Teach AI to Answer Questions Based on Your Documents
I started a 2026 series revisiting document-grounded AI systems, beginning with RAG architecture, Azure vs open-source stacks, and when fine-tuning makes sense.
Writing on Azure AI, localization infrastructure, and production LLM systems.
Field notes, architecture decisions, and implementation tradeoffs from practical AI and developer tooling work.
Fixing Broken Markdown in AI Translation
Hardening Co-op Translator after real Markdown failures in multilingual documentation.
Treating Documentation Translations as Versioned Software Assets
Why translation maintenance started to look more like dependency management than content generation.
Stop Translating Docs Manually
Explaining Co-op Translator v0.8 as a shift from manual translation to continuous repository maintenance.
Plan and Prepare to Develop AI Solutions on Azure
Presenting Azure AI planning decisions before writing the first line of implementation code.
Building an AI Chatbot with Azure OpenAI
Turning Azure OpenAI teaching material into a beginner-friendly Microsoft Korea video.
Building a Basic Chatbot with Azure OpenAI
A compact starter guide built to help new developers reach their first working Azure OpenAI loop.
How Co-op Translator Became an Azure Open-Source Project
How a translation automation tool grew into Microsoft open-source infrastructure.
Diving into Co-op Translator with Azure at Microsoft Reactor
Presenting Co-op Translator as a full workflow: setup, CLI usage, costs, automation, and maintainability.
Unlocking Multilingual Mastery with Co-op Translator
Framing multilingual documentation as an engineering workflow rather than a translation convenience.
Co-op Translator on Open at Microsoft
Presenting Co-op Translator through the Phi-3 Cookbook accessibility case study.
Automating Markdown and Image Translations with Co-op Translator
The Phi-3 Cookbook case study moved my public work from Azure AI tutorials into documentation infrastructure.
Evaluating Fine-Tuned Phi Models with Responsible AI in Mind
Fine-tuning is not complete until the model has been evaluated for safety and quality.
Fine-Tuning Phi-3 with Azure AI Studio
The low-code companion path for fine-tuning and integrating custom Phi models.
Fine-Tuning Phi-3 and Integrating It with Prompt Flow
A code-first guide connecting dataset preparation, Azure ML, deployment, and Prompt Flow.
Teaching ChatGPT to Answer Questions with Azure AI Search
The Azure AI tutorial that shaped my public writing around document-grounded AI systems.