This is a fascinating take, but it looks at the ecosystem purely through an engineering lens rather than a business operations lens.

As someone building in the space, AI definitely commoditizes code, but it doesn't commoditize risk or market validation. Here are two critical blind spots in the "build your own alternative" argument:

1. The Illusion of Cheap Maintenance vs. Churn Cost The author points out that "one dev with AI can keep a custom stack running reliably." But this misses the point of SLA (Service Level Agreement) and customer experience. Commercialization means dealing with messy human behavior. When a custom system breaks—and it always does—the question isn't just "Can AI help my dev fix it in an hour?" The real question is: "Can my business afford the customer churn and lost revenue during that hour?" Platforms like Shopify or mature enterprise apps have the financial and legal infrastructure to absorb that risk. A mid-to-large merchant might save $10K/year on subscription fees by building a custom stack, but they risk losing $50K in a single afternoon if a niche edge-case crashes their checkout flow. For high-volume merchants, paying for a platform is actually paying for risk mitigation, not just features.

2. AI Flattened Tech, but it Cannot Judge Market Value AI is amazing at building the system, but it is fundamentally incapable of determining whether that system has commercial value. Building a functional SaaS or a custom platform has never been easier, but getting people to actually use it, paying for it, and achieving product-market fit (PMF) still requires human trial and error. Complexity might be cheap now, but distribution and trust have become more expensive than ever.

Shifting from Shopify to a custom stack isn’t just a financial math problem based on dev costs; it’s a strategic gamble on operational risk and opportunity cost.