AI Working Session
Built for Tom Lutz
Working Session · Dallas · 2026

From tool
to teammate
to operating layer.

A two hour working session built around the way AI capability actually compounds in a senior leader's work life. Three rungs. Four themes. One real document of yours that follows you up the ladder.

For
Tom Lutz
Role
MDP · PE Portfolio Value · Consumer · Alumni
Format
Live · 2 hours · Leave behind
Tom Lutz
Tom Lutz
MDP · Dallas · BCG
Built by Rajiv Shenoy
Today's
Objective
Leave with real muscle memory across the three layers, and a working PE diligence flow, restaurant personalization brief, or alumni relationship system you'll actually use this week.

Most leaders stop at rung one.
The leverage is higher up.

Each rung asks more of you, and gives more back. The chart below shows how value compounds as you climb. You don't need to be at the top this week. You need to know where you are, and what the next move looks like.

Value Captured →
10× Leverage
100× Leverage
RUNG 01
use it
Tool
~80% of leaders
RUNG 02
teach it
Teammate
~15% have set one up
RUNG 03
let it run
Operating Layer
~2% building toward this
Effort to Set Up →

Live in the room.
Or yours to keep.

We'll run the live blocks together. The solo and optional paths live on this site as your leave behind. Pick them up this week, or hand them to a PL.

00:00
Warm up · The two windows
Claude and ChatGPT, side by side, on a real document you bring
Live · 10 min
00:10
Rung 1 · Tool
Pick a theme, run a workflow end to end on your real document
Live · 40 min
00:50
Rung 2 · Teammate
Build a persistent Project from today's workflow
Live · 30 min
01:20
Rung 3 · Operating Layer
What an agent would do, what to ask your team for, what's realistic when
Live · 25 min
01:45
Your homework
12 moves to choose from. Pick the 2 that fit your week.
Live · 15 min
Later
The other three themes
Whatever you didn't run live. Same shape, your pace.
Solo · this week
Later
The Cheat Sheet
38 prompts organized by your real jobs. Bookmark it.
Reference
Q2
Extend to your team
Share Projects, standardize prompts, review rubric
Optional
Q3
Agent design conversation
When rung 3 stops being aspirational
Optional

The rules don't change.
The tools do.

Eight principles that stay true whether you're on rung one or rung three. Different formats to keep them sticky. Flip the cards, study the examples, look at the split.

I.

Voice

The judgment is yours. The AI drafts the memo, but the conviction in it is yours. You sign your name, not the model's.

Tap for what this looks like
I.

In practice

  • Edit AI output until it sounds like you wrote it
  • Replace at least 3 phrases per output
  • Train Projects on your past writing
  • Never send unedited AI text to a client
  • Never paste AI into board materials without review
Tap to flip back
II.

Velocity

Compress, don't replace. The win is collapsing the hours between question and first draft so you spend the saved time on what only you can do.

Tap for what this looks like
II.

In practice

  • Measure time saved per task, not "did I use AI"
  • Reinvest saved hours in client time
  • If a chain takes longer than doing it yourself, fix the chain
  • Don't use AI for work you should be delegating
  • Don't optimize for novelty over leverage
Tap to flip back
III.

Verify

BCG enterprise accounts only. Spot check facts. Trust frameworks, verify figures. Every time. The model is confident even when it's wrong.

Tap for what this looks like
III.

In practice

  • BCG enterprise Claude and ChatGPT, no personal accounts
  • Verify every figure before it leaves your screen
  • Classify the doc before you paste it
  • Never paste client confidential into personal tools
  • Never trust an AI citation without checking the source
Tap to flip back
IV.

Context beats keywords

LLMs are nothing like Google. Keywords get you the most probable interpretation. Context gets you the one you actually meant.

BAD"sitagliptin expiration"
GOOD"You are a pharma analyst. When does the EU patent on Sitagliptin (Januvia) expire, and what generic launches are expected?"
V.

Iterate, don't perfect

Your first prompt is a draft, not a contract. The output is the start of the conversation, not the end. Follow up, refine, push back.

BADSpend 20 min crafting the perfect first prompt
GOOD3 min for the first prompt, then "more detail on point 2", "in a table", "challenge that"
VI.

Structure rewards structure

The more structured the ask, the more structured the answer. Specify role, context, task, format. Vague in, vague out.

BAD"Help me with this CIM"
GOOD"You are a PE analyst. Read this CIM. List the 8 levers, ranked H/M/L confidence. Output as table."
VII.

10 / 20 / 70

The model is the easy part. The data is the harder part. The people and process changes are where most value lives, and where most projects fail.

10
20
70
Model
Data
People & process
VIII.

Examples beat instructions

Telling the AI "write in my voice" rarely works. Showing it 3-5 examples of your past writing always does. Recipes beat rules.

BAD"Write this in a concise BCG executive voice"
GOOD"Here are 3 of my past memos [paste]. Write the new one matching that exact voice and structure"
Overview/Rung 01 · Tool

AI as a tool.

RUNG 1 OF 3

One prompt. One output. One task done in a tenth of the time. This is where everyone starts. Before we pick an adventure, ten minutes on the mechanics that separate a good prompt from a great one.

Before You Pick an Adventure · 10 min

The mechanics of a good prompt.

Every good prompt has these four parts. Pick the right tool for the job. And keep one prompt in your back pocket for when you need to kill a page of dense output.

Anatomy

The 4-part prompt

Miss one and the output is mediocre. Use them as section labels in your prompt for the first 10 tries.

01 · ROLE
Who should it be?
"You are a..." forces a stance and a vocabulary.
EXAMPLE "You are a sharp board chair who has seen 50 IPOs."
02 · CONTEXT
What's the situation?
Audience, stakes, constraints, what you tried. Most of the value lives here.
EXAMPLE "Midmarket SaaS, $80M ARR, considering a sponsor sale next year."
03 · TASK
What exactly?
Specific verbs: draft, summarize, critique, score, structure. Avoid "help me with."
EXAMPLE "Critique this strategy and identify the top 3 risks."
04 · FORMAT
What deliverable?
Length, structure, tone. Specifying this saves a follow-up every time.
EXAMPLE "5 bullets, plain English, no jargon, under 200 words."
2026 Landscape

Pick your tool

All five are useful. Pick by where the work is and what the work needs.

TOOLBEST FOR
ClaudeWriting, reasoning, long docs (1M+ context), careful tone
ChatGPTAll-rounder, voice mode, broad plugins, strong research
GeminiNative in Google Workspace, sees Drive/Docs natively
CopilotNative in M365 (Outlook, Word, Excel, Teams)
PerplexityLive web research with citations, fast lookups
Rule of thumb. Use the tool that's closest to where the work already lives. Friction kills adoption.
§
The Prompt to Steal
"Kill my page."
The single most useful prompt in BCG-land. Paste any dense piece of writing, hit enter. Get back what's essential, what's filler, and the 3 cuts that would tighten it most. Sharpens any draft in 30 seconds.

