RONGJIAN LIAO

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RONGJIAN LIAO / INDEPENDENT AI PRODUCT ENGINEER

Complex systems.
Considered products.

I'm Rongjian. From water-resources modeling to AI applications, my question has stayed the same: can the system be dependable and the experience feel simple?

Python / TypeScript · Web / iOS

THE RELIABILITY LAYER

No evidence. No output.

Change the input. See what a small gate protects.

ACCEPTED

Source present. Execution identity matches. Accept the result.

generation
7 → 7
source
present

Interactive model · no API calls, not a live agent run

Inside the gate: the Stock-Agent engineering case

SELECTED WORK / 01

The work speaks first.

Some of it lives deep in a system. Some of it fits in your hand.

All projects & technical details

AGENT ENGINEERING

Every step. An inspectable trail.

When tasks run in parallel, duplicate work, late writes, and recovery matter as much as the answer. I built runtime isolation, generation fencing, and selective resume around those failure modes.

STOCK-AGENT / E1

64/64

Fixed-commit isolation checks

64/64: private-core offline check receipt dated 2026-07-28. The public bundle verifies receipt integrity; it cannot reproduce the private tests.A separate public synthetic replay is reproducible. The two evidence scopes remain distinct.

And the details you can touch.

Real App Store screens, not product concepts.

Texas Hold’em Coach — App Store screenshot

IOS / EDUCATION

Texas Hold’em Coach

Turn rules into practice. From choosing the winning hand to reviewing mistakes, learning happens one decision at a time.

Offline learning · Free download · Optional one-time ProView on the App Store
Don't Count Sheep — App Store screenshot

IOS / WELLNESS

Don't Count Sheep

A quieter end to the day. Procedural patterns and a lightweight, account-free experience for winding down.

Offline experience · Free patterns · Optional paid contentView on the App Store

THE THREAD / 02

New domains. The same engineering instinct.

Water-resources modeling taught me to respect boundary conditions. Data systems made me care about input quality. Building products brought that same attention to the user's next step. AI is a new tool; judgment and delivery are still my responsibility.

The full story

Building notes

All notes
2025.12.20

LLM-First Workflow: Generalizing Capability

2026.02.03

Why I Chose Classic Patterns Over Pure ML for Trading

LET'S BUILD / 03

Start with a real problem.

Hiring an AI / Python engineer, or shaping a product? Tell me the goal, what's stuck, and how you'd like to work together.

Based in Chengdu · Open to remote work or relocation for the right role

Roles / Engineeringliaorongjian@outlook.com
Product / Businessfortuneinsight@outlook.com

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