# Firebase Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/firebase
> Markdown URL: https://aitinkerers.org/technologies/firebase.md
> Technology record last updated: 2026-02-22T16:48:56Z
> Generated: 2026-09-23T06:38:48Z

Firebase is Google's mobile and web app development platform: a comprehensive, serverless Backend-as-a-Service (BaaS) for building, improving, and scaling applications.

Firebase is a powerful, integrated platform from Google, offering a suite of nearly 20 products for developers targeting iOS, Android, web, and Unity. It eliminates backend complexity: services like Cloud Firestore (a NoSQL database) and Firebase Authentication (supporting providers like Google, Facebook, and Apple) handle infrastructure automatically. Developers use Firebase Hosting for global Content Delivery Network (CDN) deployment and Cloud Functions for running serverless backend logic. Post-launch, tools like Crashlytics and Google Analytics for Firebase provide crucial performance monitoring and user behavior data, ensuring the app scales reliably and efficiently.

- Official technology site: https://firebase.google.com/
- Public AI Tinkerers demos and talks: 23
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Bifrost - Coding Agents on Mobile](https://dubai.aitinkerers.org/talks/rsvp_RvVz3i3dCNE)

Often we start a conversation on Codex CLI or Claude Code and need to walk away from the laptop. It would be extremely useful to be able to fully control our terminals via our mobile phones. Bifrost does this - you can remotely start Codex/Claude sessions, run terminal commands, respond to requests and so on. All from an app on your phone.

- Event context: AI Tinkerers Dubai - May Demo Day — 2026-05-23 — Dubai
- Public talk page: https://dubai.aitinkerers.org/talks/rsvp_RvVz3i3dCNE

### [How Personalized AI Outputs Turned Our Internal Tool Into a Product](https://chicago.aitinkerers.org/talks/rsvp_V18d7zsohTA)

Food Blog Studio is a SaaS that provides food bloggers with 10+ AI powered tools to speed up their day to day workflows. Demo context: Walkthrough of the full app, show off how personalization works and how it matches the users voice/tone/context, the transition from "internal tool" to "tool with users"

- Event context: AI Tinkerers Chicago: April Meetup ft OneTwoLoop — 2026-04-14 — Chicago
- Public talk page: https://chicago.aitinkerers.org/talks/rsvp_V18d7zsohTA

### [How I Built a Presentation Coaching App in 4 days — With AI as My Engineering Partner](https://hong-kong.aitinkerers.org/talks/rsvp_XloItk_-8gA)

