Asad & Chris on adaptive products enabled by AI

Intro: the impact of LLMs on software development and product creation.

Example: building a personal tool to cluster, rank, and summarize email newsletters and content.

Exploring the benefits and drawbacks of using LLMs for tasks like clustering.

The shift from writing software to using general-purpose embedded LLMs for product development.

LLMs understand intent better than traditional systems, enabling personalized feeds and experiences.

Two tracks of AI integration: replacing traditional ML tasks with prompts and creating adaptive products.

The potential of marketplaces for user-created feeds and algorithms, empowering user control.

User choice in algorithms and the possibility of user-built feeds as the holy grail of engagement.

The complexity of adaptive products and the role of power users in creating experiences for others.

How product managers should adapt to the changing paradigm of AI-driven product development.

The trade-offs of using LLMs and the thought experiment of moving core systems to LLM-based approaches.

The disruption of traditional ranking systems and the ability to have good ranking from day zero with LLMs.

The advantage of infinite classifiers on day zero and the power of user choice in product design.