A custom AI tool offers more value than a generic one like ChatGPT because it can be trained on a brand's unique, paywalled intellectual property. This creates a curated experience that aligns perfectly with your teachings and provides answers that cannot be found for free on the web, solidifying your expertise.

The key for enterprises isn't integrating general AI like ChatGPT but creating "proprietary intelligence." This involves fine-tuning smaller, custom models on their unique internal data and workflows, creating a competitive moat that off-the-shelf solutions cannot replicate.

WCM avoids generic AI use cases. Instead, they've built a "research partner" AI model specifically tuned to codify and diagnose their core concepts of "moat trajectory" and "culture." This allows them to amplify their unique edge by systematically flagging changes across a vast universe of data, rather than just automating simple tasks.

Code-hosting platform Base44 launched its own fine-tuned model, Base1, not just to compete on performance but to control costs, latency, and reliability. This strategy leverages proprietary user data to create a defensible advantage that general-purpose frontier models cannot easily replicate, offering a playbook for other vertical platforms.

Despite the hype around AI customer support startups, large enterprises often find their products don't work. Companies like Wix end up building their own solutions because they have the scale, complexity, and specialized engineering talent to create a superior, custom product.

Create a competitive advantage by developing a unique AI model trained on your brand and customer data. Feed it everything—reviews, Reddit posts, positive and negative feedback—to build a deep understanding that can be leveraged for content creation, with a human editor as the final check.

RAMP built its AI platform in-house because they view internal productivity as a competitive moat. Owning the tool allows them to move faster, deeply understand user pain points, and leverage internal learnings to inform their external customer-facing products.

The value of AI-native builders like Wix's Base44 isn't just the AI model, which is often a third party. It's the seamless integration of backend infrastructure—hosting, databases, authentication—that eliminates significant technical friction for non-developers, making it more than a simple "wrapper."

By training a smaller, specialized model where company data is in the weights, firms avoid the high token costs of repeatedly feeding context to large frontier models. This makes complex, data-intensive workflows significantly cheaper and faster.