After Chinese New Year this year, I was preparing to teach two modules in the Masters of Economics programme at The University of Hong Kong. My sessions aren't lectures. They involve constant class interaction — students learning by doing, presenting, and getting real-time feedback. Four days before I was due to teach Effective Public Speaking on February 23rd, a thought hit me: what if there was an app for this? Not a slide deck. Not a worksheet. A proper interactive platform that could guide students through the entire process of building a presentation — from structuring their argument to generating slides. That idea became SpeakReady. ## The Approach: Discipline First, Speed Second I could have hacked something together over a weekend. Instead, I chose to treat this like a professional software project — and used AI as my development partner to make that possible. The technology behind SpeakReady is modern (Next.js, React, TypeScript, Firebase, OpenAI), but the real story isn't the tech stack. It's the engineering discipline I was able to maintain, even as a solo builder working at speed. Every feature followed the same rigorous process: define requirements, design the solution, write tests, build it, scan it for quality issues, and ship it through a proper pipeline. AI didn't replace that discipline — it made it achievable. ## Discovery Before Code Before a single line of code is written for any feature, the process starts with discovery. I write detailed design documents that explore the problem, propose two or three architectural approaches with trade-offs, and arrive at a recommended solution. These aren't vague briefs — they specify API contracts, data flows, component hierarchies, and error handling strategies. For example, when I built the AI Wand feature (a button that helps students generate content for any text field using context from their previous work), the design document defined the API request and response shapes, the prompt engineering strategy, rate limiting rules, and exactly how the feature would integrate with five different form types — all before implementation began. Every design document is committed to the repository alongside the code it describes. Requirements aren't lost in chat threads or email chains. They live with the project. ## Testing as a First-Class Citizen Quality isn't something I bolt on at the end. The project uses three layers of quality assurance. **BDD Feature Files.** Every major feature is described in plain-English Gherkin scenarios before development starts. Statements like *"Given I have a team project, When I click Invite, Then I should see the member with Pending status"* define exactly what success looks like — in language anyone can read and validate. **End-to-End Tests.** Fourteen Playwright test suites cover the application's critical flows: authentication, the student dashboard, admin functions, framework forms, AI generation, team collaboration, mobile responsiveness, and more. These tests run against real Firebase emulators, testing the full stack from browser to database. **SonarQube Scans.** Every change is scanned for code quality, security vulnerabilities, and maintainability issues. The scanner analyses the TypeScript source code and flags anything that falls below professional standards. ## Git as the Backbone The project uses Git not just for version control, but as an orchestration layer. Each feature is developed in an isolated worktree — a completely separate working copy of the codebase — so multiple features can progress in parallel without interfering with each other. Branches map to issues. Design documents, feature files, and implementation code all flow through the same pipeline: branch, build, test, review, merge. At last count, the project had managed over twenty parallel worktrees across its development history. That's a level of organisational rigour that would be impressive for a team. For a solo builder with AI assistance, it's transformative. ## What This Means for You You don't need to be a software engineer to take something away from this story. The barrier to building real, professional-quality tools has dropped dramatically. What matters now isn't whether you can write code — it's whether you can clearly define what you want, insist on quality at every step, and use AI to bridge the gap between idea and execution. Four days before I walked into a classroom at HKU, SpeakReady was just a thought. The discipline made it real. The AI made the discipline possible.

- Event context: AI Tinkerers Hong Kong GBA at the Hive: Creative AI Demos & Technical Show-and-Tell — 2026-03-26 — Hong Kong
- Public talk page: https://hong-kong.aitinkerers.org/talks/rsvp_XloItk_-8gA

### [Gist - Read More. Think Deeper. Learn Faster.](https://orange-county.aitinkerers.org/talks/rsvp_h9HyI5ORZ1U)

**If you are suffering from information overload, Gist is for you.** Gist is a browser extension that distills research papers, YouTube videos, and webpages into structured understanding — without opening a new tab. Hit the button and an overlay appears on top of the page you're already reading. If you have 47 unread Arxiv.org tabs open right now — Gist is for you. If your appetite for learning exceeds your time budget — Gist is for you. --- Most AI summarizers give you slop. Gist structures content the way a PhD would — differently depending on what the content actually is. **Arguments → Logical structure:** Thesis, evidence, counter-argument, synthesis. Built for research papers and analytical content. **Stories → Dramatic structure:** Situation, complication, question, resolution. The shape every good story already has. --- **Gist goes beyond summarization** when it detects an argument: **Counter-argument:** The strongest possible case against the author's position — not a disclaimer, the actual objection. **Steelman:** An even stronger version of the author's argument, rebuilt from scratch. You don't just learn what the author thinks. You learn exactly where they might be wrong. Gist makes the: - Complex → Comprehensible - Boring → Interesting - Slow → Fast It’s a graduate school seminar in your browser, on-demand. ⸻ **One click. Layered understanding.** - First slide: One sentence — the irreducible core of the entire piece - Swipe: Context, complications, evidence, counter-arguments - Stop anytime: You control the depth - No new tabs: Gist overlays the page you’re reading The original is always there. Gist is a pre-read — helping you decide whether to invest the time, and priming your mind to comprehend it if you do. ⸻ **Share the Gist** Share the Gist of anything as a link. - Recipient doesn’t need Gist installed - Recipient doesn’t need to sign up - They click, they see the same Gist you saw (with a link to the original) Share the Gist of a 40-page arXiv PDF in a Slack message. Send the Gist of a 2-hour YouTube podcast over WhatsApp. Gist is your Instagram filter for the internet.

