CURRENTLY BUILDING
Systems for capable, reliable LLM agents.
I work across agent runtime engineering and post-training, with a focus on simple architectures, measurable behavior, and lessons earned from real implementations.
SELECTED PROJECTS
Built to learn, tested by use.
AGENT RUNTIME
NanoDeer
A reference implementation for LLM agent runtime engineering: native ReAct loop, sandbox isolation, flat-file memory, and SSE streaming.
View project ↗
POST-TRAINING
AlignSQL
Qwen3-8B Text2SQL post-training from supervised fine-tuning through reinforcement learning.
View project ↗
CREATIVE SKILL
Pindou Growth
A Codex skill that turns photos and memories into craftable fuse-bead keepsakes with adaptive grids, real palettes, and structural-growth GIFs.
View project ↗
SELECTED WRITING
Notes from the path to AGI.
多想、多做、边试、边学
从 Agent Harness、Post-Training 和项目重构中学到的事:先跑起来不等于做对,AI 可以提方案,但判断的尺子必须在自己手里。
Transformer 核心架构逐层拆解
从 Self-Attention 出发,逐层拆解 Transformer 的编码器、缩放点积注意力、多头注意力、掩码与位置编码,配合公式、架构图和 PyTorch 实现。
NLP 文本表征:Word Embedding + Tokenizer + BPE 算法全解
从 One-Hot、词袋和 TF-IDF 到 Word Embedding、Tokenizer 与 BPE,系统理解文本如何被映射到连续语义空间,并附完整代码实现。

