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  • Haute One (KR) · Skipper Labs (US)
  • Seoul
  • 13:31 (UTC +09:00)

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blackcat610/README.md

Seonghwan Byeon · 변성환

한국어

Product & Systems Engineer building AI products—and the systems that build them.

Repeated friction is a systems problem.

I don’t like paying the same friction cost twice.

When a workflow slows me down, I turn that friction into a tool, contract, dashboard, or control plane. The goal is not only to make the current task easier, but to let the improvement compound across every task that follows.

How I work

I increasingly delegate implementation to coding agents.

My responsibility is to define the problem, make product and architecture decisions, establish boundaries and completion criteria, and design an environment where the result can be safely verified and integrated.

  • Persistent plans instead of disposable prompts
  • Isolated worktrees instead of shared-checkout conflicts
  • Executable tests and evidence instead of “done” messages
  • Local dashboards instead of memorized commands, ports, and logs
  • Feedback loops that improve the next task, not only the current one

To support this way of working, I maintain small local tools. Local Dev Mate connects coding agents with persistent plans, dependency-aware tasks, isolated worktrees, and verification evidence. A separate private control plane brings development-service health, latency, and logs into one view.

Rather than optimizing how quickly I type code myself, I focus on designing systems in which agents can continuously plan, execute, verify, and integrate work.

What I’m building

At Haute One (Korea) and Skipper Labs (U.S.), I build a financial AI platform for the Korean and U.S. stock markets.

I work across the full path from financial data and AI reasoning to product experience, production integration, and verification. I choose languages, runtimes, and tools based on the problem rather than treating any particular stack as my boundary.

My current focus includes:

  • Turning financial data and domain knowledge into reliable AI capabilities
  • Designing agent workflows, evaluation, and operational feedback loops
  • Connecting backend, client, and infrastructure boundaries into coherent products
  • Building execution and verification systems that let humans and agents work safely across repositories

Background

I have been building and operating production systems since 2014 across games, mobility, commerce, and fintech.

Outside work, I occasionally build small utilities and experimental projects whenever something feels worth fixing.

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