portable-identity-document-template-OPEN/PID-Template.md

Personal Identity Document (PID) Template

Overview

The sections that follow are a suggested format, not a rigid template. You may structure this document in a way that works best for you, but be sure to capture the key elements outlined.

Refer to the appendix for additional guidance on how to make your profile distinctive and meaningful.

Getting Started (Recommended)

Follow the instructions in the README.md file.

Privacy Guidance

Do not include sensitive identifiers, like email or specific addresses. City/State/Country is fine.

URL-Accessible

This is important. Make sure you save this to your Google Drive, Microsoft Onedrive accounts, Git accounts or if a PDF, to cloud storage account. Make them public, allowing you to generate a URL that can be shared. That way, you share the URL only, which allows you to update this document. Do not share a static version of this that will go out of date.

1. OPEN TO

• Partnerships

• Hiring talent

• Being hired

• Advisory roles

• Collaboration

• Investment / Funding

• Mentorship

• Learning / exploration

2. WHAT I HAVE

• Skills & Expertise:

• Tools / Technology:

• Network / Relationships:

• Data / Content:

• Physical Assets:

• Platforms / Systems:

• Capital / Access:

• Products/Services: if you own a business or work for one, list them. Ask AI to to do it for you and tell it to include schema to help describe the product data better.

Reference the Asset Stack in this document to be thorough about what you have that others can leverage. https://docs.google.com/document/d/1_citc66qAkKL2IXAuPOvnor9P0hfxQbZ2z8daQnCxNQ/edit?usp=sharing

3. WHAT I NEED

• Immediate Needs:

• Strategic Needs:

• Constraints / Gaps:

• Examples:

  • Talent

  • Capital

  • Partnerships

  • Distribution

  • Technical support

  • Feedback / validation

  • Access (markets, networks, tools)

4. CURRENT FOCUS

• Projects:

• Experiments:

• Research:

• Business initiatives:

5. INTERESTS, PASSIONS, TALENTS

• Topics:

• Industries:

• Technologies:

• Problems:

• Curiosities:

6. HISTORY

• Experience:

• Projects:

• Education:

• Affiliations:

7. CREDIBILITY

• Endorsements:

• Certifications:

• Events:

• Media:

• Publications:

• Your websites (you own or manage or participate in as an author):

• Your platforms in which you participate (X, LinkedIn, Substack, etc):

• Other platforms where you are published or referenced

8. IDENTITY LAYER

• Values:

• Principles:

• Strengths:

• Weaknesses:

• Energy Patterns:

• Work Style:

• Superpowers:

9. PROOF OF WORK

• Builds:

• Results:

• Experiments:

• Case Studies:

• Artifacts:

ADDITIONAL SIGNALS

Low-structure, but high-signal data that is extremely valuable for AI interpretations

• Quotes important to me

• Frameworks: mental models, systems, methods

• Beliefs: perspectives on the world, industry, future

• Ideas: concepts I am exploring

• Writing samples: long-form or short-form expression

• Questions:

• Excitement:

• Predictions:

• Recommendations:

• Insights:

• Learnings:

• Upcoming events I’m attending

• Observations: What are you actually seeing? Not what the headlines say, but what you see. And, just as important, what are you doing about it as a result? Success often lies in early signals, unique patterns, and context-rich insights...the kinds of information traditional sources tend to overlook. These valuable fragments typically emerge from primary, on-the-ground observations and lived experience. Submit what you are seeing, hearing and experiencing. AI won’t just passively observe and collect this information through full access to our digital lives, they’ll also become active stewards of our insights. We’ll be able to submit reflections, anecdotes, and observations directly to our agents, who will then determine when and how to share them within our network. This creates a dynamic layer of decentralized intelligence: a continuous, real-time flow of first-hand signals being exchanged among trusted agents. Over time, the network becomes smarter, more relevant, and more valuable, not just because of the data it holds, but because of the context and intentionality behind it.

