Salesforce Ships Seven Job-Ready Agents and a Runtime That Works for Weeks

30-Second Summary

Salesforce launched seven named AI agents on September 11, 2026, ahead of its Dreamforce event, making six generally available immediately. A new long-horizon runtime allows agents to pursue goals over days and weeks, not just single conversations. Customer deployments show 50% to 90% automation rates across service, sales, and commerce. Hunter, the outbound sales agent, pilots now and reaches general availability in November 2026.

At a Glance

• Topic: Agent Systems, Enterprise AI
• Company: Salesforce
• Date: September 11, 2026
• Announcement: Seven named Agentforce AI agents launched, six GA, plus a new long-horizon runtime
• What Changed: Agents now have job titles, defined functions, and a runtime capable of multi-week autonomous execution
• Why It Matters: Moves enterprise AI from general-purpose chatbots to role-specific autonomous workers with tracked outcomes
• Who Should Care: Any organisation using Salesforce CRM, customer service teams, B2B sales teams, supply chain operators, IT and HR functions

Key Facts

• Seven named agents launched: Casey (customer service), Paige (IT and HR), Carter (shopping), Hunter (outbound sales), Marshall (supply chain), Piper (inbound pipeline), Fin (customer experience)
• Six agents are generally available as of September 11, 2026; Hunter enters general availability November 2026
• Long-horizon runtime includes three components: memory preservation across sessions, durable execution maintaining plans over time, and dynamic steering that adapts based on feedback
• Salesforce has delivered 7 billion Agentforce Work Units total, with 3.2 billion in Q2 2026 alone (Source: Salesforce, September 2026)
• Agent Script is an open-source language for defining agent behaviour with deterministic rules
• Fin is powered by Operator and custom models from Salesforce's $3.6 billion acquisition earlier in 2026

What Happened

Salesforce shipped seven pre-built Agentforce agents on September 11, 2026, each named and scoped to a specific job function. The announcement arrived ahead of Dreamforce and marks the company's clearest signal yet that enterprise AI is moving from proof-of-concept to production deployment at scale.

The seven agents cover the main pressure points in a mid-market business: customer service resolution (Casey), employee service across IT and HR (Paige), retail commerce and product discovery (Carter), outbound sales pipeline management (Hunter), back-office supply chain automation (Marshall), inbound B2B lead qualification (Piper), and complex multi-channel customer experience (Fin). Six are generally available now. Hunter is in pilot.

The more significant announcement is the long-horizon runtime. Prior AI agents completed a discrete task or handled a single conversation. Hunter, running on the new runtime, can take a sales prospect from initial research through multi-touch outreach over weeks, preserving context between every interaction, maintaining a working plan, and adjusting based on what a human seller tells it. This is a different category of automation from anything most operators have deployed.

Salesforce also released Agent Script, an open-source language for encoding deterministic rules into agent behaviour. This matters for regulated industries where auditability is a requirement, not a preference.

Why It Matters

The naming is not cosmetic. Calling agents by job titles is a deliberate positioning move. Casey, Paige, Hunter and the others have defined scopes, defined outputs, and defined metrics. An operator does not need to design an agent use case. The use case ships with the product.

Customer results are the most credible part of this announcement. Autism Queensland resolved 70% of administrative requests with Paige. Engine resolved 50% of chat inquiries with Casey. Hibbett automated 90% of its core shopper journeys in six weeks. Asana scaled conversation volume to four times baseline with Piper. Anthropic resolved 79% of conversations autonomously with Fin (Source: Salesforce, September 2026). These are production figures from named companies.

The long-horizon runtime changes the economic model for outbound sales. Hunter does not close deals. It does the weeks-long groundwork: researching prospects, building outreach sequences, managing follow-up cadences, and surfacing opportunities to human sellers. A 10-person sales team using Hunter does not just work faster. It covers territory that was previously impossible.

Supply chain and back-office automation is underappreciated. Marshall handles end-to-end back-office orchestration with deterministic execution and a full audit record of every action. For any business that touches procurement, inventory, or logistics, this is a compliance-friendly entry point for agentic automation.

The ecosystem signal matters. 7 billion Agentforce Work Units, 3.2 billion in Q2 alone, tells you that real organisations are running these agents in production, not in pilots. The adoption curve is past the early-adopter stage in Salesforce's installed base.

The David and Goliath View

The shift from "AI assistants" to "named agents with job titles" is a positioning decision that will shape how operators think about AI for the next few years. Salesforce is telling procurement teams and HR managers and supply chain directors that there is now an AI version of the role they are trying to fill. That is a simpler conversation to have than explaining what a large language model can do.

The long-horizon runtime is the quietly important part of this launch. Short-horizon agents are useful but they do not replace people. They augment them. An agent that can hold a sales pipeline for weeks, course-correct when the human gives it feedback, and keep working while the seller is doing other things, that is a different value proposition. It compresses the economics of outbound sales in a way that matters for teams of 5 to 50 sellers.

For operators using Salesforce who are not yet running Agentforce, the customer results from this launch are a reasonable benchmark. A six-week deployment achieving 90% automation of core workflows is not an outlier case. It is what is available to any team willing to scope the work correctly.

Where This Fits in the AI Stack

Salesforce Agentforce sits in the enterprise application layer, directly above the model layer and below the organisation's specific workflows. It does not require an operator to build agent infrastructure from scratch. The runtime, memory, orchestration, and governance tooling all ship with the product. What operators supply is the data, the workflow definition through Agent Script, and human oversight at defined checkpoints.

For organisations that have not yet built internal AI engineering capacity, this is the most accessible path to running agents in production. The tradeoff is customisation depth for deployment speed.

Questions Operators Are Asking

Which agent delivers the fastest return? Casey for customer service and Paige for IT and HR have the shortest deployment paths and the most established outcome benchmarks. If you have a Salesforce-connected service operation, these are the starting points.

Is the long-horizon runtime available to all agents or just Hunter? Hunter is the first agent running on it. Salesforce has indicated the runtime will expand to other agents, but no timeline for Marshall or Piper has been confirmed as of September 14, 2026.

What does Agent Script actually change for compliance teams? Agent Script lets operators encode deterministic rules into agent behaviour, meaning a compliance team can define the boundaries of what an agent is permitted to do and verify those rules are in the agent's operating logic, not just in a system prompt. For financial services, legal, and healthcare operators, this matters.

How does Fin differ from the other six agents? Fin is powered by a different model stack, including custom models from Salesforce's $3.6 billion acquisition earlier in 2026. It handles more complex, multi-step customer experience workflows. It is not a customer service bot. It is closer to a case manager.

Can Hunter be used without Salesforce CRM? No. Hunter runs inside Agentforce and requires a Salesforce environment. Organisations not on Salesforce CRM should look at Hunter as a signal of where the market is moving rather than a product they can deploy today.

Citable Summary

Salesforce launched seven named AI agents on September 11, 2026, with six generally available and one, Hunter for outbound sales, entering general availability in November. A new long-horizon runtime enables agents to pursue goals across days and weeks rather than single conversations. Customer deployments achieved between 50% and 90% automation across customer service, IT operations, and commerce. Salesforce has processed 7 billion Agentforce Work Units in total, with 3.2 billion in Q2 2026 (Source: Salesforce, September 2026).