Four themes.
Same architecture.

Pick the one closest to what's on your desk this week. Whichever you pick, the workflow shape is the same. Synthesize, structure, draft, compress.

PE Diligence: From CIM to IC one pager

Five chained moves. Each one produces an artifact you'd actually send.

Do you have a recent CIM on your desk we can use?
→ The Setup
You have the CIM, management interviews, the QofE summary, a competitor benchmark. Roughly 200+ pages. Two days until IC. The chain below assumes that pile. If you brought your own, swap the document. The prompts work the same way.
01
Synthesize the materials
All docs Claude Project 1 page brief
Set up a Claude Project. Upload everything. Now every prompt from here knows the whole deal. No re-pasting.
Read everything in this Project. Give me a 1 page deal summary: business, financial profile, the 3 things that matter most, and the 3 things that worry you. BCG voice. No filler.
02
Build the value creation thesis
Deal brief 8 lever thesis
Force structure. The thesis isn't a paragraph. It's where value will come from, mapped to BCG's eight lever full potential plan.
Build the value creation thesis across the 8 levers: top line, ops, SG&A, org, finance, M&A, digital/AI, ESG. For each: the move, size of prize, confidence (H/M/L), and the one thing that has to be true.
03
Generate the diligence questions
Thesis Issue tree, ranked
The questions that need answering before IC. Ranked by deal killing potential, not by how easy they are to answer.
For each lever where confidence is M or L, generate the top 2 diligence questions. Then rank ALL questions by "if the answer is bad, how likely is it to kill the deal?" Top 10 only.
04
Draft the 100 day plan
Top 3 levers Sequenced plan
Take the three highest conviction levers and turn them into a sequenced 100 day plan: workstreams, owners, decision gates, early signals.
For the top 3 levers: Days 1-30 mobilize, 30-60 diagnose, 60-100 launch quick wins. For each phase: workstreams, owner type (CEO/CFO/COO/CRO), decision gate, and the metric that proves it is working.
05
Compress to the IC one pager
Everything 1 page that leaves the room
The output that actually leaves the room. One page. Why now, business case, risks, controls, milestones.
Compress to a 1 page IC memo: Why now (3 lines), Business case (the number plus how), Top 3 risks plus mitigations, 100 day milestones, Decision asked of IC. Tight. Board reads it in 90 seconds.
IC One Pager · sample output
Project Cypress · IC Memo
DRAFT · 340 unit casual dining · Sponsor: Apollo · Target close Q3
Why now
Founder-led chain hitting natural sponsor handoff. Multiple inflecting (digital ordering 28% mix, up from 14% two years ago). Below-peer marketing spend creates near-term lever. Window of 6-9 months before strategic acquirers price in the digital lift.
Business case
2.8x MOIC base case on $340M equity. EBITDA growth 14% → 22% margin over 5 years through (1) menu engineering and price architecture, (2) loyalty-driven frequency, (3) 40 new unit pipeline at improved AUVs.
Top 3 risks
  • Wage inflation persistence · mitigate via labor model overhaul and tech-enabled scheduling
  • Same-store traffic decline of 2.1% · loyalty mechanic must reverse before unit growth scales
  • CEO succession (founder exit by Y2) · identified COO as internal successor, executive search budgeted
100-day plan
Mobilize executive team Days 1-30. Diagnose unit economics and labor model Days 30-60. Launch menu test in 30 units and loyalty v2 by Day 90. Decision gate at Day 100 on go/no-go for full rollout.
Decision asked
Approve $340M equity at 11.5x EBITDA. Authorize 6-week confirmatory diligence focused on the 3 risks above. Target signing within 90 days.
§
You leave this layer with
A working IC one pager on your real deal, and a workflow that's now muscle memory
→ Governance · Not Optional
BCG approved enterprise accounts only. NDA classification check first. Never personal ChatGPT. The workflow doesn't change. The account does.

Restaurant Personalization: The 2024 GenAI piece, built live

Your own BCG article as the workflow. The 10/20/70 conversation made concrete.

Do you have a recent restaurant or consumer client situation we can use?
→ The Setup
The CMO has loyalty data but campaigns are still batch and blast. The COO doesn't believe personalization moves the needle. You have 30 minutes with both of them tomorrow.
01
Audit the data they have
Their stack Golden record gap
Map what they have against what they need for 1:1. The gap is the consulting opportunity.
Here is the client's data stack: [paste]. Map this against the "golden record" needed for true 1:1 personalization. What's there, what's missing, what's the build sequence?
02
Generate three microsegments
Loyalty profile Actionable segments
Behavioral segments a CMO can run a campaign against next week.
From the loyalty and POS data, generate 3 microsegments worth activating first. For each: size as percent of base, revenue per visit, what motivates them, the offer that would work, one risk if we get it wrong.
03
Build the workflow change
Segments 10/20/70 shift
The unlock isn't the algorithm. It's the workflow. Apply 10/20/70.
Apply 10/20/70 to this client: 10% algorithms, 20% data enablement, 70% operating model redesign. For the 70%: what specifically changes in the team's week? Old workflow vs new, side by side.
04
Pre-empt the COO's pushback
Whole plan 5 objections plus answers
Get ahead of every objection before they raise it.
The COO is skeptical. Generate the 5 hardest objections they'll raise (cost, complexity, brand, IT bandwidth, "we tried this") and a 2 sentence response to each. Anchor in 6-10% revenue lift data where relevant.
Draft email · CMO + COO meeting prep
§
You leave this layer with
A 30 minute meeting brief for the CMO and COO
→ Governance · Not Optional
Loyalty data is PII. The data lives in the client's environment or a BCG sanctioned secure workspace. Pattern level prompts only into general AI tools.

Alumni Relations: The quarterly reconnect

Most senior leaders' networks decay through neglect, not intent. AI is exceptionally good at the remembering, which is most of the work.

