tractatus/docs/outreach/FEEDBACK-REQUEST-EMAIL-TEMPLATE.md

Email Template: Request for Executive Brief Feedback

To: [Expert Reviewer - e.g., BI Professional, CTO, Governance Researcher] Subject: Quick feedback request: AI Governance ROI brief (2 pages)

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Template for Original Feedback Provider (BI Expert)

Subject: Thank you - here's the 2-page version you asked for

Hi [Name],

Thank you for your feedback on the governance BI document. You were absolutely right - I buried the core message under 8,500 words of technical detail.

You said: "Just need a few simple statements in English."

Here it is (attached PDF, 2 pages):

The Simple Version:

Problem: Organizations don't adopt AI governance frameworks because executives can't see ROI in dollars.

Solution: Automatic classification of AI work by risk level + cost calculator = "This framework prevented $XXX in security incidents this month"

Status: Research prototype. Cost numbers are illustrative placeholders. Methodology is sound; values need organizational validation.

Your question about intuition is profound. I added a section addressing: Can BI tools augment human judgment rather than replace it? Your comment about hiring for "je ne sais quoi" pattern recognition helped me clarify the positioning: machines handle routine classification, humans apply expert judgment to complex cases.

I need your help: Would you read the attached brief (2 pages, ~5 minutes) and tell me:

1. Does this answer: What problem? What solution? What status?
2. Is it clear in "simple English" or still too complex?
3. Does the AI + Human Intuition section address your concern about replacement vs augmentation?

No pressure - even "Yes/No/Maybe" on those 3 questions would be incredibly helpful.

If this version makes sense, I'll use it as the foundation for outreach. If it's still unclear, I'll keep iterating.

Thank you for taking the time. This feedback is exactly what I needed.

Best, [Your name]

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Template for Additional Expert Reviewers (CTOs, Governance Researchers)

Subject: Request for feedback: AI Governance ROI brief (5-min read)

Hi [Name],

I'm working on a research project exploring whether AI governance framework value can be quantified in financial terms.

Quick context: Organizations don't adopt governance frameworks because ROI is intangible. I've built a prototype that automatically classifies AI work by risk level and calculates "cost avoided" when violations are prevented.

I need expert feedback on whether the value proposition is clear.

Attached: 2-page executive brief (~5 minutes to read)

What I'm asking:

Would you read the brief and answer these 3 questions?

1. Does this clearly explain: What problem? What solution? What status?
2. Is the business case compelling or missing key elements?
3. What's your biggest concern about this approach?

No obligation - even a quick "Yes/No/Needs work" would be valuable.

Why your feedback matters: [Personalize based on their expertise]

• BI professionals: Validating cost calculation methodology
• CTOs: Validating business case and metrics
• Governance researchers: Validating classification approach

Timeline: I'm seeking feedback by November 3 to decide whether to proceed with public launch. If 80%+ of reviewers say "the problem/solution is clear," I'll move forward. If not, I'll iterate further.

Thank you for considering. Happy to return the favor if you ever need expert review.

Best, [Your name]

P.S. If you're interested in piloting this (30-90 day trial in your organization), let me know - we're seeking validation partners.

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Template for Industry Collaborators (Insurance, Legal, Audit)

Subject: Research collaboration opportunity: AI governance cost modeling

Hi [Name],

I'm researching whether AI governance framework ROI can be quantified using industry-standard incident cost models.

The concept: When governance prevents a security violation, classify it by severity (Critical/High/Medium/Low) and calculate cost avoided using validated incident cost factors.

Where I need help: Current cost factors are educated guesses from public reports (Ponemon, IBM). I need:

• Insurance companies: Actual claim data for cyber incidents
• Legal firms: Regulatory fine schedules by violation type
• Audit firms: Compliance remediation cost benchmarks

What I'm offering:

• Co-authorship on methodology paper (targeting ACM FAccT or IEEE Software)
• Early access to pilot data from organizations using the tool
• Citation in research publications

Attached: 2-page executive brief explaining the approach

Would you be interested in a 15-minute call to explore collaboration?

Timeline: Seeking to validate methodology by February 2026, with pilot studies starting December 2025.

Thank you for considering.

Best, [Your name]

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Validation Tracker

Goal: 80%+ of reviewers confirm "problem/solution is clear"

Reviewer Name	Role	Sent Date	Response Date	Clear (Y/N)?	Biggest Concern	Next Action
[BI Expert - original feedback]	Former BI Exec	[Date]
[Reviewer 2]	CTO	[Date]
[Reviewer 3]	Governance Researcher	[Date]
[Reviewer 4]	BI Professional	[Date]
[Reviewer 5]	Technical Lead	[Date]
...

Success Criteria: If ≥ 80% say "Clear" → Proceed with launch Iteration Criteria: If < 80% → Revise based on "Biggest Concern" themes

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Response Handling Guide

If Feedback: "Still too complex"

Action: Create even simpler 1-page version Focus: Problem/Solution/Status in 3 paragraphs max Example: "Governance prevents incidents. We calculate cost. Here's ROI."

If Feedback: "Business case unclear"

Action: Add more concrete examples with dollar amounts Focus: "Framework blocked credential exposure → Prevented $50k data breach"

If Feedback: "Status confusing"

Action: Stronger distinction between "operational prototype" vs "commercial product" Focus: "Works in our dev environment. Not yet validated for production use."

If Feedback: "AI replacing intuition" still a concern

Action: Expand that section, add specific examples of human override scenarios Focus: "Machine flags 100 cases. Human reviews, overrides 15 as false positives. System learns."

If Feedback: "Cost model questionable"

Action: Emphasize configurability, de-emphasize default values Focus: "Organizations set their own cost factors. Defaults are placeholders only."

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Follow-Up Timeline

Day 0 (Today): Send to 5-10 expert reviewers Day 3: Send gentle reminder to non-responders Day 7: Analyze responses, identify themes Day 8-10: Revise brief based on feedback (if needed) Day 11: Decision point - proceed with launch or iterate further

Target: November 3, 2025 decision on whether to proceed with Week 1 launch

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Version: 1.0 Created: 2025-10-27 Purpose: Guide expert feedback collection for Executive Brief validation