🧑‍🚀 Hi!

I'm Yong Tian, or Edward, a technology leader with over 20 years of experience specializing in artificial intelligence, large language models (LLMs), AI agent systems, and SaaS platform development. I founded a tech startup in China and currently serve as a core technical leader at an AI startup in the U.S., where I focus on turning cutting-edge AI technologies into real-world, impactful products.

Background in Product and Machine Learning Systems

My background originally came from product-oriented development, with a strong focus on big data systems and traditional machine learning. I built analytics pipelines and ML-driven features using algorithms like clustering, random forests, principal component analysis, and classical NLP techniques such as TF-IDF, topic modeling, and rule-based entity extraction.

I worked across the full stack and always focused on delivering usable, data-informed products-connecting backend intelligence with frontend experiences. I genuinely enjoy writing code and solving problems end to end.

The Turning Point: Discovering the Power of LLMs

In 2023, I faced a problem that had frustrated me for a long time: extracting clean, structured information from physical health check reports using OCR. Traditional methods-rule-based post-processing and statistical modeling-just weren't reliable enough.

But when I applied LLMs like ChatGPT, with some lightweight fine-tuning, the results were dramatically better. The model corrected noisy OCR output, inferred structure, and interpreted ambiguous entries more accurately than anything I'd built before.

That moment made it clear to me that LLMs weren't just useful tools to support existing processes-they were becoming the process itself. AI wasn't just assisting work; it was redefining how work gets done.

Going Deep: From Curiosity to Capability

After that, I committed myself fully to the LLM space. I started by writing transformer models from scratch to understand the architecture. I explored prompt engineering, tool use, multi-agent collaboration, retrieval-augmented generation (RAG), and post-training refinement. I even built internal playgrounds to test structured workflows and agents.

This wasn't about chasing hype-I wanted to understand LLMs as a new computing model. I developed what I call an AI-first mindset: thinking of LLMs not as an add-on, but as the engine behind product experiences.

Applying LLMs in Production Systems

Eventually, I joined my current company to lead the AI tean to build LLMs into real products. At the same time, I've also helped turn complex internal processes into intelligent, automated pipelines. One of the most impactful internal projects was building an LLM-powered end-to-end testing system.

Instead of relying on brittle manual test scripts, we used LLMs to simulate realistic user behavior and dynamically generate and validate integration test flows. This system significantly boosted test coverage and helped our engineering team ship faster and with greater confidence.

My Strengths

Beyond engineering, I've founded and led a company as CTO. I've managed teams, driven execution across multiple functions, and consistently delivered under pressure. I care deeply about efficiency—I like to move fast, make good decisions with limited information, and avoid unnecessary complexity or corporate BS.

I'm highly self-directed and take full ownership of my work. I don't need a manager watching over me to stay productive—I set high standards for myself and keep things moving. I thrive in fast-paced, hands-on environments. I'm used to wearing multiple hats, turning messy ideas into working prototypes, and shipping things that people actually use.

I see myself as someone who bridges two worlds:
- I can build solid products end to end—frontend, backend, infrastructure.
- I can design and implement AI-native systems that make real work smarter and faster.

The Kind of Team I Thrive In

I'm always drawn to teams that build with speed, creativity, and clarity—where execution matters, and ownership is real. Not just shipping fast, but caring deeply about how things are made and why they matter.

That’s the kind of environment I’ve always thrived in—especially during my time building my own startup. I enjoy wearing multiple hats, solving messy problems, and turning ideas into usable, thoughtful products.

Questions for My Future Team

1. Team size & hiring plans:

I’d love to get a better sense of the team — how big is the team currently, and are there any plans to grow it in the near future?

2. Funding status & future plans

Have you raised any funding so far? Just curious how you’re thinking about runway and whether there are future fundraising plans.

3. Company’s near-term direction

What’s the company focused on in the next 6 to 12 months? I’d love to understand where you’re heading strategically.