Jie Xiang

Jie Xiang.

I keep a commercial KVM cloud platform from falling over for a living. On the side I run a multi-agent Claude Code pipeline that has put 53 iOS apps on the App Store. I write here when something in either world surprises me — usually with a number attached.

Side work · reach out jie.xiang.jm@gmail.com 53 iOS apps $13K/wk Claude Code 11 npm/wk 6 yrs reliability eng
// 53 SHIPPED — tap any icon to open in App Store
NOW · week of Apr 22
  • Shipped claude-agent-ledger v0.4 — added --by project, found out 50% of my Claude Code spend goes to one codebase.
  • ShipReady v1.0 sitting in Apple review since Apr 19. PetBook v1.0.8 in queue too.
  • This site is the new public surface — built it Mon–Tue. The OG image is auto-generated with a small Python/Pillow script.
WHAT I SHIP
PREREVIEWS · MAC APP · IN APPLE REVIEW

Drop an email — I'll ping you when it ships.

60+ pre-flight checks for App Store submissions. Built from ~50 of my own rejections. First 100 emails get 25% off launch ($19.99 $14.99, lifetime, no subscription).

No spam. One email when ShipReady is approved by Apple, then nothing until v1.1.

OPEN SOURCE SPOTLIGHT
v0.4.0 on npm · MIT

claude-agent-ledger →

Per-subagent · per-model · per-project · per-session · per-day cost attribution for Claude Code. Reads the local JSONL session logs and shows what each dimension actually consumed at marginal API rates. My own pipeline runs at ~$13K/week shadow cost on a $200/mo Max plan (~250× leverage) — the gap is the most interesting thing I've seen in LLM infra this year.

npm install -g claude-agent-ledger
agent-ledger week --summary
WRITING

What my own Claude Code was doing wrong

I wrote a lint for my Claude Code session logs. 41 findings in a week: a runaway session that ate 31% of my budget, 99.6% of spend on Opus, an agent stuck on Bash for 50 turns. 12 rules, MIT.

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THE THESIS

AI Agents ship fast but break in the same long-tail ways distributed systems always have. Most teams don't yet have the eval, observability or reliability practices to catch it.

Six years of debugging a hypervisor at 3 AM gives you a reflex: if you don't have a per-component bill of materials, you don't actually understand the system. I'm pointing that reflex at AI Agents.

FIND ME

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