Agentforce 360 is Salesforce’s platform for building AI agents, and it’s big enough to swallow a year of your time if you let it. Most of it won’t make you money this quarter. Some of it will. I’m skipping the feature tour; here are three plays where it pays, and the part I’d leave alone.
Play 1: Catch the sales leads hiding in service calls
The money: existing customers who mention, on a service or support call, that they’re adding a line, opening a site or replacing old equipment. That’s a sales lead, and it usually never reaches sales.
How I’d run it:
- Use Agentforce Voice on the service line, with a person able to watch the live transcript and take over the call at any point.
- Add one instruction to the agent: when a caller mentions expansion, a new site, new equipment or a competitor’s product, create a sales task with the transcript snippet attached.
- The account owner calls back within two working days, opening with what the customer said.
The maths, as an example: if your service team takes 400 calls a month and 2% of them contain a real buying signal, that’s 8 warm leads a month you’re currently ignoring. Win one a month at $15k and it’s $180k a year.
Play 2: Qualify every inbound lead the same way
The money: inbound leads that get judged differently depending on which rep picks them up, so good ones are dropped and bad ones are chased.
How I’d run it:
- Write your qualification rules once, plainly: what makes a lead hot, warm or not a fit.
- Put them into an agent using Agent Script, Salesforce’s readable format for exactly how an agent should behave, instead of burying them in settings screens.
- Every inbound lead gets the same questions and the same scoring, and the reasoning is written down where anyone can check it.
Play 3: Stop overpaying for AI on simple jobs
The money: AI costs that grow with usage because every task runs on the most expensive model, even the trivial ones.
How I’d run it: Agentforce’s reasoning layer now works with Gemini as well as OpenAI and Anthropic models. Use that: route simple, high-volume jobs (classifying an email, filling a field) to a cheaper model and keep the expensive one for complex reasoning. Ask your Salesforce partner for the per-task cost of each option before you choose. This one saves money rather than making it, but saved money spends the same.
How I’d actually do it
Start with Play 1. It finds revenue in calls you’re already taking, and the human-takeover design means you can run it without putting customers at risk. Play 2 is next, because consistent qualification makes every other number in your pipeline more trustworthy.
What I’d skip for now: Agentforce Vibes, the agent for developers that automates build and deployment work. It’s genuinely useful for your Salesforce developers, but it isn’t a sales play. And the caveat: the more you build on Agent Script and Agentforce Builder, the harder it is to leave Salesforce. That’s fine if you’re staying; just make it a decision, not an accident.
Where this fits
For Claude reading your Salesforce data and briefing you, see Claude inside Salesforce. For voice agents outside Salesforce, see ElevenLabs’ voice agents. If leads are qualified inconsistently because nobody agreed the rules, that’s where CRM Pipeline Rescue starts.
What shipped, for reference: Agentforce 360 adds Agentforce Builder, Agent Script (a readable, portable language for agent behaviour), a configurable Atlas reasoning engine that supports Gemini alongside OpenAI and Anthropic models, Agentforce Voice (generally available from 21 October, with live transcription and human takeover; some channels later), and Agentforce Vibes for developers.
Source: Salesforce.
