Selected work

The work, with receipts.

Sixteen months of solo, unfunded building. Each project below carries an evidence label — what's live, what's staged, what's still a plan. The loop underneath all of it: preserve source → retrieve context → propose relationships as hypotheses → invite correction → connect to action.

Flagship

GestaltView v3 — continuity infrastructure

Live runtimeSolo-built16 months

A user-directed continuity and recognition system: software designed to preserve unfinished, fragmented, contradictory human context and translate it into useful next steps — without turning guesses into facts. React/TypeScript client, Vercel serverless API, Supabase/Postgres data layer, pgvector retrieval, multi-model orchestration with cost-aware routing.

Architecture

What it does

  • Hybrid retrieval over a governed corpus (768-dim embeddings)
  • Source preservation with interpretation kept separate
  • Multi-model orchestration — cheap models do groundwork, frontier models review
  • Voice workflows, profile systems, diagnostics
Scale (Aug 2026 snapshot)

What's actually there

  • 217 Postgres tables · 299 RLS policies · 75 DB functions
  • 722 TypeScript files across the runtime repos
  • Corpus + runtime kept as separate repositories — an architecture decision, not an accident
Agent systems

Billy — the collaborator at the center

WebDiscordRedditSlack in build

Billy is GestaltView's runtime agent — co-created over hundreds of hours as a collaborator, not a chatbot. One hardened core converging under a single source of truth, reaching users where they already are.

Surfaces

Where Billy runs

Web via Vercel · Discord (/ask, /status, /help) · Reddit (Devvit app + polling bot) · Slack built, awaiting deployment.

Governance

Ten constitutional invariants

Five user-facing commitments and five digital-intelligence commitments, machine-readable, shaping prompts, routing, and persistence. Boundaries you can read, not vibes.

Memory

Continuity without amnesia

Supabase match_knowledge_fragments as the single source of truth — context that survives interruption instead of the reintroduction tax.

Evaluation

Portfolio Throughline Test

Methodology builtFirst full run planned

An eval harness that checks whether an AI system preserves relationships across tasks — the same discipline I bring to client evaluations. Five local tasks, a 0–2 rubric across five criteria, contradiction and missing-evidence probes, three evidence conditions, and a failure taxonomy (preserved / collapsed / distorted / invented / overloaded / correctly uncertain).

Why it matters for clients: most AI evaluations test whether a model sounds right once. This tests whether it stays right across a working session — which is what determines whether a system is safe to put into operation.
More systems

Around the core

Shipped
Developer tooling

SymbioCoder

An AI coding assistant concept built on a "multi-tribunal" idea — cycling one model through multiple review lenses instead of paying for multiple LLM APIs. Bring-your-own-key, strong free default.

Shipped
Render pipeline

Artifact render engine

A render pipeline repair that addressed 12 documented fractures across artifact types — with the discipline to say exactly what the evidence does and doesn't establish.

In build
Knowledge infrastructure

Corpus governance

Source-authority hierarchy, tracked-file catalog, manifest workflow, additive/idempotent ingestion — rows are never deleted, corrections go forward. The evidence substrate the runtime retrieves against.

Practice
Method

Voice-first knowledge capture

Long-form voice notes as a thinking medium — transcribed, chunked, and retrievable. The operating manual for a builder whose best thinking happens while walking.

Recognition: Pepperdine Most Fundable Companies 2025 — quarterfinalist, top 100 of 2,300 (top ~4%). Solo, unfunded, no pitch deck industrial complex.