Case Study 27-1: Elena's Proposal Machine — From Discovery Call to Proposal in 3 Hours
The Challenge: Convert a 45-minute discovery conversation into a compelling, tailored proposal within 3 hours — while managing two other active client engagements.
Context
It's Wednesday afternoon. Elena has just finished a 45-minute discovery call with Northgate Technology Services, a 250-person IT consulting firm looking to improve their leadership pipeline. The conversation went well — the head of HR and the CEO were both on the call, the problems they described are squarely in Elena's practice area, and they've asked for a proposal by Friday.
Elena has two existing client deliverables due Thursday. She has perhaps three hours today and Friday morning. A full proposal from scratch would normally take her 4-5 hours. She needs a faster workflow.
What she has from the call: 4 pages of rough notes.
Step 1: Converting Discovery Notes to Proposal Brief (15 minutes)
Elena's discovery notes are honest reflections of a real conversation: fragmented, partially captured, full of her own asides ("CEO seems skeptical of formal training — probe this"), and organized around the order of the conversation rather than the order of a proposal.
She does not try to organize them first. She pastes them directly into her "brief me" prompt:
Here are my rough notes from a discovery conversation with a potential client:
[pasted notes — includes fragments like "250 people," "leadership pipeline 'creaking,'" "mid-level managers promoted for technical skills not leadership," "high turnover in senior associate level — CEO said 'losing our best people to competitors,'" "COO mentioned comp issues but CEO pushed back — not primarily a comp problem," "training budget exists but been spent on vendor compliance stuff," "CEO said 'don't want another training program that doesn't stick'"]
The prospect is: Northgate Technology Services, IT consulting firm, 250 people They want: leadership pipeline development My proposed solution: [I'll fill this in, but likely a 6-month leadership development program combining group cohort work and individual coaching] Proposal deadline: Friday
From these notes, help me draft a proposal brief that I can use as the foundation for a full proposal. Include: 1. Their situation (what I understand about their context) 2. The core problem as I understand it 3. The business impact of the problem (based on what they told me) 4. What they're looking for in a solution (based on what they said) 5. Key objections or concerns I'll need to address (based on my notes) 6. Questions I should clarify before or in the proposal
AI's output gives Elena a structured brief in about 90 seconds. Two things stand out in the output that she hadn't explicitly noticed in her own notes:
First, AI synthesizes the turnover comment with the promotion pattern: "The firm appears to be experiencing a classic 'technical-to-managerial' transition problem: high performers are promoted for technical excellence but not prepared for people management, leading to both their own disengagement and the attrition of the people they manage. The 'losing our best people' comment from the CEO likely refers to senior associates leaving because of poor management experiences, not because of compensation."
Elena reads this and realizes she'd seen both data points separately but hadn't explicitly connected them. She marks this insight — it's going in the executive summary as her core diagnosis.
Second, AI flags: "The CEO's statement 'don't want another training program that doesn't stick' signals prior negative experience with training investments. Your proposal needs to directly address sustainability and embedding — not just the program design."
Elena adds this to her "objections to address" list.
Step 2: Proposal Structure (20 minutes)
With the brief in hand, Elena runs the proposal structure prompt:
Using this discovery brief, create a proposal structure for a leadership development engagement with Northgate Technology Services.
[paste brief]
Key information: - Proposed solution: 6-month leadership development program, combining monthly group cohort sessions (full day) with individual coaching (biweekly, 45 minutes) - My differentiator: I don't use off-the-shelf programs; every program is customized based on a diagnostic phase - Target participants: 15-20 mid-level managers - Investment: approximately $85,000 (I'll include the exact number in the pricing section)
The proposal should: - Lead with their problem, specifically the turnover-leadership connection - Address the CEO's concern about training that "doesn't stick" directly - Distinguish my approach from generic training vendors - Be specific about what I deliver, not just what I do
AI generates a 7-section structure: 1. The Situation at Northgate (diagnoses the problem) 2. What's at Stake (quantifies the cost of the current pattern) 3. What a Sustainable Solution Looks Like (addresses the "doesn't stick" concern before presenting the solution) 4. My Approach: The Leadership Foundations Program (customization and diagnostic process) 5. What You'll Receive (specific deliverables) 6. Investment and Timeline 7. Why This Works (outcomes from comparable engagements)
Elena notes: Section 3 is smart — addressing the "doesn't stick" concern before presenting the solution reframes the conversation from "here's my program" to "here's why I understand the problem you've had with programs." She keeps this structure entirely.
Step 3: Content Generation (60 minutes)
Elena runs section-by-section content generation. She provides AI with the specific content for each section but asks it to shape the language:
For Section 1 (The Situation):
Write Section 1 of the proposal based on this understanding of their situation:
[paste the relevant part of the brief]
Tone: Demonstrates that I've listened carefully and understand their specific situation. Not generic leadership platitudes — this should feel like I'm describing Northgate specifically. 200-300 words.
Important: Include the connection between the promotion pattern and the turnover. This should feel like an insight, not a list of their problems back at them.
AI's draft is good but slightly too long (380 words). Elena cuts it to 250, removes one sentence that sounds like a generic consulting description, and adds a sentence specifically referencing the CEO's language about "losing our best people" — a callback to the conversation that signals she was listening.
For Section 3 (What a Sustainable Solution Looks Like):
Write a section that directly addresses the client's concern about training that "doesn't stick." They've had bad experiences with training investments before.
