes this article particularly valuable is how it moves beyond the knee-jerk reaction ("AI is stealing from artists!") to foster a more constructive conversation. Rather than futilely trying to halt technological change, Siegler suggests artists engage in shaping fair compensation systems within this new paradigm.

The historical context is illuminating: we're witnessing another transformation in the relationship between human creativity and technological tools. From cameras disrupting painting to digital software revolutionizing music production, each new tool initially faced resistance before enabling entirely new forms of artistic expression. AI follows this pattern but at unprecedented speed and scale.

Siegler's ultimate point resonates strongly: this isn't about the end of art but potentially the dawn of a new age where human-created art might become even more valued precisely because of its human origin. The challenge isn't stopping AI art but ensuring the economic ecosystem properly values the human creativity that made such tools possible in the first place.

🌎 Where the World is Going

I'm fascinated by how AI is reshaping business models across industries. Like tectonic shifts throughout history, we're witnessing dramatic transformations and subtle evolutions in how companies monetize their offerings. When SaaS disrupted perpetual licenses, it wasn't just a pricing change—it fundamentally altered customer relationships, development cycles, and company valuations. Now, AI stands poised to trigger similar seismic shifts, though curiously, most AI companies still cling to subscription models, essentially pouring new technological wine into old business model bottles.

AI is bringing new opportunities for business models including everything from upcharging for AI capabilities to pay-for-results based on agents. Companies like Anthropic have introduced "reasoning" as a premium feature, while others like Adept AI are selling task completion rather than just model access. Even RunwayML isn't simply selling generation capabilities—they're creating marketplaces where creators can monetize their aesthetic through custom models. The primary cost remains token pricing from the models used or compute if you run your own.

What's particularly fascinating is the emergence of entirely new value layers. We're seeing authentication services like Originality.AI building businesses around verifying AI-generated content. Legal-focused companies like Harvey AI are developing vertical-specific applications with pricing tied to professional value rather than computational costs. These specialized approaches move beyond the simple "access to AI" subscription model toward more nuanced value propositions.

Perhaps the most revolutionary shift will come from AI agents that act as intermediaries between consumers and services. When your personal AI negotiates and purchases on your behalf, traditional marketing and customer acquisition models fundamentally change. As I position my own business for this shift, one thing is clear: tomorrow's winners won't just leverage AI—they'll invent entirely new economies around it.

👨‍💻 About Me

🔗 Extra Links to Check Out

• Apple is Creating AI Doctors 🩺

• Gemini 2.5 Pro is Available 🤖

• MCP is Being Adopted by OpenAI 👬

• Man Saved by AI Finding an Alternative Medicine 💊