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Sales Ramp Enablement

Community
NEON-Rutger
sales-ramp-enablement

Design rep ramp as an instrumented system: milestone-gated 30-60-90 with certification evidence, ramp math wired into capacity and forecast, ramp-adjusted quota and comp, and a manager cadence that catches a drifting ramp in week three instead of month five. Triggers on 'ramp', 'ramp time', 'new rep onboarding', 'time to productivity', 'reps take too long to produce', 'certification', 'enablement program', 'sales onboarding plan', '30-60-90 for the new AE', 'ramp quota', or any hiring plan that treats the months between start date and full production as weather. BOUNDARY: assumes a playbook exists or names its absence as the first gap. Call scoring feeds certification evidence. gtm-compensation owns full comp design; this skill sets only ramp-period quota and draw. revops-org-chart owns hiring sequencing; the capacity math here feeds it.

Overview

PublisherNEON-Rutger
RepositoryB2B-revops-skills
Skill namesales-ramp-enablement
Stars
58
Forks
23
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by NEON-Rutger on GitHub. Read the source before you install it.

Installation

Install the Sales Ramp Enablement AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/NEON-Rutger/B2B-revops-skills/tree/main/sales-ramp-enablement
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/NEON-Rutger/B2B-revops-skills.git /tmp/B2B-revops-skills
mkdir -p .claude/skills
cp -r /tmp/B2B-revops-skills/sales-ramp-enablement .claude/skills/sales-ramp-enablement
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sales Ramp Enablement in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sales Ramp Enablement on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sales Ramp Enablement is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Sales Ramp and Enablement: Productivity by Design, Not by Osmosis

Ramp is the most expensive unmanaged period in a GTM budget. SDRs average around 3.1 months to productivity, from the one surveyed-methodology source in this space (The Bridge Group SDR Metrics, 2023). AE figures are softer: 2025-2026 industry compilations, published without unified methodology, put average AE ramp toward 5-6 months with enterprise motions far longer; trust the segmentation shape and the lengthening trend, not the exact numbers. Multiply the months by loaded cost and missed quota coverage and a single slow ramp costs more than the enablement program that would have prevented it. Yet most companies run ramp as scheduled exposure: a training week, a shadowing rotation, a quota that switches on at a date the calendar picked.

The core rule: ramp is graduated by evidence, not elapsed time. Every element below either defines the evidence or wires the consequences.

Ramp Math First

Before designing content, put ramp into the revenue model, because that is what makes the program a CFO conversation instead of an HR one:

  • Ramp cost per hire = months to full productivity x (loaded cost + quota coverage gap). Compute it for your last four hires; this number funds everything else in this skill.
  • Capacity planning uses ramped-equivalent reps, not headcount: a rep in month two of a five-month ramp is 0.4 of a rep in the coverage model. Annual plans that count heads instead of ramped-equivalents manufacture a pipeline gap and then blame the market (feed this into the bottoms-up capacity model in revops-forecasting).
  • Ramp-adjusted quota: stepped targets over the ramp arc with a draw or guarantee matched to the steps. A full quota on day one does not accelerate learning; it teaches new reps to chase bad deals, which your qualification gates then have to catch.

The Milestone Arc: Evidence-Gated 30-60-90

Default arc for a mid-market AE; compress or stretch by motion, keep the gate logic:

  • By 30, certified on the story: can run the first-call pitch and discovery to standard, scored against your call-scoring rubric on real or roleplay calls, not self-assessed. Knows the ICP, the top loss causes (pull them from the win-loss program, not folklore), and the qualification bar.
  • By 60, certified on the motion: running discovery on live at-bats with a manager or peer listening; first qualified opportunities created that survive the evidence gates. Leading indicators tracked from week one: time to first meeting booked, time to first qualified opportunity, activity quality scores.
  • By 90, producing with fading scaffold: owns deals through mid-funnel, first closed or near-closed outcome appropriate to cycle length, and the scaffold (shadowing, call reviews on every call) steps down on evidence.
  • Every gate has three outcomes: pass, targeted remediation with a named gap and a re-test date, or an honest early verdict. The most expensive ramp outcome is the rep who was never going to work, discovered at month nine; milestone gates exist to move that discovery to month two.

The structured-versus-unstructured gap is the one finding every source agrees on: teams with formal, milestone-based onboarding ramp materially faster than sink-or-swim (The Bridge Group, 2023; consistent across 2025-2026 aggregations). The exact multiplier varies by source; the direction never does.

Enablement as a System, Not a Binder

  • One home: playbook, call library, and assets live in a single place with an owner and an update cadence. If the playbook does not exist, that is gap zero; build it before designing week two (see the playbook-foundations boundary).
  • The call library is the curriculum: best-in-class recordings per stage, worst-call examples with commentary, and the new rep's own calls reviewed against them. Reps learn the standard from real calls, not slides.
  • Certification content comes from reality: the pitch to certify is the one your best calls actually run; the objections to drill are last quarter's top loss causes; the ICP to memorize is the scored one, not the aspirational one.
  • Measure enablement by ramp outcomes, not attendance: content completion is an input; time-to-first-qualified-opportunity by cohort is the scoreboard.

The Manager Cadence

Ramp fails silently without a manager rhythm: weekly 1:1 against the milestone plan (evidence reviewed, not feelings), two call reviews per week minimum through day 60, and a written monthly verdict (on track, remediation, or concern) that someone above the manager reads. A ramp plan without a manager cadence is a wish with milestones.

What Good Looks Like

The best ramp systems can show, for every cohort, the leading-indicator curve (first meeting, first qualified opp, first win) against the previous cohorts', and their certification gates have actually failed someone, kindly and early. The common failure is the celebratory version: full training week, a certificate for attending it, quota live in month two, and a "ramp problem" diagnosed in month six that was visible in the week-three indicators nobody was watching. You know it works when a hiring plan conversation quotes ramped-equivalent capacity by month, and when a struggling new rep's gap can be named from gate evidence instead of vibes.

Diagnostic Questions

  1. What did your last four hires cost in ramp months x loaded cost, and who owns shrinking that number?
  2. Does your capacity model count heads or ramped-equivalents? Recompute this year's plan with ramp curves and see if the pipeline target still holds.
  3. What evidence graduates a rep from ramp today: a date, or scored certifications? Has a gate ever failed anyone?
  4. What is your time-to-first-qualified-opportunity by hire cohort, and is it improving?
  5. Where does a new rep go to hear what a great discovery call sounds like, and how old is the newest example there?

Provenance and practice-based rules: read references/ramp-benchmarks.md.

Built by Neon Triforce

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Sales Ramp Enablement AI skill do?

Design rep ramp as an instrumented system: milestone-gated 30-60-90 with certification evidence, ramp math wired into capacity and forecast, ramp-adjusted quota and comp, and a manager cadence that catches a drifting ramp in week three instead of month five. Triggers on 'ramp', 'ramp time', 'new rep onboarding', 'time to productivity', 'reps take too long to produce', 'certification', 'enablement program', 'sales onboarding plan', '30-60-90 for the new AE', 'ramp quota', or any hiring plan that treats the months between start date and full production as weather. BOUNDARY: assumes a playbook...

Why use Sales Ramp Enablement on TypingMind?

Because you install it once and use it with any model. Sales Ramp Enablement is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sales Ramp Enablement in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NEON-Rutger/B2B-revops-skills/tree/main/sales-ramp-enablement. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Sales Ramp Enablement?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sales Ramp Enablement?

As many as you like. As long as a model supports skills, you can use Sales Ramp Enablement with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sales Ramp Enablement AI skill free?

Yes. It is published on GitHub by NEON-Rutger under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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