A long-form article introducing the Twin Test: a practical standard for high-stakes machine learning where models must show nearest “twin” examples, neighborhood tightness, mixed-vs-homogeneous evidence, and “no reliable twins” abstention. Argues similarity and evidence packets beat probability scores for trust and safety.

A long-form article and practical framework for designing machine learning systems that warn instead of decide. Covers regimes vs decimals, levers over labels, reversible alerts, anti-coercion UI patterns, auditability, and the “Warning Card” template, so ML preserves human agency while staying useful under uncertainty.

AI/ML Engineer — Decision Ops • LLM Observability • GenAI/RAG Systems

Event-driven NLP governance architecture using FastStream, Redpanda, and PostgreSQL with auditability, human-in-the-loop control, and ethical safeguards.

Control-plane architecture for AI & agentic systems: governance as admission control, decision admissibility, and audit-grade evidence.

Deterministic governance system for AI-driven marketing that separates diagnostics, human reasoning, and execution into strictly controlled layers.

A governed system for translating applied AI research into auditable, decision-ready artifacts.

"Advanced ternary logic framework for processing uncertainty in computational decision systems—solving the fundamental limitation of binary logic in real-world applications."

An experimental log that derives physical rules of AI + money systems from real-world failures, focusing on execution, state, authorization, and irreversible outcomes.

Optimization-driven product selection for commercial buying decisions under budget and business constraints.

Audit-grade governance artifacts documenting non-overridable behavioral constraints. Schemas and redacted audit examples showing how certain failures are made structurally impossible before discretion or hindsight.

Responsibility Normalization Contract

This tool visualizes how thresholds, top-K limits, and review budgets remove candidates before human review. It informs threshold selection, review budget sizing, and top-K choice in constrained human review workflows.

A design framework for decision-centered automation, governance, and early misalignment detection.

Analytics and automation builder focused on turning operational data into practical decision tools. Background in commercial and retail planning, moving toward decision systems and analytics engineering.

Strategic multi-dimensional customer segmentation decision system aligning marketing investment with profitability and ROI

Deterministic multi-perspective AI consensus engine with cryptographic trace verification and formal convergence guarantees.

Full-stack freelance defense toolkit featuring rule-based client risk scoring, contract generation, invoice tracking, and red-flag detection.

Judgment-preserving QA framework for agentic AI systems. v1.0 sealed.

AI-driven spatial modeling, ensemble learning, and LLM-integrated decision systems for yard-scale pollinator plant recommendations