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Where I am, autumn 2026

· 4 min read
Kit Kong
Engineer in Vancouver, AI systems and trading infrastructure

The last post here is from December 2024. This one fills the gap: a master's degree, a few systems I built and ran, and what I want to work on next.

Measure before you build

· 6 min read
Kit Kong
Engineer in Vancouver, AI systems and trading infrastructure

The expensive mistake in on-chain arbitrage is building a fast bot for a market you haven't measured. This post is about measuring first, on Solana and then on Robinhood Chain, and what the numbers changed.

Nine stages, one conclusion

· 7 min read
Kit Kong
Engineer in Vancouver, AI systems and trading infrastructure

LLM-Digest is the app I run for myself to read the market so I don't have to. This post walks through how its flagship report gets written: nine LLM stages, typed hand-offs, and the boring machinery that keeps it running.

Smaller KV cache, faster first token

· 6 min read
Kit Kong
Engineer in Vancouver, AI systems and trading infrastructure

For our graduate capstone this summer, a team of four built a latency stack on vLLM serving Llama-3.1-8B on a single RTX 3090. My part was the KV-cache layer underneath the scheduler. This post covers what that layer did and why it moved first-token latency more than anything else we tried.

A 27B model on one RTX 3090

· 4 min read
Kit Kong
Engineer in Vancouver, AI systems and trading infrastructure

Most of my local inference runs on one RTX 3090 with 24 GB of VRAM. This post covers what fits on it, what doesn't, and why the limit is usually not the model weights.

How I work with coding agents

· 5 min read
Kit Kong
Engineer in Vancouver, AI systems and trading infrastructure

Most of my code in 2026 was written with coding agents, mainly Claude Code. These are the practices that held up on large codebases, and the problems that made me adopt them.