Work
Samples.

Self-directed AI knowledge platform built to capture, structure, analyze, and retrieve complex system knowledge over time.

Highlights: 4,000+ typed knowledge nodes · 13,000+ typed relationships · 62-table PostgreSQL/Supabase schema · 200+ stored procedures / RPC functions · Custom TypeScript/Deno API surface · Large archived AI conversation corpus · Scheduled background agents · Interactive operator surfaces for search, inspection, and plan navigation.

Demonstrates AI systems analysis, knowledge graph design, data structuring, workflow automation, and long-horizon independent system development.

A structured LLM reliability evaluation method for testing how model behavior changes across multi-turn interactions, constraint shifts, evidence updates, and ambiguous instructions.

Focus areas: multi-turn stability · hallucination risk · constraint adherence · boundary drift · confidence calibration · output consistency · self-correction behavior · failure-mode detection.

Demonstrates LLM reliability analysis, AI evaluation design, structural stability testing, failure-mode classification, and repeatable evaluation methodology.

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A compact portfolio sample analyzing a product recommendation system that produced plausible but poorly coordinated outputs.

The analysis moves from: visible system behavior → hidden decision-logic mismatch → missing structure → practical improvement recommendation.

Demonstrates AI/system behavior analysis, gap and affordance detection, decision-logic diagnosis, practical system improvement design, and clear communication of complex analysis.

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Interactive structural map designed to help modern readers re-orient to a complex narrative through identity handles, power relationships, episode structure, and guided explanation.

Demonstrates information design, structural mapping, explanatory systems, audience-centered complexity reduction, and interactive portfolio design.

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