The Revenue AI Report
AI GTM

Scale Evolve

S.C.A.L.E. step 5, Evolve. Scores the pilot against the charter (expand, adjust, or stop), builds the three-layer scorecard and operating rhythm, drafts the Center of Excellence with two co-chairs and named roles, and writes the AI policy sized to the company.

Part of S.C.A.L.E. v1.2 Plugin. Get every file in the kit, plus the guide, in one place.

Where it came from

  • Source: Built by Jonathan Kvarfordt (Coach K). Package v1.2, supplied as a complete zip and served unchanged.
  • Frameworks applied: Step 5. Evolve

Why it was chosen

It covers a job one of the eight revenue seats has to finish, and it states its process, decision rules, and output format clearly enough for an agent to follow.

Known weakness, published as found: This skill reads template files that ship in the kit download. Get the full kit so the templates are in place.

How to use it

  1. 1.Copy the SKILL.md text below, or download the raw file.
  2. 2.Create a folder named exactly scale-evolve in your agent's skills directory.
  3. 3.Save the file inside that folder as SKILL.md.
  4. 4.Ask the agent one of the trigger requests below.
  5. 5.Check the output against what you already know before it leaves your desk.

Install this skill

  1. For Claude Code, copy the command below into your terminal. It creates the skill folder and saves the file as SKILL.md.
  2. For another assistant that supports skills, download the file above and place it in a folder named scale-evolve inside that assistant's skills directory.
  3. Start a new conversation and ask for the job named on this page. Review the result before using it.

For the supporting files, download the full S.C.A.L.E. v1.2 Plugin package too. The single-file command only installs SKILL.md.

mkdir -p "$HOME/.claude/skills/scale-evolve" && curl -fL "https://www.therevenueaireport.com/agent-skills/scale-evolve/SKILL.md" -o "$HOME/.claude/skills/scale-evolve/SKILL.md"

Ask it this

  • evolve the system
  • step 5
  • did the pilot work

The SKILL.md file

---
name: scale-evolve
description: S.C.A.L.E. step 5, Evolve. Scores the pilot against the charter (expand, adjust, or stop), builds the three-layer scorecard and operating rhythm, drafts the Center of Excellence with two co-chairs and named roles, and writes the AI policy sized to the company. Use when the user says "evolve the system", "step 5", "did the pilot work", "set the cadence", "who should own AI", "AI policy", "center of excellence", or after step 4.
---

# scale-evolve

Write `SCALE/5-evolve-system.md`. Don't scale chaos. Scale what works, with governance baked in.
## Preflight (every run)
1. Find the `SCALE/` folder (Desktop or Documents), or `GTM-AI-OS/artifacts/scale/` if the user runs the GTM AI OS. If neither exists, run `scale-start` first; it creates the folder and asks for access.
2. Read `SCALE/progress.md`: mode (quick or deep), AI experience level, which steps are done, the one-line context.
3. Talk short and direct. Say what each answer is for. Beginner: one question at a time, plain words. Advanced: batch questions, skip explanations.
4. Quick mode: ask only the questions marked (Q). Deep mode: ask all. Accept "skip" and "don't know"; record them as gaps.
5. If the previous step's artifact is missing, say so and offer: do that step now, or answer three questions and continue with a draft marked fast path.
6. When the user names a system (CRM, calls, email, spreadsheet), request access to that one or take an upload. Never assume a product.
7. On finish: write the artifact, update `progress.md`, say the next step in one sentence, and ask one open question if any remain.


## Part A: Judge the pilot
1. (Q) Each criterion: baseline, current, target. From the CRM if connected, else from the user.
2. Stage diagnosis: early-stage drop means ICP or signal (back to Chart); late-stage drop means motion or skill (Align); post-sale drop means product or onboarding.
3. The two headline metrics, restated with their numbers.
4. (Q) The call: Expand (to a defined next group, never the whole org), Adjust (what, and re-run the window), Stop (and what was learned).

