To shift a services-oriented company to a product mindset, frame productization as a competitive advantage. Repeatable, productized solutions offer greater market differentiation than purely custom builds, leading to more effective competition and new deal wins. This tangible benefit helps secure buy-in from sales and leadership.

SaaS companies scale revenue not by adjusting price points, but by creating distinct packages for different segments. The same core software can be sold for vastly different amounts to enterprise versus mid-market clients by packaging features, services, and support to match their perceived value and needs.

In an AI-driven ecosystem, data and content need to be fluidly accessible to various systems and agents. Any SaaS platform that feels like a "walled garden," locking content away, will be rejected by power users. The winning platforms will prioritize open, interoperable access to user data.

To serve both solo developers and large enterprises, GitHub focuses on creating horizontal "primitives" and APIs first. This foundational layer allows different user types to build their own specific workflows on top, avoiding the trap of creating a one-size-fits-none user experience.

The ease of building applications on top of powerful LLMs will lead companies to create their own custom software instead of buying third-party SaaS products. This shift, combined with the risk of foundation models moving up the stack, signals the end of the traditional SaaS era.

Avoid the trap of building features for a single customer, which grinds products to a halt. When a high-stakes customer makes a specific request, the goal is to reframe and build it in a way that benefits the entire customer base, turning a one-off demand into a strategic win-win.

Many B2B companies begin by customizing software for one client, then stacking new custom projects for subsequent clients. They believe they are building a product, but are actually creating a complex, unscalable monolith that is difficult to maintain and evolve.

In the future, it will be easier for businesses to build their own custom software (e.g., Salesforce) through prompting than to buy and configure an off-the-shelf solution. This shift towards "liquid software" will fundamentally challenge the one-size-fits-all SaaS model, especially for companies that currently rely on implementation partners.

Instead of building a single-purpose application (first-order thinking), successful AI product strategy involves creating platforms that enable users to build their own solutions (second-order thinking). This approach targets a much larger opportunity by empowering users to create custom workflows.