Building fast is table stakes now. Anyone can generate a screen. What I do is design the thing behind the screen so it doesn't fall over — and then actually operate it.

• What I actually do
• 🚀 Products in production
• 🎮 Games · Mini-apps
• 📊 Data · AI · Automation
• ⛓️ Web3
• 🌐 Web · App · Community
• 📦 Open source
• 🛠️ Tools I built for myself
• Experience
• Stack
• 🇰🇷 한국어

CTO 5 microservices Kubernetes Saga pattern LSTM 0.74% MAPE Zero designers

Planning → architecture → development → operations. All of it. Five services (dual frontend / collection API / business backend / scheduler / admin) on Kubernetes. MongoDB Time Series + Redis. Playwright market-data pipeline. GPT-4o news agent with a daily briefing. Reverse-auction orders orchestrated event-driven with the Saga pattern. Cross-platform mobile app (Capacitor) in both stores. A Windows agent syncing POS + tank sensors on-site.

In-house LSTM forecasting — MAPE 0.74%, 88% directional accuracy — benchmarked against GARCH · VAR · VECM · XGBoost before I trusted it.

300K users 100+ TPS Redis + MQ nonce-safe

Decouples transaction submission from service logic. Instead of hammering the chain, requests queue and workers drain them — sidestepping nonce collisions and rate limits. Retries, backoff, failure replay.

penguinboard.com · Chrome Extension MV3 XHR interception 2-person team launched

Fashion/beauty brands sell across many marketplaces and their numbers live in a different admin panel for each one. This pulls them into one place — pricing, orders, per-channel P&L, SKU-level margin.

The collection engine is an extension, not a scraper. Public-page scraping gets you blocked; an extension runs inside the user's own authenticated session, on the user's own data. Two-layer content script (MAIN + ISOLATED world), XHR/Fetch interception instead of DOM parsing — so a UI redesign doesn't break it — plus session keep-alive so 2FA re-login stays rare.

market-why-delta.vercel.app · quality gate replay check SEO/GEO human-gated publish

An AI analyzes the market, then interrogates its own verdict. Every call ships with supporting evidence, counter-evidence, and the condition that would falsify it. Past calls get scored — and prediction / avoidance / live-trade are scored on separate denominators, because mixing them flatters the numbers.

Nothing publishes unless the data layers validate, and a replay check re-runs the same input to confirm the same verdict. Failures aren't hidden; they show as unconfirmed.

An attached video pipeline: script → TTS (SSML-controlled) → scene timing auto-matched to the actual audio length → subtitles → thumbnail → publish package. The sync isn't eyeballed on a timeline; the voice length decides the scene length.

contract work MVP shipped payments raffle engine admin

Handed an idea, no spec, no design. Shipped the MVP. Social login and multi-role permissions, payments → points → entitlement, wishlist/challenge/raffle engine, community feed and ranking, operator admin. Frontend and backend, solo.

Solidity tokenization liquidity pool investor dashboard

Product planning, fullstack, smart contract lead. Asset tokenization (deposit / redeem / secondary trade), pooled liquidity with arbitrage logic, investor dashboard, on-chain state monitoring and alerts.

Stable Diffusion inversion style transfer solo build 🏆 TIPS selected

Research (InST · WaveFunctionCollapse · ProSpect) → data pipeline → frontend → backend. Alone. Selected for the TIPS program.

Running a game inside a messenger mini-app is not the same as shipping a web app. You inherit someone else's container, someone else's auth, someone else's lifecycle — and you still have to settle rewards on-chain without losing a transaction.

Unity WebGL C# Kotlin middleware Telegram mini-app LINE mini-app on-chain rewards Kubernetes

A solitaire-based Web3 game, built in Unity and shipped inside both Telegram and LINE mini-apps — two different host platforms, one game.

• Unity (C#) → WebGL build embedded in the mini-app container
• Kotlin middleware bridging game score ↔ platform identity ↔ on-chain settlement
• Game economy: token accrual → conversion → reward distribution, designed so a failed on-chain payout is recoverable instead of silently lost
• Kubernetes, zero-downtime deploys

The hard part wasn't the card game. It was making a Unity build, a messenger's auth, and a blockchain agree with each other — reliably, at scale, on two platforms at once.

TON Tact/FunC Telegram mini-app partner API 1-day integration

A launchpad that aggregates multiple games. Launchpad backend, TON smart contracts, mini-app frontend, partner-game integration API. Probability-driven mystery box engine with externalized probability tables — tuning odds doesn't require a redeploy. Weekly reward distribution via cron, with a recovery path for failed payouts. New partner games integrated in under a day — because the score/reward API was designed as a contract, not as an afterthought.

FANANAS is the game that goes on a launchpad. NNN is the launchpad. I built both sides.

On forecasting: the number that matters isn't 0.74% MAPE — it's that I benchmarked it against four other models before believing it. On agents: the interesting part isn't that AI writes the report. It's that AI doesn't ship it when the data is thin. On SEO/GEO: search isn't the only front door anymore. People ask ChatGPT and Perplexity, and the answer cites someone. I build content to be citable — structured markup, explicit sources, answer-first paragraphs. Applied on my own sites, not just recommended.

Teach your AI design judgment. Not just components. Live demo · 74 rules 48 components 7 brand skins MIT

AI coding tools can produce a component. They cannot tell you why 16px is wrong here. This encodes that judgment — for Claude Code, Codex, Cursor. Brand skins: Toss / Stripe / Linear / Notion / Raycast / Arc / Vercel. Named motion system, 15 slash commands.

Claude forgets everything when the session ends. CodeSyncer makes it remember. multi-repo @codesyncer-* tags npm

Decisions and inferences get recorded in the code instead of evaporating with the session. Oildealer actually runs on it — this isn't a proposal, it's how my production platform is maintained.

Your LLM is blind to what it creates. We give it eyes. render-aware feedback loop

Curated: claude-plugins agent-skills ai-coding-tools vibe-coding

Also: AX (AI transformation) engagements for clinics and investment firms — automating manual workflows with tools I built.

M.S. Computer Science, Hanyang University — Computer Network Security Lab 🏆 TIPS program — selected for SuperAsset