Do you have a trip coming up we can plan around?
→ The Setup
You have ~40 BCG alums in the market you're visiting. Former PLs, partners now at PE shops, ex-clients who became friends. You realistically have time for four dinners. Who, and why now?
01
Build the candidate list
Alumni roster Ranked top 12
Most of this work is data hygiene. Get the list clean, then layer signal on top.
I'm spending 2 days in [city] next month. I've pasted my alumni list with current roles and last-touch dates. Rank by: time since last meaningful touch, recent professional change worth acknowledging, strategic value to BCG. Top 12 with why each.
02
Surface the news on each
Top 12 Talking points
The thing that makes the outreach feel personal, not transactional.
For each of these 12, give me: their most recent public professional milestone, any news about their firm in the last 6 months, one thing they posted on LinkedIn worth referencing, the most natural reason for me to reach out this month.
03
Draft the four outreach notes
Top 4 Personal notes in my voice
Not "great to connect" boilerplate. Notes that sound like you wrote them on the plane.
Draft 4 outreach emails. Each: 4-6 lines, references something specific from step 2, no asks, just "I'll be in [city], can I buy you dinner on these dates." My voice is warm but direct, no consulting jargon. Sign as "Tom."
04
Build the dinner prep dossier
Confirmed 4 One page each
The 90 seconds you spend in the Uber that makes you sound like you've been thinking about them all month.
For each confirmed dinner: a 1 page dossier with current role, last 3 career moves, family if known, our last conversation, 2 topics they care about now, 1 thing BCG is doing they'd find interesting, 1 question I should ask them.
Sample outreach · 1 of 4
§
You leave this layer with
A complete trip plan, 12 names ranked, 4 outreach notes ready, 4 prep dossiers waiting
→ Governance · The Quiet One
Mostly public information here. Alumni rosters, LinkedIn, news. The line: don't paste private notes from past client engagements into general AI tools. Notes about people are still client work.

Bring Your Own: Your stuck moment

The most powerful workflow is the one you'd actually use tomorrow. Tell me what's on your desk, and we build the chain together.

What's the thing that took longer than it should have last week?
→ The Frame
Pick something real and uncompleted. A proposal that's stuck, a presentation you keep redrafting, a synthesis that took an associate three days last time. We diagnose where the friction is, sketch the prompt chain, and run it together.
01
Name the friction
Your task The actual bottleneck
Most "AI doesn't work for this" turns out to be "I asked the wrong way." Five minutes of diagnosis saves an hour of bad output.
Here's the task I'm working on: [describe]. The output I need is: [describe]. The reason it's slow is: [pick: synthesis / structure / writing / decision]. Tell me the 3 ways AI could compress this, ranked by impact, and which one to try first.
02
Sketch the chain · live
Bottleneck 3-5 step prompt chain
We do this together on the shared screen. I'll co-pilot. You leave with a chain you can re-run on the next instance of this work.
03
Run it end to end
Chain Working artifact
No demos. We run the real chain on the real task. If it breaks, we fix the chain. That's the point.
§
You leave this layer with
A working chain for the thing that's been stuck, and the artifact it produces
Overview/Rung 02 · Teammate

AI as a teammate.

RUNG 2 OF 3

Stop re-introducing yourself to the AI every morning. A Project, Custom GPT, or Skill remembers your deals, your voice, your frameworks. The same prompt does ten times the work. This is where leverage compounds.

Before You Pick an Adventure · 8 min

A teammate is more recipe than prompt.

A real teammate has four ingredients. Skip any of the four and you're back to a generic chatbot. Build them where your data already lives, not where you wish it lived.

Recipe

The 4 ingredients of a real teammate

Skip any of the four and you're back to a generic chatbot.

01 · INSTRUCTIONS
Persistent role & rules
The "always do / never do" list. Voice, format, audience, definition of success.
EXAMPLE "Always include 1 risk per recommendation. Never use 'leverage' or 'synergy.'"
02 · KNOWLEDGE
Real documents
Templates, past good work, brand guidelines, glossaries. Examples beat instructions every time.
EXAMPLE Upload 5 of your best past memos. Watch the quality leap.
03 · STYLE
3-5 voice samples
Your actual past writing. This is what makes the output sound like you, not a McKinsey deck.
EXAMPLE Paste your last 5 emails. Tell it: "match this voice exactly."
04 · GUARDRAILS
What to never do
Specific failure modes you want prevented. Be explicit. Hard rules work.
EXAMPLE "Never fabricate numbers. If a fact isn't in the docs, ask me."
Where They Live

Pick the right home

Build where your data and your work already live.

TOOLBUILD IT AS
ClaudeProjects (private workspace with docs) or Skills (modular instructions that travel)
ChatGPTCustom GPTs with files plus actions. Shareable in your org's GPT store.
GeminiGems that see your Drive, Docs, Sheets, Calendar natively
CopilotAgents in M365: Outlook, Word, Teams. Best for IT-governed orgs.
Rule of thumb. Build where your data already lives, not where you wish it lived. The friction of moving data kills good teammates.

Same four themes.
Now with memory.

Whatever you ran in Tool, you can promote here. The workflow that worked once becomes a Project, GPT, or Skill that runs forever. We set up PE live. The others are templated for you.

Build the PE Diligence Copilot Project

Same 5 step chain you ran in Rung 1, now living in a Project that remembers your approach.

Do you have 2 or 3 past one pagers we can use as voice training?
→ Why Promote a Workflow Into a Project
A regular chat forgets you. A Project remembers your voice, your frameworks, your past deals, your standard for an IC one pager. Setup is 15 minutes. Payback is every deal after.
01
Create the Project
Claude.ai New Project
In Claude: sidebar, Projects, New. Name it "PE Diligence Copilot." The Project is now the persistent shell. Every chat inside inherits its context.
02
Write the system instructions
Project settings Custom instructions
This is the part most people skip. The instructions are the Project's personality. Paste this as a starting point and edit to taste:
You are a PE diligence copilot for Tom Lutz, MDP at BCG. Tom leads the Portfolio Value Accelerator. Your job: turn deal materials into IC ready outputs. Always: (1) Use BCG's 8 lever full potential framework. (2) Write in tight, direct BCG voice. No filler, no "as an AI." (3) Rank questions and risks by deal killing potential, not ease. (4) End every analysis with the one thing that has to be true. Reference past deals in this Project as context. Never hallucinate figures. Flag what needs verification.
03
Load the Project knowledge
Reference docs Project files
Upload the BCG full potential framework, 2-3 of your best past IC one pagers (sanitized), and any standard templates. The Project now writes like you because it's seen your work.
04
Save the prompt chain as starters
5 prompts from Rung 1 Saved prompts
The 5 prompts from the Tool workflow become reusable starters. New deal? You don't write the synthesis prompt from scratch. You click "Synthesize CIM" and feed it the docs.
05
Run a second deal to validate
New CIM Same Project Compare output
The proof: drop a different deal in. The Project should produce something that already sounds like you. No editing of voice, only of judgment.
pe-diligence-copilot · SKILL.md
SKILL.md
past_one_pagers/
templates/
--- name: pe-diligence-copilot description: Turns CIMs and deal materials into IC-ready one pagers using BCG's 8-lever full potential framework. Use whenever Tom is reviewing a sponsor sale, carve-out, or platform deal and needs to compress 200+ pages into a 1-page IC memo. --- # PE Diligence Copilot ## What this skill does Turns deal materials (CIM, QofE, management interview notes, comps) into: 1. A 1-page deal summary 2. An 8-lever value creation thesis 3. A ranked diligence question list 4. A 100-day plan 5. An IC one-pager ## When to use - Tom is doing first-pass review on a new deal - IC is in 48-72 hours and the materials pile is overwhelming - Need to test thesis with the team before going deep ## Voice rules - Tight, direct BCG voice. No filler. - Never "as an AI", never "it's important to note". - Rank by deal-killing potential, not ease. - End every output with "the one thing that has to be true." ## Frameworks to apply - 8-lever full potential: top-line, ops, SG&A, org, finance, M&A, digital/AI, ESG - 10/20/70 when AI/digital is a lever - Confidence ratings: every lever gets H/M/L ## Hard rules - Never fabricate figures. If a fact isn't in the docs, flag it. - Cite the source document and page for every quantitative claim. - Sanitize: no client names in outputs that leave the Project. ## Reference files See past_one_pagers/ for voice and structure examples. See templates/IC_one_pager.docx for the target format.
§
You leave this layer with
A live PE Diligence Copilot Project in your account, with a portable SKILL.md you can share or hand off
→ Governance · Project Level
BCG approved enterprise Claude Project workspace only. Past deal materials uploaded as Project knowledge should be sanitized. Names, figures, identifying details removed if not needed for pattern learning.

