The next major evolution in AI will be models that are personalized for specific users or companies and update their knowledge daily from interactions. This contrasts with current monolithic models like ChatGPT, which are static and must store irrelevant information for every user.

While current AI tools focus on individual productivity (e.g., coding faster), the real breakthrough will come from systems that improve organizational productivity. The next wave of AI will focus on how large teams of humans and AI agents coordinate on complex projects, a fundamentally different challenge than simply making one person faster.

Ilya Sutskever argues the 'age of scaling' is ending. Further progress towards AGI won't come from just making current models bigger. The new frontier is fundamental research to discover novel paradigms and bend the scaling curve, a strategy his company SSI is pursuing.

Broad improvements in AI's general reasoning are plateauing due to data saturation. The next major phase is vertical specialization. We will see an "explosion" of different models becoming superhuman in highly specific domains like chemistry or physics, rather than one model getting slightly better at everything.

While language models are becoming incrementally better at conversation, the next significant leap in AI is defined by multimodal understanding and the ability to perform tasks, such as navigating websites. This shift from conversational prowess to agentic action marks the new frontier for a true "step change" in AI capabilities.

Moving beyond isolated AI agents requires a framework mirroring human collaboration. This involves agents establishing common goals (shared intent), building a collective knowledge base (shared knowledge), and creating novel solutions together (shared innovation).

The next frontier for AI isn't just personal assistants but "teammates" that understand an entire team's dynamics, projects, and shared data. This shifts the focus from single-user interactions to collaborative intelligence by building a knowledge graph connecting people and their work.

The next leap in AI will come from integrating general-purpose reasoning models with specialized models for domains like biology or robotics. This fusion, creating a "single unified intelligence" across modalities, is the base case for achieving superintelligence.

Block's CTO believes the key to building complex applications with AI isn't a single, powerful model. Instead, he predicts a future of "swarm intelligence"—where hundreds of smaller, cheaper, open-source agents work collaboratively, with their collective capability surpassing any individual large model.