Autonomous ramp plan adjustment (L5)

New hire ramp plans adjust themselves. The agent reads certification results, call scores, and pipeline creation, then reorders the next two weeks of ramp work. Managers approve exceptions and own the final readiness call.

WORKFLOW1Make ramp modularNotion2Feed real performance sig…alsGong3Let the agent reorder ins…de guardrailsAgentforce4Manager reviews weekly in…one screenSalesforce
4 steps, in order, with the tool that owns each one.
Adoption ladderSix levels from Starter to Rebuilt. This item sits at level 5.L1 StarterOne tool, no workflow changeL2 AssistedAI drafts, humans approveL3 IntegratedWired into CRM and SlackL4 OrchestratedMulti-step, owned, measuredL5 AutonomousAgent runs, human auditsL6 RebuiltThe process itself changes
This playbook belongs at L5 Autonomous. Running it above your level is how pilots stall.
Measures of successtime to first closed won; ramp module pass rate; manager override ratePROVE IT WORKEDtime to first closed wonramp module pass ratemanager override rate

The steps

  1. 01

    Make ramp modular

    Tool: Notion

    Break ramp into independent modules with a prerequisite map and a measurable exit test. An agent cannot reorder a monolithic 90 day plan. Owner: enablement. DoD: module map with exit tests published.

  2. 02

    Feed real performance signals

    Tool: Gong

    Certification scores, call rubric scores, and first pipeline created are the inputs. Activity counts are not. Reordering on activity teaches reps to game activity. Owner: RevOps. DoD: three performance signals wired with refresh cadence.

  3. 03

    Let the agent reorder inside guardrails

    Tool: Agentforce

    The agent may reorder, repeat, or add modules within the next fourteen days. It may not extend ramp, change quota, or alter the readiness date. Those stay human decisions. Pitfall: silent scope creep into performance management. DoD: guardrails written and enforced in config.

  4. 04

    Manager reviews weekly in one screen

    Tool: Salesforce

    One weekly view shows what the agent changed for each new hire and why. Managers override with a reason, and those reasons are the tuning data. Owner: hiring manager. DoD: override reasons captured and reviewed monthly.

Tools in this playbook

Next playbooks

Unfamiliar terms are defined in the AI and Revenue Dictionary. Related frameworks live in the framework library.

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