AI agent platforms are powerful but operate in a single-player mode. The key to viral growth is introducing multiplayer functionality, allowing teams to bring their specialized agents into a shared environment. This turns a productivity tool into a collaborative platform with powerful network effects.

As AI and better tools commoditize software creation, traditional technology moats are shrinking. The new defensible advantages are forms of liquidity: aggregated data, marketplace activity, or social interactions. These network effects are harder for competitors to replicate than code or features.

As AI accelerates technological progress and shortens relevance cycles, traditional tech moats become less defensible. However, network effects—especially in complex, fragmented marketplaces—remain a powerful and durable advantage. An AI agent cannot be simply prompted to "create a network effect."

The threat of AI models replicating SaaS features is real. Superhuman's defense isn't a superior core technology but a platform strategy. The bet is that users won't build their own tools if the platform offers a powerful network effect of pre-built, integrated agents that work everywhere, creating a defensible ecosystem.

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.

Asana's CEO argues its key differentiator is a "multiplayer mode" where entire human teams can collaboratively train and correct an AI agent within a project. This contrasts with typical one-on-one chat interactions, creating a unique, compounding learning environment for the agent that Asana believes cannot be easily replicated.

To build a moat against large language models like ChatGPT, focus on features they will never prioritize. Build multiplayer functionality, a strong user community, and human-in-the-loop support services around the core AI. These layers create defensibility that a generic interface cannot replicate.

The next wave of AI agents is moving beyond individual use ('single-player mode') to exist within shared team spaces like Slack channels. Tools like Claude Tag embed agents with full team context, transforming them from personal tools into collaborative resources that better mirror how organizational work actually happens.

By adding group chat functionality, OpenAI is turning ChatGPT from a solitary utility into a collaborative social platform. This strategic move aims to build a network-effect moat, increasing user retention and defending against competitors like Meta AI before they can gain traction in the market.