- Event context: AI Tinkerers OC - March 11, 2026 Meetup — 2026-03-12 — Orange County
- Public talk page: https://orange-county.aitinkerers.org/talks/rsvp_h9HyI5ORZ1U

### [I will showcase a AI assistant to assist you for your career tracking / coaching / resume building / linkedin spamming](https://montreal.aitinkerers.org/talks/rsvp_7ABBZfBH7XU)

For the science fair, quick demo of the concept and also speak about my challenge of one startup every two months :-p

- Event context: AI Tinkerers Montreal - February 2026 Meetup — 2026-02-24 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_7ABBZfBH7XU

### [I built a browser that works without tabs](https://la.aitinkerers.org/talks/rsvp__xNwjDh60CI)

A browser without tabs? Yes, imagine a big canvas, like figma but the rectangles are actually chat windows, text editors, images, and regular browser windows. Everything is observed by a cognitive layer (called the "canopy") that gets all user-interactions at runtime and models the user behavior to create propositions. The founders vision on how AI-native operation systems can look like: https://disambiguate.substack.com/p/ai-wants-to-be-connective-tissue

- Event context: AI Tinkerers LA: February Builder Meetup & Live Demos — 2026-02-24 — Los Angeles
- Public talk page: https://la.aitinkerers.org/talks/rsvp__xNwjDh60CI

### [Engineering a Consistent Image Gen Pipeline for Augmentative and Alternative Communication](https://valencia.aitinkerers.org/talks/rsvp_Y29X1ZoMALk)

I’ll demo how I built an AI-powered pictogram workflow that combines three components: 1. An offline prompt-to-image matching architecture that maps user intent to the most relevant pictograms (generated or existing), including how I represent prompts, store image/text embeddings locally, and select candidates with lightweight retrieval—so the experience stays fast and consistent. 2. Pictogram generation using an image generation model (prompt → pictogram), including the constraints and post-processing steps I use to maintain a consistent pictogram style and usable output format. 3. A lightweight “AI builder” workflow that assembles pictograms into simple compositions, focusing on the interaction model and the data structures that make the builder feel like a practical tool rather than a one-off generator. The demo will walk through each workflow step-by-step, paired with technical implementation notes and lessons learned around consistency, latency, and reliability.

- Event context: AI Tinkerers Valencia January Meetup — 2026-01-29 — Valencia
- Public talk page: https://valencia.aitinkerers.org/talks/rsvp_Y29X1ZoMALk

### [The Secret to Stunning UI: How AI Helped Me Design and Ship InkyCards in 7 Days](https://cologne.aitinkerers.org/talks/rsvp_EmnVHJCgoK0)

In just one week, I took InkyCard, a conversational language learning app from an idea in my head to a production-ready product. This session isn’t just about generating code; it’s about using AI to solve the "Developer Design Gap" and build a brand with a soul. I will demo the InkyCards workflow, focusing on: The Design Extraction Hack: How to feed UI inspiration (from sites like Dribbble) into LLMs to generate custom design systems, ensuring your app doesn’t look "AI-generated." Building the "Soul": Using Gemini Nano and Higgsfield to create a unique app mascot and custom iconography, overcoming creative blocks and building an emotional connection with users. Production Speed-running: A look at the "Plan-First" prompting strategy and context management that allowed me to build complex features—like real-time AI conversations (Firebase Vertex AI) and "Tap-to-Learn" flashcard generation—without losing code quality. Technical Deep-Dive: State Management & AI: How to use Claude and AntiGravity to scaffold architecture that stays clean as the project grows. The Fresh Convo Rule: My framework for managing LLM context to prevent "code rot" and quality degradation.

