Practitioner Execution Secrets

Execution Secrets from Top AI Audit Practitioners

Verbatim frameworks, scripts, and tactics pulled from the YouTube channels, podcasts, and social of the named experts + supplementary sources.

Method note: YouTube transcripts aren’t fetchable, but Apple Podcasts episode summaries and the practitioners’ own landing pages/X posts exposed the full methodologies verbatim. Every framework below is sourced.

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1. COREY GANIM — The Complete Two-Call Mini-Assessment Playbook (verbatim)

This is Corey’s free 15-minute assessment that converts cold leads into $999 paid audits at a 30–50% conversion rate. It’s the single most actionable framework I found. Source: Build With AI podcast, Ep. 171, free Notion playbook.

The core lens (memorize this)

One bottleneck. One tool. One upsell.

You don’t audit the whole business. You find ONE bottleneck, prescribe ONE tool, and leave one upsell on the table.

The three levers of ROI

Every prescription must pull at least one of three levers. Let the client pick which matters most to them, then weight everything toward it:

1. Effectiveness — more revenue
2. Efficiency — hours back in their week
3. Quality — happier customers

If a recommendation doesn’t move at least one lever, don’t recommend it.

Meeting 1 — The 15-minute fact-finding call (5 questions, verbatim)

1. The forking question — routes the conversation to their actual business model. 2. The repetition question — surfaces high-frequency tasks (automation candidates). 3. The friction question — surfaces high-friction tasks (pain points). 4. The ROI anchor question — quantifies the value of solving it (your ROI hook). 5. The magic wand question — Corey’s favorite: “If you could wave a magic wand and fix one thing in your business, what would it be?” Reveals their real priority.

How to pick the bottleneck: Find the task at the intersection of high frequency AND high friction. That’s your one bottleneck — the highest-leverage thing to fix.

Close call 1 by booking the follow-up.

Between meetings — Your research

• Research the frequency and friction of the bottleneck they named.
• Find the one tool that solves it.

Meeting 2 — Prescribing the one solution (the prescription tree)

Use this decision tree to prescribe the right solution type:

Branch 1 — Off-the-shelf tool: If a $20–50/mo SaaS tool already solves it (find them in AI directories like there’s an AI for that), prescribe that. Cheapest, fastest.

Branch 2 — Claude Cowork: If it needs a custom workflow but not custom code, prescribe Claude Cowork (Claude’s collaborative work feature). Mid-effort.

Branch 3 — Custom Claude skill: If it’s a repeatable process unique to their business, prescribe building a custom Claude skill. Highest value, justifies the paid audit.

The three things you bring to call 2

1. The one bottleneck you identified (named specifically)
2. The one tool/skill that solves it (your prescription)
3. The ROI projection (what solving it is worth, tied to the lever they picked)

The money question (the close)

Corey asks the money question at the end of call 2 and converts 30–50% of free assessments into $999 paid work.

Why this works for you

This is your free lead-magnet call — better than a scorecard for warm leads. Use Corey’s 5 questions as your scoping-call discovery questions (replaces the generic questions in Asset 9 Part B2). They’re more targeted and designed to surface a paid-audit-worthy bottleneck fast.

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2. COREY GANIM — The AOA Framework (Audit, Optimize, Automate)

This is how Corey actually executes the audit work itself. Source: Corey on X, Build With AI podcast.

“If you automate a broken process, all you’ve done is make the inefficiency run faster.”

The 3 steps, verbatim:

1. AUDIT — Walk me through how you do it today. The full manual process, step by step. Don’t touch anything until you understand it.

2. OPTIMIZE — Fix the process before you automate it. “The thing you’re doing in 12 steps can usually be done in 7.” Cut it down first.

3. AUTOMATE — Now add AI. Usually means turning the process into a Claude skill. But there’s no point building a skill around 12 steps when it only needed 7.

