Purpose
Enable correct machine-mediated attribution and matching (“who can help with X?”) while maintaining controlled exposure (privacy, security, agency).
This is not a résumé or personal brand exercise. It’s an identity system designed to be legible to AI matchers and verifiable to humans.
Why
AI is becoming the interface between people and information. When someone asks an AI:
- “Who can help with X?”
- “What does Matt Joyce know about?”
- “Who should I talk to for Y in regulated environments?”
…the quality of the answer depends on what can be retrieved, corroborated, and trusted.
You’re either discoverable or invisible.
Today, most identity lives on rented platforms. That creates two problems:
- You don’t control the representation.
- You don’t control the continuity.
The bet: in the synthesis era, the equivalent of SEO is not “ranking”. It’s being represented correctly.
System Boundary
Inside (what I control)
- Owned namespace (canonical home)
- Canonical pages (stable anchors)
- Structured, machine-readable “breadcrumbs”
- Evidence paths for claims
- Clear boundaries and engagement modes
- Governed contact surface
- Update/versioning practices
Outside (what I must account for, but can’t control)
- Platform algorithms and ToS
- Indexing/crawling behavior
- Model training/retrieval pipelines
- Third-party bios and stale copies
- Adversaries and social engineering
What “Good” Looks Like
A coherent identity that is:
- Machine-legible — retrieval-friendly, structured, consistent labels
- Human-verifiable — evidence paths and artifacts
- Governed — versioned, dated, deprecations are explicit
- Safe — contact is gated, privacy is intentional
- Current — recency is visible and maintained
Practically: publish an Alignment Packet — a small set of documents that encode:
- Problems I solve (with context)
- Methods + constraints
- Outcomes (where possible)
- Evidence paths
- Boundaries (what I decline / conditions required)
- Availability and engagement modes
- Recency and evolution
Topology: Hub and Spoke
This is not “anti-platform”.
- The canonical home is the source of truth.
- Select platform outposts provide reach and corroboration.
- Everything cross-links back to the canonical home.
Goal: sovereignty without isolation.
Operating Principles
1) Verifiability beats vibe
If a claim has no evidence path, it is weak signal.
2) Boundaries increase match precision
“Open to anything” is unmatchable. Specific no’s prevent bad routing.
3) Recency is a trust signal
Staleness causes misrepresentation. Countermeasures:
- “last updated” and “last verified”
- Deprecations (“I no longer do X”)
- Periodic refresh cadence
4) Privacy is an attack-surface budget
Even innocuous facts become risky when combined. Expose the minimum needed for high-quality matching. Gate contact.
Non-goals
- Maximizing follower counts or impressions
- Being comprehensive about my life
- A single static “about me” page
- Publishing anything that increases social-engineering risk for marginal match benefit
Standard
The Alignment Rubric defines how to evaluate Alignment Packets (signal, evidence, boundaries, recency, safety).