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见远而行

DATA INFRASTRUCTURE · TRUSTWORTHY AI · INDEPENDENT BUILDING

Make complex systems smaller. Put AI inside verifiable boundaries.

I build data infrastructure and trustworthy AI tools in Hangzhou, writing about real constraints, trade-offs, and reusable implementations.

Building in public, one verifiable artifact at a time.

3published notes

2active projects

Working principles

Capability matters. Boundaries make it trustworthy.

  1. 01

    Own the data

    Keep usage, cost, and operational records portable, inspectable, and under the user's control.

  2. 02

    Make behavior deterministic

    Use AI to interpret ambiguity; leave validation, permissions, and state changes to explicit systems.

  3. 03

    Build the smallest useful boundary

    Prefer focused components, boring dependencies, and interfaces that remain easy to replace.

Now building

Ideas tested as working systems

Two ongoing projects explore the same question from different angles: how do we add capability without giving up clarity or control?

01

lineage-viewer

Alpha

A zero-runtime-dependency Web Component for stable, embeddable table and column lineage diagrams.

Deterministic layout · Web Components · diagnostics

02

LarkLedger

In progress

A ledger where AI interprets natural input while deterministic services validate and commit each action.

Structured actions · confirmation boundaries · idempotency

Latest notes

New observations from systems that are still changing.

No algorithmic feed. No inbox pressure.

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