The better the AI models become, the more opportunities there are for startups to leverage these advancements. Startups need to be proactive in building their products in anticipation of new model releases rather than reacting to them.

As AI models improve, the expectation is that they will converge in quality and pricing, making it essential for startups to build software that leverages this intelligence effectively.

The asynchronous nature of AI interactions can significantly improve user experience, especially when models are readily accessible.

As AI becomes more effective, it will reduce execution friction for businesses, allowing them to focus on their core ideas and streamline operations.

Enterprises are now more focused on the value AI can deliver rather than the specific models or tools being used, seeking stable and reliable solutions.

Enterprises prioritize outcomes over the underlying AI models; they want effective solutions for customer support and workflow automation.

The more testing AI models undergo, the more reliable they become, similar to software development practices.

The more testing AI models undergo, the more reliable they become, similar to software development practices.

As AI models become more capable, they can handle nuanced issues better, allowing for more artistic freedom while maintaining responsibility.