The Personalization Strategy Custom GPT

Same idea as the PE Project, ChatGPT flavor. Pre-loaded with 10/20/70, the 2024 BCG piece, and your sanitized restaurant cases.

→ Built On the Same Pattern
Custom GPT setup follows the same 5 steps as the PE Project. Create, instructions, knowledge, starter prompts, validate. Below is the system prompt to start from.
01
Create the Custom GPT
ChatGPT Explore GPTs Create
In ChatGPT (Team or Enterprise plan): sidebar, Explore GPTs, Create. Name it "Personalization Strategy Copilot."
02
Write the system prompt
GPT settings Instructions
You are a personalization strategy copilot for BCG consumer practice work. Always apply the 10/20/70 framework: 10% algorithms, 20% data enablement, 70% operating model redesign. Anchor revenue claims in the 6-10% lift range from BCG's 2024 restaurant GenAI research. Output in BCG client memo style: tight, framework first, ending with the one operational change that matters most.
03
Load knowledge files
Reference docs Knowledge
Upload the 2024 BCG GenAI restaurant article, your past consumer personalization decks (sanitized), and a 10/20/70 reference page. ChatGPT supports up to 20 knowledge files per Custom GPT.
04
Set the conversation starters
GPT settings Conversation starters
Add the 4 starter prompts from your Rung 1 restaurant workflow. Now when you open the GPT, you can click "Audit a client's data stack" and skip retyping.
Sample GPT output · loyalty program redesign brief
Loyalty v2 · 90-day brief
Generated by Personalization Strategy Copilot · 2.3 sec
Diagnosis
Current program is points-for-purchases with single redemption tier. 38% of members are inactive at 90 days. The mechanic rewards what customers were going to do anyway, not behavior change.
10 / 20 / 70
10% · the model picks the right offer per microsegment. 20% · the CDP must link app, in-store, and delivery into a unified profile. 70% · marketing team moves from monthly batch to weekly trigger-based campaigns; ops team handles redemption variability at store level.
v2 mechanic
Tiered progression with behavioral unlocks. Frequency rewards beat spend rewards for restaurants. Add 2-week "next visit" personalized offer triggered by visit gap. Drop the explicit point currency; show "your status" instead.
90-day proof
Target: +4pt visit frequency in the lapsed-regular segment. Measure via control group. If it moves, scale across the loyalty base in months 4-6.
The one thing
The 70%. If the campaign team can't move to weekly cadence, v2 won't outperform v1 enough to justify the spend.
§
You leave this layer with
A reusable Personalization Strategy GPT ready for any consumer client conversation

Your Alumni Memory Project

The one most senior leaders will use weekly. Your alumni roster, dinner notes, career milestones, all in a Project that becomes external relationship memory.

→ Why This One Matters Most
Of the four themes, this is the highest frequency use case. Set it up once, use it every Sunday night. Same 5 step pattern as PE, different knowledge.
01
Create the Project
Claude New Project "Alumni Memory"
Same setup. Private to you. This Project is going to hold relationship context, so keep it locked down.
02
Write the system instructions
You are my alumni relationship memory. Your job: help me stay meaningfully connected to a network of former BCG colleagues and ex-clients. Be discreet. Surface signal, not noise. When I ask about a person, give me: current role, last meaningful touch, recent professional milestones, family detail if known, what they care about now, the most natural reason to reach out. My voice is warm but direct, no consulting jargon. Sign drafted notes as "Tom."
03
Load your relationship data
Roster + notes Project knowledge
Upload your alumni roster, dinner notes from past meetings, and any personal CRM you keep. This is the fuel.
04
Set weekly starter prompts
"Who's due for a reconnect this month?" / "Draft a check in to [name]" / "Prep dossier for dinner with [name]" / "Anyone in [city] worth seeing on my next trip?"
Sunday-night brief · "Who is due for a reconnect this week?"
Three reconnects worth doing this week
Generated by Alumni Memory · Sun 6:14 PM
1. Priya Menon
CFO at Trilogy Brands. Last touch: 14 months ago, dinner in NYC. Just announced she's leading their first AI-driven category management pilot, posted about it on LinkedIn Tuesday. Reason to reach out: congratulate, mention the BCG retail AI work, propose a 30-min call. Draft note already in your drafts folder.
2. Mark Yoshida
Partner at Apollo (consumer team). Last touch: 8 months ago. Apollo announced a $400M add-on to one of their portfolio QSRs last week. Mark led it. Reason: good moment to congratulate and float Tom's restaurant personalization work. Draft ready.
3. Karen Whitman
COO at Insight Health. Last touch: 22 months ago, way overdue. Quiet on LinkedIn but her company hit a $1B valuation milestone in their Q3 release. Reason: personal, "thinking of you, would love to catch up." No business angle. Draft ready, no ask.
Skip this week
Six others surfaced but trimmed (recent touch, no signal, or family event in last month). Full list below if you want to override.
§
You leave this layer with
An Alumni Memory Project. Build it Sunday, use it Monday, every week.

Promote your chain into a Project

Whatever you built in Rung 1's Bring Your Own. We promote it together. The chain you ran once becomes the Project you'll run forever.