## Part B: Scorecard and rhythm
1. Three layers: executive (impact, adoption, three numbers), management (driving KPIs, red / yellow / green), technical (system health, data quality, guardrail incidents, reversal-trigger status).
2. The weekly review, named: 20 minutes, one owner, reads the scorecard and the pilot's weekly row, decides what to change (a message, a criterion, a step), and the owner approves each change. In SCALE this is a cadence you run; the GTM AI OS adds the mechanism that proposes changes from a log.
3. (Q) "Which revenue meetings already exist?" Attach artifacts to them before adding any. Weekly: pipeline review by motion, signal refresh, one ride-along. Monthly: review and rewrite. Quarterly: ICP refresh, reallocation, re-run step 1. Owner, day, artifact read, artifact updated. Offer to place on the calendar if connected.

## Part C: Who owns AI
1. (Q) Company size and regulation. Small or unregulated: three to five people. Mid-size or regulated: the full model.
2. Executive sponsor as high as possible. If it's HR: HR on the team, not in the chair; say so plainly.
3. Technology co-chair (speed, build, safety) and business co-chair (ROI, adoption, prioritization). Core team by title: legal, security, enablement, GTM, product and engineering, RevOps as data steward, industry-specific roles.
4. Purpose, decision rights, intake, budget path, relationship to tiger teams. Biweekly to start, two standing items: the prioritized use-case list and performance of what shipped.
5. Deep: the 90-day and 12-month view, including whether a dedicated forward-deployed pod reports to the CRO, RevOps, or the CTO. Don't deploy it until the foundations exist.

## Part D: The rules
1. Inherit any existing IT or security policy; extend, don't duplicate.
2. Thirteen areas, one paragraph each for small orgs, full for regulated: roles, operating model, risk and compliance, rules of use, security, model management, bias, tools and monitoring, transparency, accountability, trustworthiness, responsibility, incident response.
3. Risk register seeded from the step 3 reversal trigger and guardrails: risk, likelihood, impact, control, owner, review date.
4. Quality gates before any AI output reaches a customer, a forecast, or a system of record.

## Part E: The 30-day commitment
Ask, one at a time: (Q) the one AI opportunity you'll act on in 30 days; (Q) the specific action; the resources needed; (Q) the metric that proves it. Write it as one sentence at the end of the file and read it back.

## Write
`5-evolve-system.md` from `references/evolve-template.md`. Quality gate: no "expand" to the whole org; a scorecard nobody is scheduled to read isn't done; a CoE with one chair isn't done.

## Hand off
Mark the step done in `progress.md`. Return to `scale-start` for the close: the map of files and the 30-day commitment read back.

Common questions

What does the Scale Evolve skill do?
S.C.A.L.E. step 5, Evolve. Scores the pilot against the charter (expand, adjust, or stop), builds the three-layer scorecard and operating rhythm, drafts the Center of Excellence with two co-chairs and named roles, and writes the AI policy sized to the company.
Where does the Scale Evolve skill come from?
Built by Jonathan Kvarfordt (Coach K). Package v1.2, supplied as a complete zip and served unchanged.. The source and included files are shown on this page and in the package download.
Why was the Scale Evolve skill chosen for this library?
It covers a job one of the eight revenue seats has to finish, and it states its process, decision rules, and output format clearly enough for an agent to follow.
When should the Scale Evolve skill not be used?
Use it only for the job named above. A skill applied outside its scope produces confident output on the wrong question.
How do I install the Scale Evolve SKILL.md file?
Download the file, create a folder named exactly scale-evolve inside your agent's skills directory, and save the file inside it as SKILL.md. The agent loads it when a request matches the description.

Raw file: https://www.therevenueaireport.com/agent-skills/scale-evolve/SKILL.md. Plain-language skills with worked examples live in the Skills and Prompts library.

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