The challenge in AI is that while the underlying technology is evolving rapidly, it complicates product development because you have to predict where the tech will be in a year.

Incorporating AI into workflows presents challenges, particularly in building trust with users and ensuring that AI helps them progress rather than causing frustration.

In the AI era, many teams excel in technology but struggle with achieving product-market fit, often overlooking what users truly want.

Managing user expectations is challenging, especially when AI delivers results that may not fully meet their needs, necessitating manual features to enhance user experience.

When consumers encounter limitations with AI, it reveals opportunities for developers to create solutions that meet those needs.

AI companies need to articulate what's in it for the user and make a remarkable promise that they can keep, as AI will soon be seen as a standard feature rather than a unique selling point.

Ultimately, success in AI relies on the ability to effectively stitch together existing models into products that users genuinely love, rather than reinventing the wheel.

As AI capabilities grow, product teams can still add significant value by focusing on user experience, ethical considerations, and strategic direction.

The challenge in AI lies in balancing supply and demand; while we invest in building models, we must also focus on how to effectively utilize these models for economic and mission advantages.