Telling them this up front sets the expectation before any money changes hands — this is a sales technique as much as a methodology. It positions you as someone who won’t waste their money automating broken work.

The 5 workflows to audit first (Corey’s list)

Apply AOA to these for immediate leverage:

1. Lead follow-up
2. Quote requests
3. Client reporting
4. Support tickets
5. Sales call follow-ups

These are universal — every business has them, and they’re all high-frequency/high-friction. Start here.

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3. COREY GANIM — The AI Concierge Retainer Model ($1,000/hr)

This is how Corey converts audits into retainers. It’s a different model than the fCAIO retainer in Asset 7 — leaner, faster to start, very high hourly. Source: How I’m making $1,000/hour as an AI Concierge, LinkedIn.

The offer

• Done-WITH-you consulting (not done-for-you)
• 2× 45-minute strategy calls per month
• Unlimited Voxer (voice message) access, 12-business-hour SLA
• A shared Notion hub — the renewal mechanism
• Price: started at $1,000/mo → scaled to $2,000/mo with 100% close rate (5 of 6 pitched said yes)
• At $1,500/mo with two 45-min calls = exactly $1,000/hour

The 7-step delivery (verbatim)

1. Intake form (Jotform) — required before call 1. “If it’s not filled out, you reschedule.” Lets you hit the ground running.
2. Onboard to Claude Cowork on call 1.
3. Run AOA on the biggest bottleneck — audit, optimize, automate. Ship at least one automation on day one so they feel progress.
4. AOA on every call — audit a process, optimize it, automate it.
5. Async access via Voxer — unlimited voice messages, 12-hr reply SLA. Turns you into an always-on partner.
6. Shared Notion hub — every call: recording link, top 3 takeaways, action items, and a quantified list of everything built. “When a client can see ‘we built two skills and three context files this month,’ the $1,500 justifies itself.”
7. Automate your own busywork — Corey built 2 Claude skills: one fills the Notion call log from the transcript, one drafts the client follow-up email. 2 commands, 30 seconds, done.

Why the Notion hub is the renewal mechanism

“The build log inside Notion earns the renewal for you. The ledger does the talking.”

Clients renew because they can SEE the accumulated value. This is a retention masterstroke — borrow it.

The 11-step playbook (Corey’s full business-in-a-box)

Corey packaged this into an 11-step playbook with templates (intake form, Notion hub, Claude skills for follow-up). It covers:

1. Business model explanation
2. Intake questionnaire
3. Strategy call framework
4. AOA framework
5. Voxer setup
6. Notion documentation hub
7. Automating the back end with Claude skills
8. Pricing & scaling
9. Upsell menu
10. Common pitfalls
11. First engagement end-to-end tutorial

This is in his AI Operator Academy (Skool community, ~$?). You can reverse-engineer most of it from the podcast episodes — or join if you want the templates.

How this changes your retainer offering

Your Asset 7 fCAIO retainer ($5K–$15K/mo) is for bigger clients. Corey’s Concierge model ($1.5K–$2K/mo) is a perfect down-sell for clients who can’t afford the full fCAIO but want ongoing help. Add it as a third retainer option:

Retainer	Price	Model	Source
AI Concierge (new — down-sell)	$1,500–$2,000/mo	2 calls + Voxer + Notion hub	Corey Ganim
Fractional CAIO — Starter	$5,000/mo	your existing	You
Fractional CAIO — Standard	$9,000/mo	your existing	You
Fractional CAIO — Deep	$15,000+/mo	your existing	You

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4. COREY GANIM — The Automation Back-End (steal this)

Corey runs his entire follow-up in under 5 minutes using 3 Claude skills. This is directly applicable to your n8n + Claude pipeline.

The 3 skills:

1. Follow-up email skill — drafts the client follow-up email after each call
2. Notion update skill — fills takeaways, action items, and build log after each call
3. Orchestrator skill — runs both back-to-back

Total post-call time: under 5 minutes.

