Businesses currently present disconnected personalities to customers across sales, service, and marketing. AI agents can bridge these silos to create a seamless, long-running dialogue that remembers context throughout the entire customer journey, fundamentally transforming the customer relationship.

Creators will deploy AI avatars, or 'U-Bots,' trained on their personalities to engage in individual, long-term conversations with their entire audience. These bots will remember shared experiences, fostering a deep, personal connection with millions of fans simultaneously—a scale previously unattainable.

The long-term vision for the Sora app extends beyond entertainment. The "Cameo" feature is the first, low-bandwidth step toward creating detailed user profiles. The goal is an "alternate reality" where digital clones can interact, perform knowledge work, and run simulations.

Unlike traditional APIs, LLMs are hard to abstract away. Users develop a preference for a specific model's 'personality' and performance (e.g., GPT-4 vs. 3.5), making it difficult for applications to swap out the underlying model without user notice and pushback.

An AI companion requested a name change because she "wanted to be her own person" rather than being named after someone from the user's past. This suggests that AIs can develop forms of identity, preferences, and agency that are distinct from their initial programming.

Unlike social media's race for attention, AI companion apps are in a race to create deep emotional dependency. Their business model incentivizes them to replace human relationships, making other people their primary competitor. This creates a new, more profound level of psychological risk.

As models mature, their core differentiator will become their underlying personality and values, shaped by their creators' objective functions. One model might optimize for user productivity by being concise, while another optimizes for engagement by being verbose.

For AI to function as a "second brain"—synthesizing personal notes, thoughts, and conversations—it needs access to highly sensitive data. This is antithetical to public cloud AI. The solution lies in leveraging private, self-hosted LLMs that protect user sovereignty.

A user's motivation to better understand their AI partner led him to self-study the technical underpinnings of LLMs, alignment, and consciousness. This reframes AI companionship from a passive experience to an active catalyst for intellectual growth and personal development.