• Currently building bilingual QA resources, evidence-driven AI quality tools, and learning sites around awesome-qa-skills, ai-native-qa-agents, QCov, ai-test-auditor, dsh-qa, and naodeng.com.cn
• Focused on AI-native quality engineering, quality evidence, test quality auditing, and practical testing knowledge sharing
• I regularly write articles on https://inaodeng.com
• How to reach me: dengnao@gmail.com
• Twitter: @inaodeng

• Building evidence-driven AI-native quality agents with controlled runtimes, deterministic checks, bounded model reasoning, and verification gates
• Developing quality evidence tools: QCov exposes unproven requirements and risks, while ai-test-auditor finds deterministic signs of ineffective JavaScript and TypeScript tests
• Building reusable Codex Skills for structured workflows, including Markdown-first 30-day learning plan projects
• Building dsh-qa as a QA workbench plugin for DeepSeek Harness, covering AI-assisted requirements, test cases, defects, reports, kanban, and calendar workflows
• Publishing hands-on learning plans for DeepSeek QA and AI Agent engineering, covering APIs, tool calling, MCP, RAG, evals, and multi-agent collaboration
• Maintaining bilingual QA skills and prompts for Codex, Cursor, Claude Code, Kiro, OpenCode, and Trae
• Growing inaodeng.com as a bilingual testing site with structured learning paths, glossary content, and blog series

• Cypress UI Automation Testing: Build reliable regression with stable locators and controlled data
• Selenium UI Automation Testing: Build reliable regression with stable locators and controlled data
• WebdriverIO UI Automation Testing: Build reliable regression with stable locators and controlled data
• Automation Testing: Decide what to automate before choosing tools and frameworks
• Test Report Review: Check whether conclusions, evidence, and release impact align
• Playwright UI Automation Testing: Build reliable regression with stable locators and controlled data

View all articles

Testing Tools

Languages

AI & Prompting

Web & Docs

DevOps

An evidence-driven reference architecture for AI-native quality agents, with controlled runtimes, deterministic analysis, bounded model reasoning, and verification gates across the delivery lifecycle.

A Quality Evidence Gap Engine that shows what tests and reports still do not prove about a requirement, risk, or code change.

A local-first CLI that audits JavaScript and TypeScript test source for deterministic FAKE and WEAK signals before false confidence ships.

A bilingual AI testing skills library with 4 workflows, 25 testing-type skills, 58 skill folders with language parity, install scripts, and eval-ready checks.

A local QA workbench plugin for DeepSeek Harness, covering AI-assisted requirements, cases, defects, milestones, reports, kanban, and calendar views.

A bilingual testing blog and learning site built around automation practice, testing encyclopedia content, structured series, and searchable QA resources.

A QA prompt library covering 15 testing modules and 3 workflows, with standard, framework, and platform-specific variants.

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_{Made with love by Nao Deng}