Share request behavior across business APIs while handling protocol changes, existing callers, and retry conditions.
Contributed to APIs and led the merchant-funds SDK refactor and compatibility work.
Projects
Selected work and explorations in Python test infrastructure and AI-assisted test engineering.
Selected work
Work and personal projects selected for their engineering questions; each retains its actual stage.
Follow discovery and report validation through concurrent failures, deadlines, and missing results.
Defined scope and execution behavior; collaborated with AI on implementation and code review.
Ongoing practice
Work being developed, maintained, or documented; write-up status is separate.
Connect staged LLM generation, human review, and execution checks to turn generated code into useful test cases.
Build a staged LLM test-generation pipeline at work, combining AI-agent delivery with human review gates.
Exploration
Study, design, and planned experiments; inclusion does not imply completed experiments.
A planned project covering data, training, evaluation, and integration for a task within the AI testing workflow. Write-up in progress.
Plan to define the task, data and evaluation, run training experiments, and integrate the model. Practice details are being updated.
Interactive walkthrough →: From samples to adapters: SFT + LoRA