Connie Leung
Software Architect, GDE, Content Creator, Speaker
Hong Kong
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Connie is a software architect who is passionate about Angular, NestJS, AI, Web AI, and building stuff with JS frameworks. She loves coding with Angular and NestJS, and blogging about these topics to share knowledge with members in the communities. She also demos Web AI technology on her YouTube channel, allowing web developers to integrate AI into their web applications. Her hobbies are blogging, running, language learning, and attending conferences to meet new friends. She hopes to be able to present at meetups and conferences in Spanish, Mandarin, and other foreign languages fluently one day.
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Build a Offline, Privacy-first Personal Finance Assistant with LiteRT JS and Gemma 4
Get hands-on with LiteRT.js and Google's open-source Gemma 4 models. Learn to retrieve models from Hugging Face and leverage WebGPU for high-performance in-browser inference.
Key Takeaways: Setting up LiteRT-LM; optimizing WebGPU for browser acceleration; designing offline-first security.
Slide Deck: https://docs.google.com/presentation/d/1uurdocDeLhBKhYf1K4IKFg066LD5v-VFAQbskWA18DA/edit?usp=sharing
YouTube: https://youtu.be/shFsYiugCjE?si=_pPx1TwbItNJopUS
In-Browser AI Meets the Cloud: Building Smarter Web Apps with Firebase
To build fast and cost-effective web applications, developers can split AI workloads between the user's browser and the cloud using Firebase. This talk demonstrates this hybrid approach through a live web app demo: we use a lightweight, in-browser model (Gemini Nano) to quickly handle simple client-side tasks like generating image descriptions and alt text, while routing complex demands—like live web searches and image generation—to powerful cloud-based models like Gemini Flash. Attendees will learn how to implement this practical workflow to balance performance, cost, and user experience in their own web projects.
Agentic Auditor: Spotting the Gaps with AI Reasoning
Most AI implementations focus on retrieval—finding information that exists. But in high-stakes industries like compliance, legal, and ESG, the most critical question isn't "What is there?" but rather "What is missing?"
Traditional RAG (Retrieval-Augmented Generation) patterns often fail at gap analysis because they rely on semantic similarity, which struggles to identify incomplete information. To solve this, we need to move from simple pipelines to Agentic Reasoning.
In this session, I will demonstrate an Agentic Auditor that performs automated gap analysis of an answer against a structured checklist. We will dive deep into how an agent can "reason" through a checklist to identify semantic discrepancies and missing requirements.
Go deep with Nano Banana - Use Angular + Firebase AI Logic to build a Photo Edit App
In this session, I want to show that Firebase AI Logic, Angular and Nano Banana make photo editing easy.
in the session, I can show photo creation, editing, fusing, restoration, and 2D-to-3D transformation.
Build Dynamic Apps in AI: Decouple Prompts with Firebase & Angular
Hardcoding AI prompts in frontend JSON files creates a deployment bottleneck every time you need to tweak an image style or fix a hallucination. In this session, we will build a scalable Angular v21 app that decouples its AI logic using Firebase Server Prompt Templates. Learn how to move Nano Banana 2 prompts to the cloud, manage versioning with Remote Config, and connect real-time `onConfigUpdate` listeners to Angular signals to push live AI updates instantly - zero redeployments required.
Slide Deck: https://docs.google.com/presentation/d/1CNvkiGkMMhFk3NLa9zvV121QFZ6VoDw9IKIPcBSEM7w/edit?usp=sharing
From Prompt to 100 Lighthouse: Building Firebase & Angular Apps with Antigravity CLI and MCP
In this session, I share what I learned about hooking Model Context Protocol (MCP) servers and agent skills into an everyday Angular and Firebase development workflow using Antigravity CLI and Gemini:
* Architecture stress-testing with skills: Using custom skills to question assumptions, catch edge cases, and force an actionable architectural plan before writing boilerplate.
* Prototyping with Stitch MCP
* Automating cloud setup: Using Firebase MCP and CLI to provision projects, sync Remote Config, and deploy via Firebase App Hosting.
* Scaffolding and testing: Using Angular CLI MCP to generate features, run test suites, and inspect real code coverage directly in the workflow.
* Chasing 100 Lighthouse: Spotting bottlenecks with Chrome MCP and tackling the challenge of lazy-loading heavy Firebase modular SDKs to keep main.js lean.
Key Takeaways:
1. Minimize context switching between the Firebase web console, project CLIs, and disconnected terminal tabs.
2. Unified UI Source of Truth.
3. Divert developer energy away from repetitive boilerplate and manual setups toward profiling bundle size, refactoring heavy Firebase dependencies, and achieving a 100 Lighthouse score.
The content comes from my traditional Chinese blog post series: https://ithelp.ithome.com.tw/users/20168314/ironman/9463
Connie Leung
Software Architect, GDE, Content Creator, Speaker
Hong Kong
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