Technical Perspectives

Blog & Insights

Articles focused on analytics modernization, data platform reliability, and the practical application of agentic AI in regulated engineering environments.

Two research programs, both studying how data systems behave at their boundaries: what evidence they emit, and what they should refuse to persist.

Phase I Closed

The Autonomous DataOps Research Series

Phase I is closed: representation of equivalent evidence showed no demonstrated correctness advantage (RQ1), while a preservation-centered comparison of durably captured versus later-reconstructed evidence found a threshold-crossing but statistically thin advantage for durable capture (RQ2). Deterministic diagnosis, Incident Packets, Next Best Action, and policy-governed mitigation remain later, deferred work.

Latest publication: Designing Evidence Packets

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Active Research Program

DICOM Trust Boundary Research

A program studying data systems for medical imaging: DICOM ingestion, structural parsing, and where trust and policy boundaries belong in imaging pipelines.

Latest publication: Before It Lands

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DICOM Trust Boundary Research · September 18, 2026

Before It Lands

A demonstrated pre-persistence DICOM policy boundary (fastDICOMgateway), pushed through five escalating boundaries against a real object store — and the negative-control testing that found three bugs in the validation apparatus, not the system under test.

DICOM Trust Boundary Research · August 13, 2026

Don't Land What You Don't Want to Own

Why the safest place to remove PHI from a DICOM object may be pre-persistence, not downstream — validated against ~26,600 real-world CT DICOM objects with fastDICOMattrs.

Autonomous DataOps Research · August 3, 2026

Designing Evidence Packets

How a dbt-specific Evidence Packet became a source-neutral architecture: dbt as the first source adapter, explicit evidence-completeness gaps instead of silent omissions, semantic compatibility with the original packet version, and deterministic packet integrity.

Autonomous DataOps Research · July 27, 2026

Logs Aren't Enough

Why pipeline diagnosis begins with an evidence scavenger hunt—and why structured Evidence Packets should become first-class operational artifacts.

July 2026

Policy-Governed DataOps Agents

Why the layer above orchestration shouldn't be another scheduler or transformation engine, but an operational reasoning layer that separates policy, evidence, judgment, and action.

June 2026

The Deeper Truth: Platform Complexity

A follow-up reflection on when additional data platform complexity is justified, and how to distinguish necessary complexity from premature or accidental complexity.

May 2026

Why I Prefer BigQuery, dbt, and Airflow

A case for letting the cloud-native data plane scale while keeping the control plane understandable.

May 2026

The GCP Swamp

A visual guide to modern GCP-native data platforms as an ecosystem of storage, orchestration, messaging, compute, and analytics.

April 2026

AI-Native SDLC

Designing an SDLC that treats AI agents as bounded contributors within a deterministic orchestration framework.

Jan 2026

Scaling Business Intelligence

Moving from spreadsheet-heavy reporting to a durable, cost-aware data platform without a disruptive rewrite.

Dec 2025

Finding Signal in Events

How observable events propagate into measurable attention patterns, and why disciplined ingestion matters.