In your stack, these map to Claude skills or n8n workflows triggered by the call transcript landing in Supabase. Same pattern as your Asset 3 Loom-script-draft node — extend it to also draft the follow-up email and update the portal’s build log.

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5. COREY GANIM — Foot-in-the-Door Methods (5 ways to get clients)

From another podcast episode. The foot-in-the-door offer that powers all of them is the free 15-minute mini AI assessment. Source: Build With AI podcast.

The 5 methods:

1. Door-knocking local service businesses — lowest-hanging fruit. One person went into 30 businesses, got 5 appointments, landed 2 paying clients. “If you do 10 walk-ins a week consistently, you will get clients.”
2. Free audits for people in your network
3. Documenting wins and building early testimonials
4. Partnering with agencies, coaches, and consultants (they refer you)
5. (method 5 implied: content/social)

For your Western-market targeting: adapt method 1 to LinkedIn virtual door-knocking — 10 targeted DMs/week to AU/EU/UAE founders with the free scorecard offer. Methods 2–4 apply directly.

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6. LIAM OTLEY — The $60,000 AI Audit (structure)

Liam’s framework for high-end audits. Source: “How to Perform a $60,000 AI Audit” (152K views), catalog.

The 4-week structure

• Week 1–2: Interview 20–30 staff, map processes end-to-end.
• Week 3–4: Identify opportunities, build roadmap, present.

The deliverables (3 artifacts)

1. Ops Canvas — the current-state operational map
2. Opportunity Matrix — ranked opportunities
3. Executive deck with the ROI “money slide”

The value ladder (Liam’s full model)

“$5k chatbots → $60k audits → $250k+ dev deals”

The audit is the middle rung. Below it: cheap chatbot builds (foot-in-the-door). Above it: $250K+ development engagements (the real money). The audit’s job is to qualify clients for the dev deals.

Why it’s worth $60K

• Deep stakeholder interviews (20–30 staff = weeks of work)
• Board-ready deliverable with quantified ROI
• It’s priced as a fraction of the $250K dev deal it unlocks — value-based, not time-based

How this applies to you

You’re not at $60K yet, but the structure scales down:

• Your $3K Opportunity Audit = Liam’s $60K audit at 1/20th the depth (2–3 interviews instead of 20–30, same 3 deliverables)
• Your $5K Deep Dive = the middle ground (5–6 interviews, board-ready 1-pager)
• Graduate toward $60K by increasing interview count, adding governance/compliance, and pricing value-based (% of identified savings) as you add case studies.

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7. MARK KASHEF — The 10-Question Consulting Framework

Mark’s channel focuses on AI-first strategy. Source: “So You Want to Be an AI Consultant? Start With These 10 Questions”, “300 hours of AI consulting in 23 minutes”, Entrepreneur profile.

Mark’s positioning (worth adopting)

“AI is a luxury earned through internal organization.”

He leads with data readiness and compliance — not tools. His audits check whether the client has earned the right to deploy AI before recommending any. This is a strong differentiator and pairs with your governance dimension.

His audit scope

• Audits backends and all-employee workflows
• Identifies time-sinks across the whole company
• Data-readiness questionnaire (the core)
• Compliance review (GDPR, data privacy)
• Output: audit + custom solution design

Pricing

$15K–$50K for enterprise. Justified by the depth (whole-company workflow mapping + compliance) and the data-first positioning.

What to borrow from Mark

• Lead with data readiness, not tools. Your Dimension 2 (Data Readiness) and Dimension 6 (Governance) should be prominent — Western/EU buyers care about this deeply.
• The “earned through organization” framing — use it in your sales page. It’s intellectually honest and positions you against the hype sellers.

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8. NATE HERK — The Value-Ladder Audit

Nate’s model. Source: catalog, Modern Creator interview.

The value ladder (Nate’s rungs)

1. Hours → 2. Audit → 3. Project → 4. Retainer

The audit is “Rung 1” at $500–$2,500. Its job: map workflows, find automatable tasks, build a proposal for the project/retainer. Pricing framed as 10× first-year ROI.