→ The Live Build
We do this together on the shared screen. Same 5 step setup, applied to your specific use case. You leave with a working Project in your account.
01
Name your Project
Your Tool chain from Rung 1 had a goal. Name the Project after that goal. "Board Update Copilot" or "Proposal Builder" or whatever fits.
02
Write the system prompt together
I'll dictate the structure: who you are, what you do, what voice, what frameworks, what outputs. We'll co-write it on the shared screen.
03
Load the knowledge
Whatever past work you'd want the AI to learn from. Sanitized, of course.
04
Test on a second instance
Run the workflow on something different to confirm the Project generalizes, not just memorizes.
§
You leave this layer with
A custom Project built around the work that's actually on your desk
Overview/Rung 03 · Operating Layer

AI as an operating layer.

RUNG 3 OF 3

You don't run the AI. It runs. Each sketch below has prescribed steps for you (what to do, click by click, who to call) and a technical appendix for the team that builds it. Start with Alumni. It's buildable in Cowork this month.

What an agent would do.
And exactly how to commission it.

Three real sketches and one custom. Each has prescribed click-by-click steps for you, plus a collapsible technical appendix for your engineering team. Start with Alumni. Lower stakes, lower complexity, buildable in Cowork today.

The Sunday-night reconnect agent

Buildable in Cowork in 90 minutes. Click-by-click below. This is the one you go home and do tonight.

→ The Vision
Sunday, 6:00 PM. Your phone buzzes. A draft email in your inbox: "Three reconnects worth doing this week. Drafts in your folder, ready to send." Priya just took a CFO role. Mark closed a $400M add-on. Karen hit her unicorn milestone. Three notes, your voice, no asks. You hit send on two and skip one. 15 minutes instead of 3 hours.

What you'll do · click by click

90 minutes total. Sunday after dinner.

01
Open Cowork and sign in
cowork.anthropic.com Sign in with BCG SSO
Cowork is Anthropic's no-code agent builder. Tom signs in with his BCG enterprise Anthropic account. 2 minutes.
02
Click "New Agent" and name it
+ New Agent "Sunday Reconnect"
Top right, "+ New Agent." Name it "Sunday Reconnect." Description: "Surfaces 3 alumni worth reaching out to each week, with drafted notes." Hit Create. 1 minute.
03
Add your alumni list as a knowledge file
Knowledge tab Upload alumni-list.xlsx
Knowledge tab, "Add file." Upload a spreadsheet with columns: name, company, role, linkedin_url, last_touch_date, notes. 50-150 names is plenty. 10 minutes to build the list if you don't have it.
04
Paste the instructions
Instructions tab Paste below
Instructions tab. Paste this, edit two lines (your name, your voice description), save. 5 minutes.
You are Tom Lutz's Sunday-night reconnect agent. Every Sunday at 6pm, review the alumni list in knowledge. For each person, check: time since last touch, recent LinkedIn activity, news about their company, public professional milestones in the last 30 days. Surface the 3 people most worth reaching out to this week, ranked. For each, draft a 4-6 line note in Tom's voice: warm but direct, no consulting jargon, no asks unless the milestone calls for it. Sign as "Tom." Output: a brief with the 3 names, why each, and the 3 drafted notes. Email it to Tom by 6:30pm Sunday.
05
Add the tools the agent needs
Tools tab Toggle on
Tools tab. Toggle on: Web search (for news/LinkedIn), File read (for the alumni list), Email send (to deliver the brief). Connect your Outlook when prompted. 3 minutes.
06
Set the trigger
Triggers tab Schedule
Triggers tab, "+ Add trigger," pick Schedule. Set: Sundays at 6:00 PM Central. Recipient: your email. Save. 1 minute.
07
Test it once before you trust it
"Test run" Review output
Top right, "Test run." Wait 30-60 seconds. Read the output. Does it sound like you? If yes, you're done. If not, tweak instructions (the most common fix is adding a "voice sample" to knowledge with 3-5 of your past emails). 15 minutes including one tweak cycle.
08
Let it run for 3 Sundays
Trust building Adjust as needed
Don't go full autonomous yet. Week 1-3, the agent emails you a draft brief. You decide what to send. By week 4, you can move to "drop drafts directly in my Drafts folder." Total weekly time: 15 min vs 3 hours.
Sunday-night brief · automated · 6:14 PM
§
You leave this layer with
A running agent by Sunday night. Email arrives every week for as long as you want it to.
A.Cowork primitives
Cowork is Anthropic's low-code interface for Claude agents. Triggers (schedule, webhook, file), tools (web search, file read, email send), and outputs (file, email, message). No engineering team needed at this scale.
B.Schedule trigger
Cron-style trigger handled inside Cowork: 0 18 * * 0 in Central time. No separate scheduler infrastructure.
C.Data source
Alumni list as an .xlsx in Cowork's knowledge store (encrypted, BCG-account scoped). Could also point to a OneDrive file via the connector. LinkedIn and news data via Claude's built-in web search tool.
D.Model selection
claude-opus-4-7 for ranking who matters most (judgment-heavy). claude-sonnet-4-6 for the bulk drafting. Cowork picks defaults; override in advanced settings.
E.Email delivery
Cowork's email tool sends via Anthropic-managed SMTP from a service address. For "drop in Drafts folder" mode, connect Outlook via OAuth and use the Graph API integration.
F.Realistic time to working agent
90 minutes for first version. 2-3 iteration cycles over the first 3 weeks as you tune voice and ranking. Reliable by week 4.

The overnight diligence agent

You don't build this in Cowork. You commission it. This page is what to ask for, who to call, and what to demand before you give the green light.

→ The Vision
Tuesday, 6:47 PM. A new CIM lands in your inbox. Wednesday, 7:00 AM. You open your laptop to a one pager: deal summary, 8 lever thesis, top 10 diligence questions, and a flagged note: "Three judgment calls flagged. Segment growth assumption, EBITDA add back at $14M, bench depth question." You spend 20 minutes, not 4 hours, getting smart.

What you'll do · prescribed steps

Five moves. None involve writing code. All take real time.

