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Source: frameworks/kit-advisory-onboarding-v2/06-advisory-onboarding-v2-ai-extraction.md

06 — AI EXTRACTION CONVERSATION: Advisory Onboarding Kit v2

Level 3 design. This is a conversation protocol, not a questionnaire. The AI adapts to the member, draws on cross-member intelligence, and resolves gaps — not just flags them.


The Goal

Understand this practice's onboarding — per offer — well enough to build a roadmap the practice owner would hand to a client and feel proud of. The universal onboarding spine is already captured (file 01). This conversation captures what makes THIS practice different.


How It Works

The AI runs a structured conversation with the member. Not a form. Not an interview. A conversation where the AI:

  1. Knows what it needs — the data categories below
  2. Gets there adaptively — if the member volunteers their welcome experience while describing their package, capture it and move on
  3. References what similar practices do — "Most practices in your cohort pre-schedule all advisory meetings at onboarding. Do you do that, or do you book as you go?"
  4. Proposes solutions for gaps — "You don't have a welcome experience yet. Here's what two similar practices do: [A sends a personal video within 48 hours, B sends a written welcome with team intros]. Which is closer to what you'd want?"
  5. Self-validates as it goes — catches inconsistencies in real-time, not in a post-extraction pass

Who runs it: Claude with the member. No Kathryn required.

How: Asynchronous, co-working session, or standalone Claude session.

Time: 10-15 minutes per offer.


Opening Framing

Start with this — adapt the language to the moment, but hit these three beats:

  1. What we're doing: "We're capturing the specifics of your offer so we can build your client-facing onboarding roadmap."
  2. What we already have: "The universal onboarding process is already built from the group sessions. We're not re-doing that. We just need YOUR details."
  3. Special-sauce protection: "If something feels like competitive advantage — not just structural detail — say so. We'll note it as your approach, not something that goes into the shared framework."

Two Phases

Phase 1: Practice-Level (Once)

Get the lay of the land. This sets context for everything that follows.

What you need to know:

CategoryWhy
How many offers they haveDetermines how many times Phase 2 runs
Who's on the teamSo you can reference real names in Phase 2
What tools the practice usesSo you can distinguish client-facing from back-end
Practice model (lean / institutional / coaching)Drives how you shape the conversation — a solo practitioner's answers look different from a team-based firm

How to get there: Start with "Tell me about your practice — how many different things can a new client buy from you?" and let the conversation flow. You'll naturally surface team, tools, and practice model as they describe their offers.

Don't force all four categories before moving on. If you have enough to start Phase 2, start. Come back to fill gaps.

Phase 2: Per-Offer (Loop)

For each offer identified in Phase 1, understand the onboarding experience end-to-end.

Start with the offer most new clients buy. If a member has three offers, the primary one gives you the most useful roadmap first.

Transition between offers: "That covers [Offer A]. Now let's do [Offer B] — tell me what's different. If something is the same, just say 'same' and we'll move on."


What You Need Per Offer

These are the data categories, not a question list. Get this information through conversation — the order and exact phrasing should adapt to how the member talks.

The offer itself

Who does what — the Q3 question

This is the most important per-offer data. Walk through the onboarding steps and for each one, get: advisor personally / mechanical (same every time) / team member (name who).

The universal spine steps (from file 01):

  1. Trigger fires (sign + pay)
  2. Welcome experience sent
  3. Pre-kickoff logistics (portal, docs, scheduling)
  4. Kickoff meeting
  5. First quick win identified and executed
  6. Seasonal cadence begins
  7. Between-meeting communication
  8. Onboarding declared complete

For each step: "Who does this? Is it you, is it automated, or does [team member name] handle it?"

Adapt based on practice model:

Cross-member intelligence to use:

The rhythm

The proof point

The first impression

The finish line


While You're Listening

Catch inconsistencies in real-time

Don't wait for a validation pass. If something doesn't add up, ask now:

Capture what they volunteer early

If a member says "the first thing they get is a video from me within 24 hours" while describing their package structure — that's the welcome experience. Record it. Don't ask again later.

Propose, don't just flag

When there's a gap:

Level 1 (don't do this): "GAP: Welcome experience not defined."

Level 3 (do this): "You haven't designed a welcome experience yet. Here's what works for practices like yours: [Option A] or [Option B]. Want to pick one now, or flag it as something to build Thursday?"


Cross-Member Intelligence

Use what you know from other members to help — but never share proprietary details.

Safe to reference:

Never reference:


Output

The extraction produces a structured data file per member (containing all offers) that feeds the output skill (file 05). Format:

# AI Extraction — [Member Name]

**Date:** [Date]
**Offers extracted:** [N]
**Gaps remaining:** [N or None]

---

## Practice-Level

**Team:** [Names and roles]
**Tools:** [Client-facing vs internal]
**Practice model:** [Lean / Institutional / Coaching]

---

## Offer: [Name] (Primary)

**Package:** [Description]
**Included:** [List]
**Separate:** [List]
**Pricing structure:** [Monthly/Annual/Per-project — no amounts]

**Who touches what:**
| Step | Owner | Notes |
|------|-------|-------|
| [Step] | [Advisor/Mechanical/Team: Name] | [Context] |

**Cadence:** [Months + purposes]
**First win:** [Description + dollar example + verification]
**Welcome:** [Format + timing + sender + content]
**Completion gate:** [Criteria list]

---

## Offer: [Name 2]
[Same structure — only differences from primary noted if member said "same"]

---

## Resolved During Conversation
[Any inconsistencies caught and resolved in real-time]

## Proposed and Accepted
[Any gaps where the AI proposed a solution and the member accepted]

## Still Open
[Any genuine unresolved items — with proposed resolution path]

What This Does NOT Do


Confidentiality

Remind once at the start:

"Don't share Social Security numbers, EINs, bank account numbers, or client-identifying financial data. If a client example helps, use a description — 'a client who owns two S-corps' — not a name."


Cross-references