• Currently building bilingual QA resources, evidence-driven AI quality tools, an AI-native Quality Engineering workbench, and learning sites across AI-Native-QA-Workbench, ai-automation-test-starter, 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 AI-Native-QA-Workbench as a local-first Quality Engineering workbench that connects requirements, quality risks, tests, execution, evidence, and human-controlled decisions; its v0.1 MVP is now in place
• Developing ai-automation-test-starter with a v0.1 deterministic Pytest API vertical slice and framework-native Learn, Build, Verify, and Ship flows
• Advancing ai-native-qa-agents through v0.4 Test Effectiveness & Mutation, with bounded mutation evidence, effectiveness scoring, trace persistence, and quality gates
• Shipping quality evidence tools: QCov reached v1.0 with change-to-obligation impact analysis and adapter SDKs, while ai-test-auditor v1.2.1 keeps source-only JavaScript/TypeScript auditing and advisory workflow semantics
• Evolving awesome-qa-skills through v1.5.2 Skill Router & Evaluation Pilot Hardening, with bilingual composition routes and verifiable offline eval traces
• Building dsh-qa as a QA workbench plugin for DeepSeek Harness; v0.5.0 now uses the official Panel/Slot API for native integration
• Building reusable Codex Skills for structured workflows, including Markdown-first learning plans, release delivery, and version DoD evidence
• 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 on performance, observability, and quality engineering

• Production Incident Analysis: From incident timeline to containment, validation, and retrospective actions
• Production Verification: Verify business flows, metrics, logs, and rollback conditions after release
• Root Cause Analysis: Move from symptoms to hypotheses and find a verifiable root cause
• Distributed Trace Analysis: Use a trace to locate cross-service latency and error propagation
• Log Analysis: Cluster errors at scale and locate post-release issues
• Metrics Anomaly Analysis: Use anomalous metrics to locate the time window, impact, and candidate causes

View all articles

Testing Tools

Languages

AI & Prompting

Web & Docs

DevOps

An AI-native, local-first Quality Engineering workbench that connects requirements, quality risks, tests, executions, and evidence into traceable quality decisions. The v0.1 MVP includes local contracts, deterministic validation, controlled agent workflows, a local API, and a bilingual UI.

A beginner-first, AI-native test automation kit. Its v0.1 Pytest API slice keeps framework-native behavior and connects Learn, Build, Verify, and Ship with deterministic checks and explicit evidence boundaries.

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. v0.4 adds a bounded Test Effectiveness & Mutation workflow with traceable mutation evidence.

A Quality Evidence Gap Engine that shows what tests and reports still do not prove about a requirement, risk, or code change. v1.0 adds change-to-obligation impact analysis and a public adapter SDK.

A local-first CLI that audits JavaScript and TypeScript test source for deterministic FAKE and WEAK signals before false confidence ships. The current stable release is v1.2.1.

A bilingual AI-native Quality Engineering skill system with 328 skills (zh+en), 10 workflows, 149 testing types, and 5 skill-engineering skills. The v1.5.2 release adds Composition Router and Evaluation Pilot hardening.

A local QA workbench plugin for DeepSeek Harness, covering AI-assisted requirements, cases, defects, milestones, reports, kanban, and calendar views. v0.5.0 uses the official Panel/Slot API for native host integration.

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

A bilingual QA Prompt Baseline covering 256 capabilities and modules across requirements, test design, automation, performance, security, release, production quality, and AI testing.

If you find my work helpful:

Thank you to the following supporters for their kindness:

_18773050607

_{Made with love by Nao Deng}