Automation & Applied AI
Automation for expensive manual work, decided step by step: full automation, a human in the loop, or no software at all. When a model is part of the answer, it comes with evals, guardrails, and a measured cost.
Industries
What it covers
Typical work
How I think about it
Consequential automation is an engineering problem before it's an AI problem. The first question is whether a step should be automated at all. When a model earns a place, I treat it like any other dependency: measured, tested against an eval suite, and replaced when a cheaper one does the job.
Other expertise
Agentic Engineering
Coding agents as part of the engineering system. Harnesses, guardrails, quality gates, and telemetry.
Platform & Infrastructure
AWS and GCP platforms defined in code. Kubernetes, GitOps delivery, observability, and cost control.
Security & Compliance
Identity, least privilege, audit trails, and data boundaries designed in. Architecture that holds up under HIPAA, SOC 2, and ISO 27001 review.
Data Engineering
Ingestion, enrichment, and event pipelines. Data modeled and accessible for products, analysis, and automation.
Product Engineering
Web, mobile, and backend products from first version through launch and iteration. Full stack, from data model to interface.