The Local-First Advantage
Tools that run locally aren't just a privacy feature — they're a different product category with different adoption dynamics, different pricing, and a different relationship with the user.
Product-Design
The Niche Depth Tradeoff
Going narrow is uncomfortable. It feels like you're leaving users out. But the depth you can achieve in a specific domain is exactly what makes a tool worth paying for.
The Protocol as Product
Protocols are infrastructure. But the products built on top of them aren't all equal — and the ones that solve domain-specific problems tend to have the most durable advantage.
The Adoption Hurdle
The hardest part of selling tools that work with private data isn't building the product — it's clearing the trust threshold that sits between interest and usage.
The Pricing Floor
The workaround your users are already doing tells you the minimum viable price. It's right there in the math.
The Trust Gap
Between 'this product could solve my problem' and 'I'm going to pay for this product' sits a specific kind of distance. It's not about price.
The Spec That Ships
Most products have a spec. Few have a spec that anyone reads, agrees on, and actually builds from. The difference is smaller than it looks.
The External/Internal Divide
Two AI tools can solve the same problem completely differently depending on where their data lives. This distinction matters more than it looks.
The Switching Cost Asymmetry
Switching costs are usually thought of as a retention mechanism. They're also a signal about where value actually lives.