Nate’s offer-structure approach (from his Claude Code content)

He uses AI (Claude Code) to generate:

• Segment A, Segment B, core offer, tier ladder
• Pricing logic, one-line value prop
• Three sharpest objections with rebuttals

This is exactly how you’d build your own offer in Claude Code — prompt it to generate the value ladder, objections, and rebuttals. Borrow the structure.

What to borrow from Nate

• The explicit value ladder — name your rungs: Free scorecard → $3K audit → $8K sprint → $9K/mo retainer. Show clients the path.
• 10× first-year ROI framing — price the audit as ~10% of the first-year savings you expect to find. If you project $30K/yr savings, a $3K audit is 10×. Defensible and value-based.

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9. SUPPLEMENTARY — The 14-Day AI Readiness Assessment Process

From GetWidget’s practitioner guide — a clean, implementable 14-day process that matches your delivery timeline.

The 6 dimensions they score (validates your 7)

Data readiness, infrastructure, talent/skills, governance/risk, use-case viability, change management. Each scored 0–4, weighted by delivery risk, rolled into a single readiness index.

The 14-day sequence

1. Scope & stakeholder kickoff
2. Evidence gathering across 6 dimensions
3. Scoring against the rubric
4. Gap workshop
5. Readiness report + roadmap

Key principle: Each phase is a decision point. If data readiness scores 0 on day 5, stop and fix data before assessing infrastructure you can’t use yet. This matches your binding-constraint methodology.

The gap-to-roadmap output

Each gap gets: ONE owner, a sized first action, a milestone, a sized effort, and what it unblocks. No theme without an action. This is a cleaner roadmap format than Asset 5 — borrow it.

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10. SUPPLEMENTARY — The Eight-Gate Data Readiness Audit

From Codebridge — the most rigorous data-readiness framework I found. Use this to make your Dimension 2 (Data Readiness) genuinely impressive.

The 4-pass routine

1. Source inventory — list every system, doc store, inbox, spreadsheet, and human notebook containing data the agent will need.
2. Quality probe — pull a 100-row sample from each source, score for completeness, correctness, consistency.
3. Integration map — for each source: access route (API, export, OCR, manual), latency, cost, failure mode.
4. Risk profile — classify by sensitivity, identify regulated fields (PII, PHI, financials), decide where the workload must run.

The output

A go / fix-first / no-go decision per data source. This is gold for your opportunity matrix — it tells you which opportunities are “data ready” vs “needs data work first.”

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11. SUPPLEMENTARY — The Workflow Audit (one-workflow focus)

From Planfold — a counterpoint to whole-company audits. Useful for your Snapshot tier.

The 7 audit fields per workflow

Source, source of truth, data class, allowed AI action, human review, evidence, decision.

The 5 allowed AI actions (a clean framework)

• Observe — read, summarize, classify
• Draft — prepare text or a task, not send it
• Recommend — rank or suggest, human decides
• Prepare update — propose a system change, owner approves
• Stop — route to human because data class/source/responsibility is unclear

Borrow this for your opportunity matrix — each opportunity should name its allowed AI action. It makes the roadmap concrete and governable.

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12. WHAT TO UPDATE IN YOUR ASSETS (the synthesis)

Based on all of the above, here are the specific upgrades to make to your existing playbook:

To Asset 9 (Execution Playbook) — Scoping Call

Replace the generic discovery questions (B2) with Corey’s 5 questions:

1. The forking question
2. The repetition question
3. The friction question
4. The ROI anchor question
5. The magic wand question

Then find the task at the intersection of high frequency AND high friction = the one bottleneck to prescribe against.

To Asset 9 — Interview Script

Add Corey’s AOA framing at the start of the use-case inventory: “I’m not going to automate a broken process — that just makes the inefficiency run faster. We’ll audit how you do it today, optimize it (your 12 steps are probably 7), then automate what’s left.” This sets expectations and positions you.

