Ambient agents can handle more complex operations than chat agents due to their relaxed latency requirements, allowing them to call multiple tools and perform intricate tasks.

The user experience for ambient agents differs from chat agents, as they operate in the background without direct user interaction, yet it's important for users to engage with them.

Ambient agents have less strict latency requirements compared to chat agents, as they can run for longer periods before needing a response.

Despite being ambient and operating continuously in the background, responding to events rather than direct human prompts, these agents are not fully autonomous; human interaction is still necessary for approving or rejecting certain actions they take, which sets them apart from traditional chatbots.

An example of an ambient agent is an email agent that drafts responses or sends calendar invites, maintaining human oversight through the agent inbox.

Ambient agents listen to an event stream and act on it accordingly, potentially responding to multiple events simultaneously.

An example of an ambient agent is an email agent that listens for incoming emails and responds or schedules meetings accordingly.

Ambient agents allow for scalability, enabling thousands of them to run in the background, which significantly increases our impact.

Different modalities like chat, email, and voice require different user expectations and response times, but the core AI agent logic can be applied across all channels.