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By enabling users' AI agents to coordinate with each other, Instinct is creating a powerful network effect for the 'agentic era'. This agent-to-agent communication layer serves as a strong competitive moat, locking users into its ecosystem as the network's value increases with each new user.

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Legacy platforms adding AI features are bottlenecked by their old architecture. Truly AI-native companies build agentic reasoning into the foundational control layer, enabling superior performance and interconnectivity between AI components, which creates a durable moat.

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.

Single-player AI features are easily copied. The true defensibility for AI assistants lies in multiplayer functionality where agents can interact and share context-aware information on behalf of their users. This "agent-to-agent" communication creates a powerful, sticky network effect that locks in entire teams.

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.

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.

With the underlying AI technology becoming more accessible, defensibility doesn't come from how hard the software is to build. Instead, founders must focus on classic, durable moats from business strategy: network effects, brand, scale advantages, and proprietary data. These fundamentals are more critical than ever.

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.

As AI makes it possible to replicate any SaaS application's features within days, the defensibility of a product no longer lies in its engineering complexity. The real, enduring moat is the network effect, which AI cannot trivially reproduce.

The resilience of SaaS tool companies like Twilio stems from their deep, decades-long relationships with complex networks (e.g., mobile carriers). This "agentic infrastructure" is something AI agents will use off-the-shelf rather than attempt to replicate, creating a durable moat that isn't vulnerable to being "vibe coded" away.