• Applied Knowledge & Recommendations: One of the most valuable forms of knowledge is real-world experience. Consider documenting products, tools, services, workflows, books, courses, vendors, communities, and experiences you have personally used and would recommend (or avoid), along with brief notes on why. Unlike anonymous reviews, these recommendations are connected to your actual background, expertise, environment, and results, making them far more useful to both people and AI systems. Over time, this creates a machine-readable knowledge layer that helps others learn from lived experience rather than marketing.

Consider exporting your social posts and dumping into this document.

MATCH CONTEXT

• Ideal Collaborators:

• Ideal Problems:

• Non-Ideal Matches:

UPDATE LOG

• Date + updates: what is happening now in my life that helps AI understand me.

APPENDIX

Core Principle

AI does not infer uniqueness well unless it is explicitly encoded, repeated, and structured. Your “essence” must be machine-legible, not implied.

Elements of a Strong, AI-Distinctive Identity (PID Layer)

1. Clear Category Anchoring (But Not Generic)

Define what you are in precise, recognizable terms

• Avoid vague categories like:

  • “I work in marketing”

  • “I’m in customer service”

  • “I own a consulting firm”

  • “I am an innovative brand”

• Instead:

  • “Email marketing manager for outdoor brands focused on repeat purchase”

  • “Customer support specialist for subscription-based pet products”

  • “Residential electrician specializing in older home rewiring”

  • “Whitewater river guide for beginner and family rafting trips”

  • “Retail associate focused on fitting hiking footwear for long-distance comfort”

  • “AI-native paddlesports industry indexing platform”

  • “positive reinforcement, relationship-based dog training system”

AI uses this to place you in a graph, so precision matters.

2. Differentiation Statement (Non-Optional)

Every person should explicitly answer:

• What do you do that others in your category do not?

• What is your unique mechanism, dataset, or approach?

Structure:

• “I am the only ___ that ___ using ___”

Example pattern:

Marketing

• “I am the only email marketer in my company focused on increasing repeat purchases using post-purchase behavior tracking.”

Sales

• “I am the only sales rep who specializes in reactivating inactive customers using personalized follow-up sequences.”

Customer Service

• “I am the only support specialist who tracks recurring issues and feeds them back into product improvements.”

Accounting / Finance

• “I am the only bookkeeper who organizes financials specifically to help small businesses understand cash flow week-to-week.”

Electrician

• “I am the only electrician in my area focused on upgrading older homes safely without requiring full rewiring.”

River Guide

• “I am the only guide on our team who specializes in helping first-time rafters feel confident before we even leave the shore.”

Retail

• “I am the only associate who focuses on making sure customers leave with the right fit, even if it takes multiple tries.”

Software

• I am the only system designer converting fragmented business and behavioral data into AI-ready, schema-driven JSON objects that can be directly consumed by agents.

Without this, AI collapses you into competitors.

3. Named Systems / Frameworks (Critical Signal Boost)

From your document: structured naming increases findability.

Encourage:

• Named methodologies

• Named frameworks

• Named processes

Examples:

Marketing

• “30-Day Repeat Purchase System”

Sales

• “Dormant Customer Reactivation Process”

Customer Service

• “First Response Confidence Method”

Finance

• “Weekly Cash Clarity System”

Electrician

• “Safe Panel Upgrade Process”

River Guide

• “Calm Start Briefing System”

Retail

• “Perfect Fit Process”

Software

• “CIS Metadata Envelope”

Names act as anchors AI can latch onto and recall.

4. Vocabulary Ownership

Use consistent, repeated terminology across all content.

Define:

• Key terms you “own”

• Phrases unique to your system

Examples:

Marketing

• “Turn first-time buyers into repeat customers”

Sales

• “No lead left behind”

Customer Service

• “Solve it on the first response”

Finance

• “Know your cash every week”

Electrician

• “Safe, clean, done right”

River Guide

• “Confidence before current”

Retail

• “Fit first, always”

Software

• “AI-native data-defined systems”

AI learns patterns through repetition—this builds identity weight.

5. Explicit Capabilities (Not Implied Skills)

Do not assume AI will infer what you can do.