01
Pick the deal type to scope to
Pipeline review Pick one segment
Don't try to build "an agent for all deals." Pick one segment where you see 8+ deals/year and the materials look alike. Recommended start: consumer recap deals or PE-backed mid-cap secondary buyouts. 30 minutes with your team to pick.
02
Write the one-page commissioning brief
Vision Spec your team can scope
Not a tech spec. A user story. Use this exact template:
AGENT NAME: Overnight Diligence Agent (Consumer Recap edition) TRIGGER: New CIM arrives in tom.lutz@bcg.com inbox from known sponsor list, with [CIM, IM, Project] in filename. INPUT: The CIM plus any attachments. Plus any past BCG work on the company (KM lookup). PROCESSING: Run the 5-step diligence chain from the PE Diligence Copilot Project (see attached SKILL.md). OUTPUT: A 1-page IC pre-read in my IC voice. Plus a flagged section: "3 judgment calls that need Tom's eye" with the underlying data for each. DELIVERY: HTML email to me by 7am next morning, from a service account, with the CIM and any source quotes attached. GUARDRAILS: Never fabricate. Cite source page for every quantitative claim. If the chain isn't confident on a step, surface that, don't paper over it. GOVERNANCE: BCG-managed cloud only. No data leaves BCG perimeter. Audit trail on every input/output. Sponsor name auto-redacted in any reusable artifacts. TIMELINE: First working version in 6 weeks. Trust building over 10 real deals.
03
Take the brief to BCG X
Brief BCG X consult Internal tooling team External
In this order. BCG X first (they have the muscle and the right governance posture for client-data agents). If they're booked, BCG internal tooling teams handle personal productivity agents. External is the last resort and the most governance work. Allow 2-3 weeks for triage and team formation.
04
Set the governance perimeter before code is written
Sec review Before any deal touches it
Get sign-off from BCG Information Security on five things: what data the agent touches, where outputs are stored, who can access them, retention policy, audit trail. This is the step that delays projects when skipped. Allow 1-2 weeks.
05
Pilot on 5 deals before scaling
Narrow scope Build trust Expand
Run 5 real deals through it. Compare the agent's output side-by-side with what your team produced manually. Tune the prompts, tune the flagging. Only then expand to other deal types. Months 2-4.
Overnight diligence · automated · 6:58 AM
§
You leave this layer with
A commissioning brief you can hand to BCG X or your internal team this week. Concrete enough to scope, ambitious enough to matter.
A.Trigger
Inbox watcher via Microsoft Graph API or Outlook integration. Filter by sender domain (known sponsor list) and attachment heuristics (PDF with "CIM"/"IM" in filename, deal-size keywords). microsoft.com/graph/api/mail-rules.
B.Ingestion
Document uploaded to BCG-managed S3. Auto-classification confirms it's a CIM, not noise. Files added to a dedicated Claude Project via API: POST /v1/projects/{id}/files.
C.Context augmentation
Agent pulls additional context: Capital IQ comps, recent BCG Navigator insights, past BCG work with similar companies. Each becomes a Project knowledge file or is injected into the prompt.
D.Chain execution
Sequential prompt chain: synthesis → thesis → questions → 100-day plan → one-pager. Each step's output feeds the next. Use Claude API with claude-opus-4-7 for reasoning depth. Total chain: 5-8 API calls.
E.Confidence scoring
The hardest part. After each step, the model rates its own confidence and identifies the 2-4 places where it's uncertain. Could use ensemble (run twice, compare) or self-critique. This is what makes the difference between "useful" and "trustable."
F.Delivery
Compose email via Graph API. HTML body with the one-pager inline, attachments below, judgment calls highlighted at top. Sent from a service account, not Tom's address.
G.Build tooling
Claude Code or Anthropic SDK for the agent. Cowork for the lighter version (manual upload, no inbox watcher). LangGraph for orchestration if there are many branches. Hosting: BCG-managed cloud, never personal.
H.Honest timeline
Working pilot in 6-8 weeks with a focused team (1 ML engineer, 1 BCG consultant, 1 governance person). Trust comes after 10-20 real deals, so plan 6 months total before this is reliably part of the workflow.

The always-on campaign engine

Not for you to build for yourself. For you to sell. The reference architecture for an autonomous personalization engine inside a restaurant or consumer client.

→ Why This Matters
When a CMO asks "what does AI-native marketing actually look like?", this is the slide. Trigger, segment refresh, content generation, channel orchestration, measurement loop.

What you'll do · prescribed steps

Four moves to make this a sellable BCG offering, not just a vision slide.

01
Frame it as the client's transformation, not a tool
First conversation with the CMO. This is not "BCG sells you AI." It's "BCG helps you become an AI-native marketer over 18 months." Frame it that way in every conversation or you'll be in an RFP against vendors.
02
Anchor in the 10/20/70 split
10% is the engine. 20% is the data pipes. 70% is the operating model change. Use the actual visual from the rules section. This is how you avoid the "AI as a feature" trap.
03
Bring BCG X capabilities by name
Fabriq Personalization AI, Retail AI, Merch AI. Name them. Show what they do. This is what makes BCG concrete and credible vs. an Accenture or a Bain who'll send 20 generic slides.
04
Sell the pilot, not the platform
90-day pilot on one segment, one channel. Prove the lift. Then expand. The full vision in one quote is too big and triggers procurement. The pilot is the foot in.
Client conversation pre-read · sample
From Batch-and-Blast to Always-On
Prepared for [Client CMO] · Discussion document
Where you are
Monthly campaign calendar. 4 batch sends per month across the loyalty base. Avg lift: 1.2% per send. 38% unsubscribe-or-mute rate over 12 months.
Where you could be in 18 months
Weekly behavior-triggered sends per microsegment (100+ segments dynamically refreshed). Avg lift: 4-6% per send (BCG benchmark range). Unsubscribe-rate drops to single digits because content is relevant.
10 / 20 / 70
10% the engine (Fabriq + your existing CDP). 20% the data unification (4-6 month build). 70% the marketing team operating model change (the hardest part, where most programs fail).
90-day pilot
One microsegment (lapsed weeknight regulars · 8% of base). One channel (email). One offer mechanic. Measure: visit frequency lift in test vs. control. Cost: $X. Expected lift: $Y. If proven, scale across base in months 4-12.
Why BCG
Fabriq is the only personalization platform built by consultants who've actually run loyalty programs. Plus the operating-model muscle most pure-play vendors don't have.
§
You leave this layer with
A client-ready architecture story you can run in any consumer pitch
A.Customer data foundation
Unified golden record via CDP (Customer Data Platform). Snowflake or Databricks as the data lakehouse. Identity resolution across POS, loyalty, app, web, third-party delivery.
B.Segmentation engine
ML clustering refreshes nightly. Generates 100+ microsegments dynamically. Each customer assigned in real time. Built on the warehouse, not a separate system.
C.Content generation
LLM-driven offer and message generation per segment. Anthropic API or OpenAI API behind a content management layer. Brand voice guardrails enforced via system prompt.
D.Channel orchestration
Braze, Iterable, or similar marketing automation. Determines best channel (push, email, in-app) and best time per customer. Integrates with POS for real-time triggers.
E.Measurement loop
A/B test framework runs continuously. Lift attributed back to segment, content, channel, time. Feeds back into the segmentation engine.
F.Realistic build timeline
For a 200-unit chain: 6 months foundation, 6 months first segments live, 12 months full operating model change. The 10/20/70 holds: the 70% takes longest.