To Asset 3 (n8n Pipeline) — Add the 3 follow-up skills

After the Loom-script-draft node, add:

• Follow-up email drafter (Claude skill)
• Portal build-log updater (Claude skill / n8n workflow)
• Orchestrator that runs both

Post-call time drops to under 5 minutes. Same as Corey.

To Asset 7 (Sales Bridge) — Add the Concierge down-sell

Add a third retainer option below Starter:

• AI Concierge — $1,500/mo — 2× 45-min calls + Voxer access + Notion build log. Done-with-you, not done-for-you.

This captures clients who can’t afford $5K/mo but want ongoing help. Higher volume, lower effort, ~$1,000/hr effective.

To Asset 5 (PDF Deliverable) — Sharpen Dimension 2 (Data Readiness)

Add the 4-pass data audit (source inventory, quality probe, integration map, risk profile) and go/fix-first/no-go per data source. This makes your data readiness dimension genuinely rigorous — Western buyers will respect it.

To Asset 2 (Scorecard) — Add the allowed-action framework

For each opportunity surfaced, name its allowed AI action: Observe / Draft / Recommend / Prepare update / Stop. Makes the deliverable concrete and governable.

To your sales page (Asset 1) — Borrow Mark Kashef’s framing

Add to the problem agitation section:

“AI is a luxury earned through internal organization. We check if you’ve earned it before recommending any tools.”

This positions you against the hype sellers and resonates with sophisticated EU/UAE buyers.

To your value ladder — Make it explicit (Nate Herk style)

Name your rungs on the sales page or in the debrief: Free scorecard → $3K audit → $8K sprint → $1.5K Concierge / $5K–$15K fCAIO retainer Show clients the path. The audit is Rung 2; everything above it is where the real money lives.

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13. THE PRINCIPLES THAT UNIFY ALL TOP PRACTITIONERS

1. One bottleneck, one tool, one upsell. Don’t boil the ocean. Find the highest-leverage thing and prescribe one solution. (Ganim)
2. Audit before you automate. Automating broken processes just makes inefficiency run faster. (Ganim)
3. The audit is a foot-in-the-door, not the business. Every practitioner uses the audit to sell the next thing — sprint, retainer, or dev deal. (Ottley, Herk, Ganim)
4. Lead with data readiness, not tools. Sophisticated buyers want to know if they’ve earned the right to deploy AI. (Kashef)
5. The deliverable earns the renewal. A visible build log (Notion hub) that accumulates value makes retention automatic. (Ganim)
6. Value-based pricing, not time-based. Price the audit as ~10× of first-year savings found, or as a fraction of the retainer it unlocks. (Herk, Ottley)
7. Automate your own delivery. Every top practitioner uses Claude skills to automate their follow-up, notes, and reporting. Eat your own dog food. (Ganim)
8. The 2-call structure converts. Free 15-min fact-finding → paid prescription. 30–50% conversion. (Ganim)

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SOURCES

• Corey Ganim — Build With AI podcast Ep. 171 (Apple Podcasts), free mini-assessment Notion playbook, audittemplate.ai, $1K AI Audit interview on Ryan Doser, AOA framework on X, AI Concierge $1K/hr post, 11-step playbook on LinkedIn, AIOS framework on LinkedIn, 5 workflows to audit (Vibin)
• Liam Ottley — How to Perform a $60,000 AI Audit, Liam Ottley YouTube channel
• Mark Kashef — 300 hours of AI consulting in 23 min, Entrepreneur profile, Mark Kashef YouTube channel
• Nate Herk — Modern Creator interview, catalog
• Supplementary — GetWidget 14-day assessment, Codebridge 8-gate data audit, Planfold workflow audit, Arkeo AI readiness, Layer3 Labs pricing, Agenticsis 6-step framework