- Event context: AI Tinkerers Cologne #2: Let's Build. — 2026-01-21 — Cologne
- Public talk page: https://cologne.aitinkerers.org/talks/rsvp_EmnVHJCgoK0

### [Preventing prompt injection: An MVP solution](https://amsterdam.aitinkerers.org/talks/rsvp_6fLf-ZhblUA)

DoneThat is an AI work tracker - it takes screenshots and analyzes those to automate time tracking. It has several opportunities for prompt injection: * A chat-based agent * "Memories" that refine processing * The screenshots themselves I will walk through the basics for preventing abuse (rate limiting, authentication, etc) but then focus on preventing prompt injection. I am working on this right now so can't say what the exact solution will be but most likely using LLMs to identify and flag potential abuse. I will walk through the options considered, why I selected the one I chose, and the final implementation on live data. Can also do a live demo.

- Event context: Trust & Security in AI Demo Night — Amsterdam Edition — 2025-12-16 — Amsterdam
- Public talk page: https://amsterdam.aitinkerers.org/talks/rsvp_6fLf-ZhblUA

### [AI Trainer](https://la.aitinkerers.org/talks/rsvp_mnNiCgw7LGA)

fitness app powered by AI agents to actually personalize training analysis and plans url included below but you need to be whitelisted to sign up

- Event context: AI Agentsgiving Los Angeles — November 20th, 2025 — 2025-11-21 — Los Angeles
- Public talk page: https://la.aitinkerers.org/talks/rsvp_mnNiCgw7LGA

### [Building VM Fitness Hub — A Headless AI-Powered E-Commerce and Content Platform](https://nyc.aitinkerers.org/talks/rsvp_u6I28r8KaRA)

In this demo, I’ll walk through the technical implementation of VM Fitness Hub, a fully headless e-commerce and content platform built with Next.js, Firebase, Stripe, and Google’s Genkit (Gemini) for personalization. We’ll go line-by-line into how the application connects front-end React components with Firebase server actions, integrates secure Stripe payments, and uses Genkit flows to power two AI features: a Workout Plan Generator that builds weekly routines from structured prompts, and a Shopping Assistant that uses tool-calling to dynamically search product data. The session will focus on code, architecture, and real implementation challenges — including environment configuration, authentication flow design, API security, and SSR optimization in Next.js 14. No slides. No pitch. Just raw build walkthrough: code, debugging, and deployment to Firebase App Hosting.

- Event context: November Demo Day ft. Google Cloud and CopilotKit — 2025-11-17 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_u6I28r8KaRA

### [MapScroll: Prompt to Maps within minutes](https://tokyo.aitinkerers.org/talks/rsvp_IUC2KCapZpk)

MapScroll is basically a copilot for maps which lets creators, educators, or explorers built and share narrative driven story rich maps. In the presentation, I can walkthrough several examples use cases along with some new experimental features that I am currently building.

- Event context: AI Tinkerers Tokyo Kickoff – October 10, 2025 — 2025-10-10 — Tokyo
- Public talk page: https://tokyo.aitinkerers.org/talks/rsvp_IUC2KCapZpk

### [Agentic Wallets and AI-Driven Patronage with Stablecoins](https://austin.aitinkerers.org/talks/rsvp_wIP36d0REp8)

I’ll walk through the design and implementation of ClamBot, an agentic wallet system that distributes patronage automatically based on AI-curated recommendations. The core idea: users deposit tokens, and autonomous agents allocate funds across creators, categories, and up-and-coming voices. I’ll demo how recommendation logic, fund distribution, and programmable vaults work, and how we’re extending this into “taste as currency.”