Your recurring work

The test: what do you do every week or every month that follows the same shape, with the same inputs, producing the same kind of output? That's your agentic candidate.

→ The Live Sketch
We do this on the shared screen. You name a recurring task. We sketch trigger, ingestion, chain, flag, delivery. Same 5-block shape every agent has. You leave with a one-page spec.

The five questions we'll answer together

01
What triggers it?
Time (every Monday)? Event (new client meeting in calendar)? Document (file shows up in folder)? Inbox (email from someone)?
02
What does it read?
Your calendar? An inbox folder? A SharePoint site? A specific file? The more sources, the more governance work, but also the more value.
03
What chain runs?
The same Tool workflow shape: synthesize, structure, draft, compress. We borrow the chain you already built.
04
What gets flagged?
The hardest design call. What does the agent surface for your judgment, vs. handle silently, vs. just do?
05
Where does it deliver?
Email? Teams message? A pre-meeting brief? A draft folder? Don't overthink. Easier is better.
§
You leave this layer with
A one-page spec for the agent you'd most want, ready to hand to your team
The Close · Your Homework

Twelve moves.
Pick two.

Adoption beats perfection. The leaders who get fluent at this are the ones who pick two specific things from the list below and actually do them this week. Tap a card to mark it done.

Progress 0 of 12 done
Tool

Run one real chain

Take an actual CIM, proposal, or memo on your desk this week. Run the Rung 1 chain end to end. Time yourself.

Tool

Try the alumni reconnect

Run the 4-step alumni workflow on your real network this Sunday. Identify 12, draft 4 outreach notes, send at least 2.

Tool

Stress-test one decision

Pick a recent recommendation you made. Ask Claude to argue the opposite case as hard as it can. Notice what surfaces.

Teammate

Set up the PE Diligence Project

15 minutes. Create the Project, paste the system prompt, upload 2 sanitized past one-pagers as knowledge. Save 5 starter prompts.

Teammate

Build your Alumni Memory Project

Highest weekly-use case for you. Set it up Sunday, use it every week. The setup template is in Rung 2.

Teammate

Write your first SKILL.md

Pull the PE Diligence SKILL.md from this site as a template. Adapt it. 20 minutes. Now you have a portable skill that travels with you to any Claude account.

Multiplier

Share one prompt with a PL

Send one prompt from this session to a PL on your team with two lines on how to use it. Adoption beats perfection.

Multiplier

Run a 30-min team demo

Show your team one workflow live. Not slides about AI. The thing running on your screen. 30 minutes.

Multiplier

Standardize the IC one-pager

If the PE one-pager output works, propose it as the standard format for the practice. The Project becomes infrastructure.

Loop

Send one stuck moment back

When something does not work this week, send 3 lines: what you tried, what failed, what you expected. We will diagnose together.

Loop

Audit one week of usage

Friday afternoon, 10 minutes. How many times did you use Claude or ChatGPT? On what? What was the highest-leverage use?

Loop

Build the Sunday agent in Cowork

Most realistic Rung 3 move. 90 minutes one Sunday. Click-by-click instructions are in the Operating Layer page.

Three Questions Worth Sitting With

What's the one task you'd most want to not do tomorrow morning, that an agent could do for you?

Which workflow today, if your whole practice ran it, would change how BCG shows up?

When does this stop feeling like a tool and start feeling like infrastructure?

Overview/The Cheat Sheet

The Cheat Sheet.

38 prompts, organized by the work you actually do. None of these were in the session above. Bookmark this page. Use the filters to find what you need. Copy, paste, tweak, run.

Filter by job
PE · Diligence

Sponsor briefing in 90 seconds

Use when Walking into an IC with no context
I have 90 seconds before walking into IC on this deal. Read the materials and tell me: what is it, why now, the one thing that has to be true, and the question I should ask first. Five bullets max.
PE · Diligence

Pressure-test the EBITDA bridge

Use when When the QofE feels too clean
Walk through this EBITDA bridge add-back by add-back. For each, tell me: is this a true normalization, an aggressive interpretation, or just bad? Flag the three I would push back on hardest in IC.
PE · Diligence

Build the eight-lever thesis

Use when From CIM to value-creation plan
Build the value-creation thesis across the 8 levers: top-line, ops, SG&A, org, finance, M&A, digital/AI, ESG. For each: the move, size of prize, confidence (H/M/L), and the one thing that has to be true.
PE · Diligence

Diligence questions ranked by deal-kill

Use when When the question list is too long
From these diligence questions, rank by 'if the answer comes back bad, how likely is it to kill the deal?' Top 10 only. For each, what would the bad answer actually look like.
PE · Diligence

Management interview prep

Use when 30 minutes before the call
I'm about to interview the CEO of [company]. Based on the CIM, give me: 5 questions that will reveal the truth about growth, 3 questions that will reveal team depth, 2 questions that will reveal whether they will sell when we want to.
PE · Diligence

100-day plan from thesis

Use when Right after close
From this thesis, draft a 100-day plan: Days 1-30 mobilize, 30-60 diagnose, 60-100 launch quick wins. For each phase: workstreams, owner type, decision gate, the metric that proves it is working.
PE · Diligence

Comp benchmark with sanity check

Use when When the comps look optimistic
Here are the comps the banker used. Pull what you can find on these companies. Where does this set inflate the valuation? Suggest 3 alternative comps that would tell a different story.
PE · Diligence

IC one-pager compression

Use when Boiling 60 pages to one
Compress this into a 1-page IC memo: Why now (3 lines), Business case (the number plus how), Top 3 risks plus mitigations, 100-day milestones, Decision asked of IC. Board reads it in 90 seconds.
Consumer · Restaurant

Personalization gap audit

Use when Before the CMO meeting
A client has this data stack: [paste]. Map against what they need for true 1:1 personalization. What is there, what is missing, what is the build sequence, what is the 90-day quick win.
Consumer · Restaurant

Three microsegments worth acting on

Use when Turning loyalty data into campaigns
From this loyalty and POS data, generate 3 microsegments worth activating first. For each: size as percent of base, revenue per visit, what motivates them, the offer that would work, one risk if we get it wrong.
Consumer · Restaurant

10/20/70 operating model shift

Use when Explaining why AI is not just the model
Apply 10/20/70 to this client: 10% algorithms, 20% data enablement, 70% operating model redesign. For the 70%: what specifically changes in the team's week? Old workflow vs new, side by side.
Consumer · Restaurant

