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sales-coach-agent-rollout

Use when an admin or RevOps team is rolling out the out-of-the-box Sales Coach agent (the Agentforce template that role-plays opportunity-stage conversations with reps for Discovery, Needs Analysis, Qualification, Proposal/Pricing, and Negotiation/Review).

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Sales Coach Agent Rollout

Activate this skill when an admin, enablement lead, or RevOps team is rolling out the Sales Coach agent — the Agentforce out-of-the-box template that role-plays opportunity-stage conversations with sellers and gives stage-appropriate feedback. The skill is about deployment, configuration, and adoption of the template, not about building a bespoke coaching agent from scratch.

Note on naming: depending on doc vintage and licensing pack, this template is referenced as Sales Coach, Agentforce Sales Coach, or Einstein Sales Coach. Treat the names as interchangeable for this skill — the underlying template is the same.

Terminology. Agentforce topics were renamed subagents in April 2026. This skill leads with subagent. The older term still appears in metadata and API names, in older Help articles, and in many orgs; nothing about behaviour changed with the rename.

Before Starting

Gather this context before configuring anything:

Core Concepts

Concept 1 — What Sales Coach actually is

Sales Coach is a packaged Agentforce agent template — a pre-defined agent with subagents, actions, and instructions tuned to opportunity-stage selling. It does three things, layered:

  1. Role-plays a buyer. A rep asks for practice on a specific stage; the coach plays the buyer side of the conversation, reacting to the rep's pitch with realistic objections, push-back, and follow-up questions.
  2. Critiques the rep's approach. After or during the role-play, the coach evaluates the rep's responses against the configured methodology — did they discover pain, qualify budget, handle the objection, surface a value prop?
  3. References Opportunity context. When invoked from an Opportunity record, the coach reads the record (stage, amount, contacts, products) and tailors the role-play to that deal — buyer persona implied by Account Industry, objections likely for the product, etc.

What it is not: a real-time call coach (that is a separate Einstein Conversation Insights product), a deal-review summarizer (that's Sales Cloud Einstein Opportunity Insights), or an autonomous deal-progressor. It only acts when a rep starts a conversation with it.

Concept 2 — Stage configuration: which prompts activate on which stage

Sales Coach ships with five stage personas mapped to the standard Opportunity stages. The mapping is enforced via subagent instructions inside the agent — not via a hard-coded SOQL filter — which means stage names labels matter.

Standard stageCoached behaviors
Prospecting / QualificationCold-outreach role-play, BANT/MEDDIC qualification questioning, ICP fit-checking
DiscoveryOpen-question framing, pain identification, decision-criteria extraction
Needs AnalysisStakeholder mapping, technical-fit probing, evaluation-process clarification
Proposal / Price QuoteValue-prop articulation, pricing objection rehearsal, ROI framing
Negotiation / ReviewConcession strategy, mutual close plan, redline / legal handoff

Two patterns matter for activation:

Concept 3 — Customizing role-play scenarios

The shipped role-play prompts are deliberately generic. A rollout that stops at "default + publish" produces a coach that sounds like a B-school case study — directionally right, never actually relevant. Three customization points matter:

  1. Industry and persona seeds. In Agent Builder, the subagent instructions for each stage allow free-text additions like "When playing the buyer persona, default to a {Industry} {Title} archetype with {top 3 priorities}." Inject your ICP segments here. This is the highest-leverage customization — it transforms generic coaching into "you're now selling to a CISO at a 5,000-employee health system."
  2. Objection library. The coach generates objections from the LLM's general knowledge, augmented by grounded knowledge sources. If your sellers face specific objections ("why your platform vs incumbent X", "the data residency question", "ROI for the SMB tier is hard to justify"), put them in a Knowledge article tagged for Agent grounding. The coach will then surface them during role-play.
  3. Value-prop and proof-point grounding. Same mechanism — a Knowledge article enumerating your three top value props, key proof points, and competitive battle cards is the substrate for the coach's critique behavior. Without it, "did the rep handle the value prop well?" defaults to LLM generality.

The general rule: every customization belongs in grounded data (knowledge articles, Data Cloud objects), not in agent instructions. Agent instructions describe behavior; data describes the world. Don't stuff your battle cards into the agent's system prompt — they'll go stale and you can't version them.

Concept 4 — Measurement: leading and lagging indicators

A Sales Coach rollout without a measurement plan is theater. Two layers:

Common analytical mistake: comparing coached-opp win rate to global win rate. Reps who choose to use the coach are not random — they self-select for engagement and effort, biasing upward. Always compare within a segment (region, quota tier, product) and ideally use a randomized opt-in cohort.

  1. Verify prerequisites. Confirm Agentforce SKU, Einstein Generative AI activation, Trust Layer settings, and Opportunity stage hygiene. Run the bundled scripts/check_sales_coach_agent_rollout.py against retrieved metadata to detect: missing agent definition, opportunity-stage drift from standard, absent grounded knowledge sources tagged for Sales Coach.
  2. Ground the methodology. Locate or author the canonical methodology document (MEDDIC, BANT, Challenger, custom). Publish as a Knowledge article with the data-classification + Agent-accessible flag set. Without this, customization is shallow.
  3. Customize stage prompts in Agent Builder. Open the Sales Coach template, walk each of the five stage subagents, and inject ICP seeds, industry archetypes, and references to grounded knowledge. Do not paste battle cards directly into instructions — reference grounded sources.
  4. Configure the embed surface. Decide between (a) embedding in the Lightning sales console as a utility item / Einstein panel, (b) embedding on the Opportunity record page as a component, or (c) launching a separate /agentforce portal. Console embedding has the highest engagement; portal isolates legal exposure if you're nervous. Pick one for the pilot — don't do all three.
  5. Run a privacy review. Document what data flows to the LLM (Opportunity fields read by the agent's actions, rep's typed input), what is logged (Agentforce session logs in Setup → Einstein), and retention defaults. Get sign-off from legal/compliance before publishing to production. For EU tenants confirm Einstein Trust Layer EU data-residency settings are honored.
  6. Pilot with the chosen cohort. Publish to a subset of users via permission set. Communicate the purpose (practice tool, not a deal-tracking tool, no manager surveillance), the measurement plan, and the feedback loop (where reps report bad coaching). Run 4 weeks before expanding.
  7. Re-measure and iterate. At week 4, re-run the checker, pull engagement analytics, and gather rep feedback. Tune objection library and ICP seeds based on what reps say felt off. At week 8–12, evaluate lagging indicators and decide expand / hold / sunset.

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