AI doesn't replace creative experts; it elevates their role. Their craft shifts from manually creating individual assets to designing and building robust, reusable AI systems that empower the entire organization to generate on-brand content.

Minimax builds both foundation models and user-facing applications in-house. This structure enables research and engineering teams to work side-by-side, getting direct feedback from internal developers to rapidly identify and address model weaknesses, ensuring models meet real-world needs.

Hanover Park’s organizational design has no product managers or designers. Instead, it embeds engineers directly with fund accountants—the domain experts. This creates a tight feedback loop that allows them to build a more informed and practical product much faster by aligning development directly with user needs.

Contrary to the belief that viral AI tools are driven by individual creators, Higgsfield's primary customer base is creative agencies. These agencies adopted the platform not as a threat, but as an opportunity to drastically increase efficiency, expand their service offerings, and capture new revenue streams from clients demanding AI-generated content.

Lovable employs a full-time "vibe coder," a non-engineer who is an expert at using AI tools to build functional product prototypes, templates, and internal applications. This new role collapses the idea-to-feedback loop, allowing teams to prototype and ship at unprecedented speeds without relying on engineering resources for initial builds.

BuzzFeed is using AI-powered toolkits that allow creative staff, like writers, to design and launch interactive products such as games. This dramatically increases the speed and volume of new product experimentation without relying on traditional engineering resources.

By embedding product teams directly within the research organization, Google creates a tight feedback loop. Instead of receiving models "over the wall," product and research teams co-develop them, aligning technical capabilities with customer needs from the start.

Products like video generator Flow and research tool NotebookLM are not built in a vacuum. Google Labs actively seeks input from creatives like filmmakers and authors to shape experimental AI tools, ensuring they solve real-world problems for non-technical users from the start.

Top product managers view designing with AI as a holistic process. Instead of focusing solely on prompt engineering, they consider the entire workflow: understanding constraints, leveraging different AI tools for specific tasks, and maintaining human oversight to ensure quality and empathy.