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

TypeScript / Frontend

TypeScript / React / Next.js

Shipped demos

Private product shells, workflow tools, operator interfaces, stateful UI, CSV import/export, and review dashboards.

SearchCaliber / ReachLog

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

Diffusion / image-generation workflows

Self-hosted image proof

Self-hosted diffusion workflows around SDXL-style image generation, prompt presets, batch output review, API wrapping, and local/private generation experiments.

Private lab proof