Stack

Technical stack

Skills, tools, and systems I can point to with public proof, shipped work, or client-style implementation evidence. AI work is framed as implementation: local models, API wrappers, queues, review surfaces, content governance, GEO/AEO technical structure, and human-controlled automation.

5 skills

Core

Web/software systems

21+ years

Broad web/software implementation across production sites, technical systems, debugging, automation, and delivery.

IndexLane work

Backend / Crawling

Python / FastAPI / crawling systems

Portfolio proof

FastAPI crawler and decision systems with raw/rendered audits, worker queues, evidence APIs, market evidence, exports, and technical SEO diagnostics.

ILCrawler / MarketEngine

AI / Workflow

AI-assisted implementation

Workflow proof

Practical LLM-supported implementation, triage, classification, drafting, QA, and handoff workflows with deterministic filters and human approval boundaries.

ReachLog / workflow proof

Local LLM / model serving

Local model proof

Self-hosted and local LLM workflows using open-weight models, quantized builds, API wrappers, prompt pipelines, and operator review boundaries.

Private lab / workflow proof

Multi-model editorial pipelines

Review pipeline proof

LLM-assisted drafting, rewrite, critique, comparison, and review pipelines across multiple models, with deterministic checks and human approval before publishing.

AI-assisted content governance