Ron Bronson
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Leafroll — Professional Identity Layer

Dynamic, modular professional profiles that travel across networks—rethinking how people present work, skills, and trajectory.

The Problem with Static Résumés

Traditional career documentation is broken:

  • Résumés are static snapshots optimized for a single use case (job applications)
  • LinkedIn profiles become cluttered catch-alls with no context
  • Work samples live in scattered portfolios with no connective tissue
  • Reputation doesn’t travel—references and endorsements are locked to platforms
  • Context collapses—you present the same profile whether pitching a collaboration, applying for a job, or joining a community

You can’t easily answer:

  • “What does this person bring to a specific project?”
  • “How has their work evolved over time?”
  • “Who can vouch for their skills in this domain?”
  • “What artifacts best demonstrate relevant capability?”

What Leafroll Does

Leafroll treats professional identity as composable, portable infrastructure. Instead of static career pages, profiles are:

1. Living Documents

  • Dynamic, not fixed: Update as skills evolve, projects complete, and focus shifts
  • Signal-rich: Not just job titles—artifacts, endorsements, collaboration patterns
  • Contextual: Rearrange based on who’s viewing and why
  • Time-aware: Show trajectory and evolution, not just current state

2. Modular & Composable

Profiles are built from structured components:

  • Artifacts: Work samples, case studies, projects
  • Signals: Skills, tools, methodologies
  • Endorsements: Vouches from collaborators (verified via Glowrm)
  • Context: Why you did the work, what you learned, how it fits your trajectory
  • Metadata: Structured tags for discovery and filtering

Each component can be:

  • Rearranged for different contexts (hiring vs. collaboration vs. community)
  • Linked to other people, projects, and organizations
  • Versioned to show how work evolved
  • Selectively shared based on permissions

3. Portable & Network-Native

Built on AT Protocol, so:

  • You own your data (not the platform)
  • Endorsements travel with you across networks
  • Profiles can be queried by compatible services
  • Reputation is portable (verified by Glowrm trust layer)

4. Context-Aware Presentation

Instead of one static profile, Leafroll can generate contextual views:

  • For hiring: Emphasize relevant experience, endorsements, work samples
  • For collaboration: Highlight complementary skills, past projects, availability
  • For community: Show shared interests, values, background
  • For discovery: Surface emergent skills, trajectory, unique combinations

Design Principles

Show Work, Not Just Credentials

Leafroll prioritizes artifacts and endorsements over job titles and dates. What you’ve built matters more than where you worked.

Dynamic Over Static

Profiles evolve as you do. New skills, completed projects, and endorsements update automatically. You see trajectory, not just snapshots.

Composable Over Monolithic

Profiles are assembled from components that can be mixed, rearranged, and filtered. No single “correct” view—presentation adapts to context.

Portable Over Locked-In

Your professional identity travels with you. No platform lock-in; endorsements and work history follow you across networks.

Social Proof Over Self-Report

Endorsements are verified (via Glowrm). Collaborators can vouch for specific skills or projects, creating trusted reputation.

How It Works

Profile Components

Artifacts:

  • Case studies, projects, portfolios
  • Work samples (code, designs, writing, media)
  • Links to live work or deployments
  • Context: problem, approach, outcome, learnings

Signals:

  • Skills (verified by endorsements)
  • Tools and methodologies
  • Domains and industries
  • Interests and values

Endorsements:

  • Verified vouches from collaborators (Glowrm integration)
  • Skill-specific endorsements (“Alice is excellent at X”)
  • Project endorsements (“Bob contributed to Y and was great to work with”)
  • Context: who, when, why, for what

Trajectory:

  • How skills evolved over time
  • Thematic arcs across projects
  • Transitions and pivots
  • Emergent patterns (e.g., “increasingly focused on civic tech”)

Metadata:

  • Structured tags for discovery
  • Availability and preferences
  • Collaboration style and values
  • Communication preferences (pulled from Glowrm consent layer)

Contextual Views

Hiring Mode: Shows relevant experience, endorsements from past employers/clients, work samples aligned with job requirements, and skill verification.

Collaboration Mode: Highlights complementary skills, availability, past collaboration patterns, and communication preferences. Shows what you bring to a team.

Community Mode: Surfaces shared interests, values, and background. Emphasizes fit and contribution potential rather than credentials.