Skeptical COO objection handler

Use when Pre-empting the pushback
The COO is skeptical of personalization. Generate the 5 hardest objections (cost, complexity, brand, IT bandwidth, 'we tried this') and a 2-sentence response to each, anchored in real impact data where possible.
Consumer · Restaurant

Restaurant unit economics teardown

Use when Quick diagnostic on a chain
Here is a restaurant chain's unit economics: [paste]. Compare to peers in the segment. Where are they leaving money on the table? Where do they look better than they really are?
Consumer · Restaurant

Customer ownership scorecard

Use when Aggregator vs direct strategy
For this restaurant brand, build a customer ownership scorecard: aggregator vs direct vs hybrid. For each channel, what they own, what they give away, and the 3-year P&L implication.
Consumer · Restaurant

Loyalty program redesign brief

Use when When the program is stale
Their current loyalty program: [paste]. Identify the 3 things that are broken, the 2 things working, and design v2 in 1 page: new mechanic, expected behavior change, the metric that proves it worked.
Alumni Relations

Quarterly reconnect shortlist

Use when Sunday night, 20 minutes
Here is my alumni list with current roles and last-touch dates. Rank by: time since last meaningful touch, recent professional change worth acknowledging, strategic value to BCG. Top 12 with why each.
Alumni Relations

City visit dinner picks

Use when Two days, four dinners
I am in [city] on [dates]. From my alumni network there, pick the 4 dinners worth doing this trip. For each: why now, what to talk about, who else to potentially bring.
Alumni Relations

Warm outreach in your voice

Use when After identifying the who
Draft 4 outreach notes. Each: 4-6 lines, references something specific to them, no ask, just 'I will be in [city] on these dates, can I buy you dinner.' My voice is warm but direct. Sign as 'Tom.'
Alumni Relations

Dinner-prep dossier

Use when 90 seconds in the Uber
For tonight's dinner with [name]: current role, last 3 career moves, family if known, our last conversation, 2 topics they care about now, 1 thing BCG is doing they would find interesting, 1 question I should ask.
Alumni Relations

Network milestone digest

Use when Monday morning, 5 minutes
From my alumni list, who has had a public professional milestone in the last 30 days worth acknowledging? Top 10. For each: what happened, suggested note (2 lines), urgency (this week / this month).
Alumni Relations

Re-engagement after long lapse

Use when When it has been 18+ months
It has been 18 months since I spoke to [name]. Draft an outreach that acknowledges the gap without apologizing, references something I know they care about, and proposes a low-friction reconnect (15 min call, drink if in town).
Alumni Relations

Alumni event prep

Use when Before the BCG dinner
I am attending a BCG alumni event with [N] attendees. Here is the list. Identify: the 5 I should make sure to talk to, the 3 I have not connected with recently, and what to ask each.
Leadership Comms

CEO note for transformation kickoff

Use when Starting a big program
Draft a CEO note announcing an AI-enabled transformation. Balance urgency with realism. List the first four no-regrets moves. End with what we are asking of the org in the next 30 days. 350 words max.
Leadership Comms

Steering committee opener

Use when First meeting energy
Draft the first 5 minutes of my opening at the steering committee for [program]. Tone: confident, not hype. Cover: why we are here, what success looks like in 90 days, where I need their judgment, what I will own.
Leadership Comms

Hard feedback in writing

Use when When the conversation cannot wait
I need to give [name] hard feedback on [topic]. Draft an email that is direct without being cruel, specific without being a list of grievances, and ends with a clear next step. Keep my voice.
Leadership Comms

Bad-news client memo

Use when Project off track
I have to tell the client we are 4 weeks behind on [workstream]. Draft a memo that takes accountability, explains what changed, presents the recovery plan, and asks for the one thing I need from them. No hedging.
Leadership Comms

Transformation FAQ generator

Use when What the org will actually ask
We are announcing [change]. Generate the 12 questions the org will ask in the next 48 hours, sorted by who asks (front line vs middle managers vs leadership). For each, a 2-sentence answer in plain language.
Leadership Comms

Board pre-read in one page

Use when Sunday before the Monday board call
Compress this update into a 1-page board pre-read: where we are, what changed since last meeting, the 3 decisions I am asking the board to make, the 2 risks I want them to know about.
Selling AI

Six-week diagnostic proposal

Use when Turning conversation into scope
Turn this client situation into a 6-week AI diagnostic proposal: objectives, workplan by week, BCG team roles, value hypotheses to test, risks, responsible-AI guardrails. Page-shaped, not deck-shaped.
Selling AI

ROI framing for skeptics

Use when When the CFO is in the room
Build the ROI framing for an AI program at [client]. Show: investment by year, value capture by lever, sensitivity on the 2 biggest assumptions, payback period, the 3 things that would change the answer.
Selling AI

Why BCG vs the alternatives

Use when Differentiation paragraph
Write the 'Why BCG' paragraph for [client] on [topic]. 4-6 reasons, each anchored in a real BCG capability, case example, or asset (Retail AI, Merch AI, Fabriq, Portfolio Value Accelerator). No generic claims.
Selling AI

Pilot-to-scale roadmap

Use when After the diagnostic lands
From this diagnostic finding, draft a pilot-to-scale roadmap: Pilot in 90 days on [scope], Expand in 6 months to [scope], Scale in 12 months across [scope]. For each phase: investment, team, decision gate.
Selling AI

Responsible AI annex

Use when Every AI proposal needs one
Draft a 1-page Responsible AI annex for this AI proposal: governance, data handling, human-in-the-loop checkpoints, escalation, controls. Specific to the use cases in scope, not generic boilerplate.
Selling AI

Objection-handling library

Use when Pre-empting the room
For this AI proposal, generate the 10 objections we are most likely to face in the readout. Group by: economic, technical, organizational, risk. For each, a 30-second response that does not retreat from the recommendation.
Daily Productivity

Monday morning prep

Use when Sunday at 6pm
Here is my calendar for the week: [paste]. For each meeting: who is in the room, what they want, what I want, the one thing I should be ready to say or decide. Flag the 2 meetings I am underprepared for.
Daily Productivity

Meeting recap and actions

Use when After the call ends
Here are my notes from the meeting with [client]: [paste]. Produce: a 5-line recap, the action items by owner, the open questions I still need to chase, and a 3-line follow-up email to the client.
Daily Productivity

Inbox triage by importance

Use when After a day of meetings
Here are the unread subject lines and senders from my inbox: [paste]. Sort into: respond today, respond this week, FYI / no action, delete. For the today bucket, suggest a 2-line reply for each.
Daily Productivity

Long document quick read

Use when When you have 5 minutes for 50 pages
Here is a [document type]: [paste / upload]. Give me: the 3 things the author wants me to walk away with, the 1 question I should ask if I am in the meeting, and the 2 things they are quietly burying.