- Event context: AI Tinkerers Austin AI Demo Night w/ Google & Comet — 2025-10-09 — Austin
- Public talk page: https://austin.aitinkerers.org/talks/rsvp_wIP36d0REp8

### [Powering Up Games with AI](https://brisbane.aitinkerers.org/talks/rsvp__42WvF7v1Lg)

"Building the Future of Gaming: A Complete AR MMORPG with AI-Driven Content Generation" I'll present a comprehensive case study of developing B3200 AR Clean, a location-based AR MMORPG that seamlessly integrates React Native, Unity, Firebase, and Niantic Lightship ARDK. The presentation will demonstrate how I solved complex technical challenges including: Cross-platform AR integration using Unity embedded as an Android library with React Native bridge Real-time GPS-based building placement with Mapbox (React Native) and Niantic (Unity) coordinate synchronization AI-powered content generation using Firebase Functions with automated product creation, quest generation, and market analysis Direct Unity-Firebase integration bypassing traditional bridge limitations for real-time building data Advanced AR player movement with GPS tracking, gyroscope/compass controls, and laser combat systems The talk includes live demonstrations of buildings appearing in AR from Firebase data, AI-generated quests and products, and the complete build process from Unity export to Android APK deployment.

- Event context: AI Tinkerers – Brisbane Inaugural Meetup · 11 September 2025 — 2025-09-11 — Brisbane
- Public talk page: https://brisbane.aitinkerers.org/talks/rsvp__42WvF7v1Lg

### [GPU Sharing for AI Computations](https://nyc.aitinkerers.org/talks/rsvp_lTMJXnmec7s)

I’ll be demoing an app that lets you use the GPU of another computer to run AI computations. It works with Cursor so you can easily connect from your own machine and offload heavy AI work to a more powerful GPU elsewhere.

- Event context: AI Tinkerers August Demo Day ft. Auth0 and Comet. Demo what you've built! — 2025-08-26 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_lTMJXnmec7s

### [Leverage AI Web Agent + MCP in Your Own Browser](https://sf.aitinkerers.org/talks/rsvp_OQ_O1-hEPtU)

Demonstrate implementation and technical details of setting up MCP Oauth Client within Chrome Extension. Why calling MCP's with web agent context is a killer use case. How we are exposing our web agent as a MCP Server

- Event context: AI Tinkerers - Advanced MCP Showcase — 2025-06-19 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_OQ_O1-hEPtU

### [CEO](https://miami.aitinkerers.org/talks/rsvp_4XKrr6PPzOA)

Where's the spoon? Often we oversee some of the most basic needs a customer wants. Let's focus on bringing business value and lead with that. The end result.

- Event context: AI Tinkerers - Miami: Building the Future of AI in Miami Tech — 2025-04-22 — Miami
- Public talk page: https://miami.aitinkerers.org/talks/rsvp_4XKrr6PPzOA

### [FINDER AFRIC](https://nairobi.aitinkerers.org/talks/rsvp_EJjkc96NLNs)

Finder is an AI-powered shopping tool that lets buyers find exactly what they’re looking for just by using images. We’re building a platform where vendors don’t need to be known or followed to make a sale—if they have the product, we’ll match them with the buyer using visual search. I’ll be showcasing how Finder helps small vendors increase visibility and reach, and how we use cutting-edge image recognition to simplify product discovery.

- Event context: AI Tinkerers - Nairobi Inaugural Meetup (April) — 2025-04-09 — Nairobi
- Public talk page: https://nairobi.aitinkerers.org/talks/rsvp_EJjkc96NLNs

### [AI Junk Removal Workflow Hack](https://montreal.aitinkerers.org/talks/rsvp_pZb_wImr5iE)

In this talk, Marie Pelletier from Kanastruk shares how they integrated AI and cloud technologies to enhance junk removal and recycling processes, offering practical insights on automating workflows and improving customer interactions.