Discovery Mode: Showcases unique skill combinations, emergent expertise, and trajectory. Helps people find you based on what makes you distinct.

User Journey

  1. Create Profile:

    • Add artifacts (projects, work samples)
    • Declare signals (skills, tools, interests)
    • Connect to Glowrm for identity verification

  2. Request Endorsements:

    • Invite collaborators to vouch for specific skills/projects
    • Endorsements are cryptographically verified (Glowrm)
    • Build social proof over time

  3. Configure Context Views:

    • Decide what to emphasize for different audiences
    • Set permissions (what’s public vs. restricted)
    • Define routing rules (who sees what)

  4. Share & Discover:

    • Share contextual profile links (e.g., “my collaboration profile”)
    • Allow compatible services to query your data
    • Be discovered based on skills, trajectory, or unique combinations

  5. Evolve:

    • Add new artifacts as projects complete
    • Update skills and signals as you grow
    • Accumulate endorsements from new collaborations
    • Profile stays current without manual résumé updates

Technical Architecture

AT Protocol Foundation:

  • Decentralized identity (DIDs)
  • User-controlled data repositories
  • Structured schemas for professional records
  • Composable queries for discovery

Data Structures:

  • Artifact Records: Structured case studies, projects, portfolios
  • Signal Declarations: Skills, tools, methodologies, interests
  • Endorsement Records: Verified vouches (Glowrm integration)
  • Trajectory Metadata: How work evolved over time
  • Context Configurations: Rules for what to show when

Services:

  • Profile Composer: Generates contextual views from components
  • Discovery Engine: Query profiles by skills, trajectory, signals
  • Endorsement Verifier: Check cryptographic signatures (via Glowrm)
  • Artifact Renderer: Display work samples in context

Integrations:

  • Glowrm: Trust layer for endorsement verification and consent
  • HeyPBJ: Professional discovery rundles for collaboration matching
  • External Services: Any AT Protocol–compatible platform can query profiles

Use Cases

Hiring & Recruiting

  • Employers: Search for candidates by skill combinations, trajectory, or verified endorsements
  • Candidates: Present contextual profiles optimized for specific roles
  • Referrals: Endorsements provide trusted social proof

Collaboration & Freelancing

  • Project Matching: Find collaborators with complementary skills
  • Team Assembly: See how people work together (past collaboration patterns)
  • Vetting: Check verified endorsements and work samples

Community & Discovery

  • Find Your People: Discover others with shared interests, values, or trajectories
  • Community Fit: See if someone aligns with group culture/values
  • Emergence: Surface unique skill combinations or non-obvious expertise

Career Trajectory & Reflection

  • See Your Growth: Visualize how skills and focus evolved over time
  • Identify Patterns: Notice emergent themes across projects
  • Signal Shifts: Broadcast career pivots or new directions

Integration with Other Projects

HeyPBJ (Matching Platform)

Uses Leafroll for:

  • Professional discovery rundles (collaboration, not dating)
  • Skill-based matching for project teams
  • Verified credentials for professional contexts

Glowrm (Trust Layer)

Uses Glowrm for:

  • Cryptographic verification of endorsements
  • Portable reputation across networks
  • Consent management (who can see what)
  • Trust routing (weighting endorsements by relationship strength)

Occupant (AI Benchmarks)

Could use Leafroll for:

  • Contributor profiles (expertise in AI/data)
  • Verified credentials for data submissions
  • Community governance (who can vote on methodology changes)

Part of the AT Protocol Suite

Leafroll is one of several interconnected projects exploring decentralized infrastructure:

Research Questions

Leafroll explores:

  • Can modular profiles better reflect how people actually work than static résumés?
  • Do verified endorsements create more trusted reputation than self-reported credentials?
  • How do contextual views change hiring, collaboration, and discovery?
  • Can portable identity reduce lock-in and improve labor market fluidity?
  • What happens when professional reputation travels across networks?

What This Demonstrates

  • Composable professional identity: Treating careers as living documents, not static snapshots
  • Portable reputation systems: Building verified endorsements that travel across platforms
  • Context-aware presentation: Adapting profiles based on audience and use case
  • Social proof infrastructure: Creating trusted verification without centralized platforms
  • Decentralized career infrastructure: Proving you can build professional networks without LinkedIn-style lock-in
  • Modular data design: Showing how structured components enable flexible presentation
  • Trajectory thinking: Emphasizing evolution and growth over fixed credentials