Me Page | Ziyang Zeng

April 26, 2026AI Agents Claude Code Alignment Developer Tools Skills

The Ambiguity Tax

What /grill-me taught me about shifting agent risk from verification to alignment — and why senior agent users should restructure their workflow around this.

December 4, 2025Software Engineering Business decision making Product work

The Art of the "No Go": What I Learned From Killing My Own Feature

In the world of software engineering, we often measure success by what we ship. The code that lands, the features that go live, the press releases that go out.  But working in a large-scale tech organization has taught me a counter-intuitive lesson: sometimes, the most valuable work you do is the work that doesn't ship. Recently, I led a project that seemed like a slam dunk on paper. We i

November 2, 2025AI ML KNN Recommendation Systems Vector Search

The Industrial Leap from KNN to ANN for Real-Time Recommendations

In the world of machine learning, K-Nearest Neighbors (KNN) is often one of the first algorithms taught. Its simplicity is elegant: to classify a new data point, find the $k$ training examples "nearest" to it and take a majority vote.\[^1] In recommendation systems, this translates to a powerful and intuitive concept: "people like you also liked..." (user-based collaborative filtering) or "people

August 23, 2025AI ML LLM Agents Automation

Autonomous Horizons - LLM Agents for Strategic Planning and Execution

The Cognitive Architecture of Modern LLM Agents The transition from Large Language Models (LLMs) as sophisticated text predictors to LLM-based autonomous agents represents a significant paradigm shift in artificial intelligence. This evolution is not merely an incremental improvement in model capability but a fundamental change in system architecture. The true "agentic leap" lies not in the LLM it

August 1, 2025AI ML LLM Copyright protection

LLM Watermarking for Copyright Protection and Content Integrity

The Imperative for Provenance: Situating Watermarking in the LLM Ecosystem The rapid proliferation and increasing sophistication of Large Language Models (LLMs) have precipitated a paradigm shift across numerous sectors, unlocking unprecedented capabilities in content creation, dialogue systems, and automated reasoning.\[^1] However, this transformative potential is shadowed by significant and s

June 1, 2023AI ML Recommendation Systems

A Deep Dive into AI/ML Recommendation Systems

Recommendation systems are integral to modern digital platforms, facilitating user engagement by suggesting relevant content or products. This paper provides a comprehensive analysis of the foundational algorithms and advanced architectures that constitute these systems. We examine the evolution from traditional methods, such as content-based filtering and collaborative filtering, to the sophistic