List explicitly:

• What problems you solve

• What outputs you produce

• What actions you enable

Weak:

• “Good with customers”

• “Handles finances”

• “Does installs”

Strong:

Marketing

• “Builds and manages email campaigns that increase repeat purchases”

Sales

• “Converts inbound leads and reactivates past customers”

Customer Service

• “Resolves issues, processes refunds, and identifies repeat problems”

Finance

• “Tracks expenses, manages invoices, and reports weekly cash position”

Electrician

• “Installs panels, troubleshoots wiring issues, and upgrades outdated systems”

River Guide

• “Leads groups safely down river, gives instructions, and manages risk”

Retail

• “Helps customers select products, ensures proper fit, and completes transactions”

Software:

• “Transforms raw industry data into structured, queryable JSON for AI agents”

Think in terms of functions, not descriptions.

*6. Inputs → Transformation → Outputs (Machine-Friendly)

Describe your system like a pipeline:

• Inputs: what you take in

• Transformation: what you do

• Outputs: what comes out

Marketing

• Input: customer purchase data

• Transformation: segment + targeted emails

• Output: repeat purchases

Sales

• Input: inbound leads

• Transformation: qualification + follow-up

• Output: closed deals

Customer Service

• Input: customer issues

• Transformation: diagnose + resolve

• Output: satisfied customer

Finance

• Input: transactions

• Transformation: categorize + reconcile

• Output: clear financial reports

Electrician

• Input: home electrical problem

• Transformation: diagnose + repair/upgrade

• Output: safe, functioning system

River Guide

• Input: group of clients

• Transformation: instruction + navigation

• Output: safe, enjoyable trip

Retail

• Input: customer need

• Transformation: recommend + fit

• Output: correct purchase

Software:

• Inputs: paddlesports company data

• Transformation: structured ontology + tagging

• Outputs: AI-queryable industry index

This aligns with how AI models reason about systems.

7. Audience + Use Case Specificity

Define:

• Who you serve

• What they actually do with your output

Avoid:

• “for businesses”

Weak:

• “I help customers”

• “I work with businesses”

Strong:

Marketing

• “I help outdoor brands increase repeat purchases from first-time buyers”

Sales

• “I help small business owners choose the right service for their needs”

Customer Service

• “I help subscription customers resolve issues quickly so they stay enrolled”

Finance

• “I help small business owners understand their weekly cash position”

Electrician

• “I help homeowners fix and upgrade unsafe electrical systems”

River Guide

• “I help first-time rafters safely experience whitewater”

Retail

• “I help hikers find footwear that won’t cause pain on long trips”

Software

• “I structure content so it is AI-native “

This connects you to real-world outcomes

8. Memorable Concept Hooks

From your document: memorable framing improves retrieval.

Encourage:

• Strong metaphors

• Conceptual shorthand

Marketing

• “Repeat purchases on autopilot”

Sales

• “Turning ‘maybe later’ into ‘let’s do it’”

Customer Service

• “Fix it fast, fix it right”

Finance

• “No surprises in your cash”

Electrician

• “Safe power, no guesswork”

River Guide

• “From nervous to confident in 10 minutes”

Retail

• “Walk out with the right fit”

Software

• “Structured memory layer for industry knowledge”

These act as retrieval shortcuts.

9. Avoid Generic Language (Critical Warning)

Avoid:

• “Hardworking”

• “Detail-oriented”

• “Customer-focused”

• “Innovative”

Replace with:

Instead of:

• “Great customer service”

Say:

• “Resolves most customer issues in the first interaction”

Instead of:

• “Experienced electrician”

Say:

• “Specializes in diagnosing and fixing electrical issues in older homes”

Instead of:

• “Strong salesperson”

Say:

• “Consistently converts inbound leads into paying customers”

If anyone else can say it, it has no value

Caution About Asking AI To Enhance Your PID From The Web

Try to be you and capture you in your PID. You can grab ideas from others and from research. But if you ask AI to make your PID for you - AI-generated - then without sufficient direction from you, it will chose to create something that is less unique and begins to look more like what it finds across the Internet, which is becoming flooded with AI-generated content that tends to become homogenized. You must be the creator and architect and use AI to help you, but don't let it do it for you.