This section should: - Acknowledge the valid frustration with training that doesn't change behavior - Explain what makes the difference between programs that stick and ones that don't (embedding, manager accountability, observable behavior change) - Position my diagnostic-first approach as the reason this program will be different
Do NOT mention my specific program yet — this section should make the case for what good looks like before I describe what I offer. 200-250 words.
This is the section Elena spends the most time editing. AI's first draft is accurate but slightly academic. She rewrites three sentences to make them more concrete: instead of "behavior change requires sustained reinforcement," she writes: "The managers you develop need to use new skills with their teams the week after the session — not six months later during a follow-up training day." More specific. More credible.
For Section 5 (What You'll Receive):
Create a deliverables list for a 6-month leadership development program including: - Monthly cohort sessions (full day, 15-20 participants) - Biweekly individual coaching (45 min per participant) - Diagnostic phase at program start - Progress reporting to HR and CEO at 3-month and 6-month marks - Participant handbook and resource library
Format as a detailed deliverable list. For each item, include: - What it is - What purpose it serves - What the participant/organization receives from it
AI generates a clean deliverables table. Elena reviews each item. She removes one AI-suggested deliverable (a 360-degree feedback process) that she doesn't typically include in this format and adds a note to the coaching deliverable specifying her approach: "Coaching sessions are focused on current real situations, not case studies."
Step 4: The Pricing and Closing Sections (30 minutes)
The pricing section is the one Elena never asks AI to draft. She builds it herself:
- Discovery and diagnostic phase (2 weeks): $8,500
- Monthly cohort sessions × 6: $36,000
- Individual coaching × 20 participants × biweekly × 6 months: $36,000
- Progress reporting and HR advisory: $4,500
- Total investment: $85,000
She uses AI for the pricing framing:
I need to present $85,000 as the investment for a 6-month leadership development program.
Context: 250-person IT firm. High turnover at the senior associate level — they've lost several people they describe as their best talent. Rough cost of losing one senior associate (recruiting + lost productivity + client relationship impact): $80,000-$120,000 per departure.
Write a pricing section that: - Anchors the investment to the cost of the turnover they're trying to address - Presents the $85,000 as specific (itemized) rather than a round number - Includes a payment schedule - Is confident about the price without over-explaining it
AI's framing draft: "The investment in the Leadership Foundations Program is $85,000 over six months, structured as follows: [itemized breakdown]. To put this in context: based on your current retention challenge, the cost of replacing a single senior associate ranges from $80,000 to over $100,000. Retaining two or three people who would otherwise leave is enough to pay for the program many times over — and the compounding benefit of a stronger leadership culture continues long after the engagement ends."
Elena accepts this framing with one change: she removes "many times over" as too salesy for her style. She keeps everything else.
Step 5: Review and Personalization (30 minutes)
With all sections drafted, Elena reads the proposal from beginning to end. Her personalization pass:
What AI got right: The core structure, the objection-handling sequence, the business case framing, the deliverables clarity.
What Elena adds: - Opening paragraph: adds a specific reference to "the conversation on Wednesday" and thanks them for their candor — AI had no way to write this - Section 1: adds the phrase "architecture firm growing through acquisition" to describe their situation more precisely — she'd noted this detail but AI had generalized away from it - Section 7: adds two case study references from comparable engagements — anonymized ("an IT services firm of similar size in the Northeast") but real - Closing paragraph: adds her personal contact information and a specific commitment: "I'm available for a 30-minute conversation before your Friday deadline if any questions arise"
She reviews once more for "robot language" — reads aloud, marks three sentences, rewrites them.
Final proposal: 7 pages, approximately 2,200 words. Total time: 2 hours 55 minutes.
The Outcome
The proposal lands in the client's inbox at 4:45 PM Wednesday — less than three hours after the call ended. The HR head responds within 30 minutes: "This is remarkably well-tailored to our situation. We'll discuss internally and get back to you by Thursday."
Thursday morning, the CEO emails directly: "The section on training that sticks vs. doesn't — you clearly understand what went wrong with our last vendor. When can we talk?"
The engagement is confirmed Friday afternoon.
What the Workflow Contributed
Elena's reflection:
"The 3-hour proposal is not a magic trick — I'd done 45 minutes of excellent discovery before I started writing. The proposal quality depends completely on the quality of the listening that precedes it.
What AI gave me was structure speed. The proposal skeleton — the logical sequence of sections, the objection-handling structure, the deliverables format — was ready in 20 minutes. Without AI, I'd have spent at least 90 minutes on structure alone.
The sections that required the most editing — Section 1 and Section 3 — were the sections that required the most knowledge of this specific client. The AI had the brief I gave it; it didn't have the full conversation. Every place in the proposal where Northgate's specific situation shows through clearly is a place I edited in. The places that are more generic are places I let AI's first draft stand.
That's the pattern: AI owns the structure and the standard language. I own the insight and the specific. Neither alone would have produced a proposal worth winning."
The Proposal That Didn't Win: A Contrast
Three weeks earlier, Elena had sent a proposal to a similar-sized firm using her old workflow — four days to draft, longer, more comprehensive, and organized around what she delivers rather than what the client needs. She lost that engagement to a larger firm.
In her retrospective, Elena notes: "The proposal I lost was more comprehensive than the one I won. It was also more about me. The AI-assisted proposal is more about them — because the workflow started with their brief, not with my service description. That's not AI being smarter. That's me building a better discipline."