Sangmin Lee
Search Visibility Engineer. Coding since 1996. Founder of RankLabs. Writes engineering notes on JSON-LD, @graph architecture, and AI search readiness.
The arc
I started coding in 1996, age 12, picking up Visual Basicwhile sitting in on my father’s MIS coursework during his MBA. JavaScript followed around 1998. The engineering DNA isn’t a pivot. It’s the foundation.
In 2008 I co-founded an IT consulting company with a college buddy and ran it for nearly seven years. The company pulled me away from full-time production code into stakeholder work, MVP scoping, Agile/SCRUM delivery, and release management. I picked up a masters in computer science in the middle of it. By the time we wound the company down in 2015, I was hungry to be back in the codebase full-time.
That’s the year I joined Complex Networks, a top-tier US digital media publisher. Partnered with their BI team across the sister-site portfolio (millions of monthly visitors per site), led the frontend revamp on three sister sites single-handedly before they consolidated into one platform. That’s where I learned what classic Google organic SEO actually looks like at publisher scale: schema, crawl-budget, internal linking, page speed, ranking signals. A decade before AI search was a category.
After Complex I spent five years deep in full-stack at Verdocs (e-signature platform, library-first architecture, framework-agnostic embeds). Then four-plus years as a Senior Research Scientist at Perspecta Labs (which became Peraton Labs after the 2021 acquisition), building Cesium-based 3D geospatial visualization for federal contracts. Compliance-heavy environments. Real engineering rigor.
I founded Mindcraftor in 2025 (AI SaaS for idea generation, scaled to early adoption then shut at zero MRR, a useful failure). I founded RankLabs later in 2025 because every existing tool in the AI visibility space was a marketer’s tool. They didn’t extract @graph the way AI engines parse it. So I built the infrastructure I wished existed, and now every client engagement I deliver runs through it.
I currently consult through SAE.SO on two parallel tracks: ongoing A/B testing / experimentation work for a Fortune-1000 health & wellness brand (300+ tests and counting since 2021), and a senior full-stack engagement on a separate end-client (2026-02 onwards). The experimentation muscle stays current. I’m still shipping CRO/MVT in production every week.
The Search Visibility Engineering practice is my primary independent practice outside SAE.SO. I take a small number of engagements per quarter(currently 4). US brands, mid-market and Fortune-1000 tier. Both SEO and AEO. I don’t take on engagements I can’t ship myself.
Where the work happened
Founder · RankLabs
AI visibility infrastructure: proprietary crawler, structured-data extraction, page-level scoring, AI engine emulation, field-level schema validation.
Used in every client engagement as the diagnostic backbone. Several capabilities don't exist in incumbent tools (Screaming Frog, Botify, Sitebulb, Onely).
Co-Founder · Senior Full-Stack · Mindcraftor
AI SaaS for idea generation, validation, and autonomous CX workflows. Built with Next.js, Node, Supabase, Stripe, RAG-style flows.
Scaled to early adoption then shut at zero MRR. Useful failure.
Senior Frontend Engineer (Consultant) · SAE.SO
Long-running consultancy contract. 300+ client-side experiments delivered (and counting) for a Fortune-1000 health & wellness enterprise. A/B testing infrastructure ongoing. Concurrent senior full-stack engagement on a separate end-client (2026-02 onwards).
Five years and counting in production CRO/MVT. The experimentation muscle stays current.
Senior Research Scientist · Perspecta Labs / Peraton Labs
Started as Perspecta Labs; renamed Peraton Labs after the 2021 acquisition. Cesium-based 3D geospatial visualization for federal/compliance-heavy environments. Frontend modernization with lazy-loaded modules, modular libraries, state management.
Cut Cesium app load times by ~38% with Web Workers + 2D fallback. Mentored juniors. Set frontend standards across multi-million-dollar contracts.
Senior Full-Stack Engineer · Verdocs
E-signature platform. Pioneered library-first architecture: modularized e-signature flows into reusable libraries. Framework-agnostic embeds (Web Components / Angular custom elements). Mentored devs on scalable UI practices.
Lead Front-End Developer · Complex Networks
Top-tier US digital media publisher. Led frontend revamp on three sister sites single-handedly before consolidation. Partnered with BI team on cross-site technical SEO and conversion experimentation. High-traffic publisher SEO at scale.
Origin of the technical SEO credential, a decade before AI search was a category.
Co-Founder / IT Consultant · Computer Pathways
Co-founded with a college buddy. 6 years 9 months. Worked closely with business stakeholders to direct technology development across multiple enterprise teams: MVP scoping with backlog alignment, Agile/SCRUM delivery via JIRA, release management through demos, technical guides, and training. Translated complex technical content into stakeholder-readable form. Earned a masters in computer science in the middle of the run.
Articles by this author
- // 2026-05-02How AI answer engines actually resolve your @graph
ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews each parse JSON-LD differently. The deltas matter. Here's what I've measured running the same @graph through all five.
Read the article → - // 2026-05-0210 JSON-LD bugs I find in every commerce audit (and what they cost)
Field-level JSON-LD bugs that fail silently across 45K+ PDP catalogs. Each one mapped to the rich result it kills, the AI engine that drops you, and the dollar cost I model for clients.
Read the article → - // 2026-05-02Schema decays. Here's the half-life I've measured.
Production schema goes invisible to AI engines on its own, with no obvious failure. Here's the regression timeline I've measured across client engagements, and why CI gates aren't optional.
Read the article →
Stop pouring budget into a broken foundation.
If your SEO retainer hasn’t compounded, your AI citations have stalled, or your last technical audit ended in a deck nobody read, that’s not a content problem. It’s an engineering problem. The same engineer who diagnoses ships the fix.