- Event context: AI Tinkerers Montreal - March 2025 Meetup at Shopify — 2025-03-12 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_pZb_wImr5iE

### [Hacking Together an AI-Powered Resale & Recycling Workflow](https://montreal.aitinkerers.org/talks/rsvp_Bmvo0-RszAE)

Aside from my developer dayjob, I'm co-owner of a junk removal and recycling company. We pick up unwanted items, sorts them for disposal, donation, or recycling. For the last few months, we’ve been throwing a mix of generative AI, computer vision, and cloud tech at a pretty gnarly problem—how to streamline everything from customer intake to reselling upcycled goods. Here’s what we’ve cooked up: • Photo-Based Job Evaluation: We use Hugging Face inference endpoints running on GPUs to clean up and segment images, helping us estimate object volumes for collection jobs. • LLM-Powered Product Descriptions & Inventory Sync: GCP endpoints manage our LLM calls, turning item photos into marketplace-ready product descriptions and syncing them with Shopify. • Live Transcription & Sales Insights: We’re experimenting with LiveKit for real-time call transcripts, helping phone operators with sales insights and CRM automation. • In-House Call Transcription System: We built our own system to transcribe and structure customer calls for CRM purposes—no reliance on third-party services. The demo will dive into the nuts and bolts—how we’ve wired up Firebase, GCP, OpenAI, Anthropic, Hugging Face hosting, Twillio and LiveKit to make all this work. I'll touch also on how using Cursor.ai really sped up our development.

- Event context: AI Tinkerers Montreal - March 2025 Meetup at Shopify — 2025-03-12 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_Bmvo0-RszAE

### [The Browser is Dead, Long Live AI Browser Agents](https://sf.aitinkerers.org/talks/rsvp_Xdizo7gUhLw)

The technical challenges of building an AI browser agents and important design choices

- Event context: AI Tinkerers - San Francisco - February 2025 Demos + Science Fair — 2025-02-28 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_Xdizo7gUhLw

### [Building AI Agents for Cancer cure - Optimizing protocol and trial design](https://nyc.aitinkerers.org/talks/rsvp_tK842VNu7zw)

This talk explores the practical applications and strategic integration of AI and GenAI in clinical trials. Clinical trial documents authoring and quality control is still riddled with inefficiency due to the time-consuming, expensive, and manual way of working. AI has the potential to transform this space. I've been developing AI agents to streamline and accelerate the protocol design process, potentially speeding up the pathway from treatment conception to protocol finalization. These agents are constructed using LangGraph and trained on proprietary data labeled by PhD scientists with pharmaceutical industry experience, ensuring accuracy and domain expertise. Firebase serves as the backend for knowledge embedding and agent memory management. The primary technical challenges involve securing high-quality training data and managing memory for agent workflows. outline of challenges including 1.State Management 2.Action Selection 3.Environment Interaction 4.Memory and Knowledge Base 5.AI guardrails. The live demonstration will consist of three parts: I will upload a clinical protocol and query the system about domain-specific topics such as patient demographics and endpoint design. I will showcase a medical writer agent capable of drafting protocols with human in the loop design.Lastly I will demonstrate how I build CICD pipelines on AWS. Finally I will share some technical challenges related to distributed training and model serving for optimized latency and throughput Takeaway : transforming clinical trials, reducing timelines, improving data integrity, and ultimately bringing treatments to patients faster.

- Event context: October Meetup at AI Tinkerers! — 2024-10-17 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_tK842VNu7zw

### [Polyfire - Javascript SDK to build AI apps](https://sf.aitinkerers.org/talks/rsvp_Q-V2NH2BwQU)

We are working on a simple simple JavaScript SDK to build AI apps without having to think about infrastructure. You code in your frontend using a LangChain-like library (polyfire-js) and your calls are routed to our hosted GoLang API (your managed backend). You can configure and interact with your managed backend on a dashboard at beta.polyfire.com. It is a Firebase like expérience to build AI apps quickly, with no backend.

- Event context: 🤖🔄🧠 AI Tinkerers SF - October Meetup — 2023-10-26 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_Q-V2NH2BwQU

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