---
schema_version: "newruntime-agent-readable-v0.1"
type: "post"
slug: "sierra-horizon-long-running-agent"
title: "Sierra Horizon Makes Long-Running Agents Look Like State Machines"
description: "Sierra Horizon shows that a long-running customer agent should be a state machine with signals, playbooks, suppression rules, and terminal outcomes, not a long chat."
status: "published"
published_at: "2026-07-22"
topics: []
source_urls: ["https://sierra.ai/blog/horizon"]
routes: {"html":"https://newruntime.com/posts/sierra-horizon-long-running-agent/","markdown":"https://newruntime.com/posts/sierra-horizon-long-running-agent.md","json":"https://newruntime.com/posts/sierra-horizon-long-running-agent.json"}
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# Sierra Horizon Makes Long-Running Agents Look Like State Machines

Sierra Horizon is useful as a more mature form of long-running agent. It is not a "chat that lasts for weeks", but a state machine around the customer journey.

The agent works with signals, playbooks, suppression rules, and a measurable terminal state. It can move a customer toward a mortgage, renewal, or sale through calls, email, messages, and internal systems. The important detail: payment is tied to the outcome.

This kind of agent requires a different operating model. It needs states, prohibitions, events, escalation routes, measurable outcomes, and protection against unnecessary customer touches.

Editorial read: a long-running agent becomes a product only when it has a terminal state and a business outcome, not merely a long message history.