# React Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/react?page=2
> Markdown URL: https://aitinkerers.org/technologies/react.md?page=2
> Technology record last updated: 2026-09-18T15:13:52Z
> Generated: 2026-09-21T16:33:30Z

React is an open-source JavaScript library for building dynamic user interfaces (UIs).

React is a component-based JavaScript library, developed by Meta (Facebook), engineered for building fast, declarative UIs. It mandates a one-way data flow and utilizes a Virtual DOM mechanism to ensure efficient, predictable updates to the user interface. Developers construct complex UIs by composing small, encapsulated components; this architecture promotes code reusability and simplifies state management across large applications. The library employs JSX (a syntax extension) to integrate HTML-like markup directly within JavaScript logic, supporting development for both web (React DOM) and native mobile platforms (React Native).

- Official technology site: https://react.dev/
- Public AI Tinkerers demos and talks: 220
- Result page: 2 of 10

## 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

### [Edge Power](https://pereira.aitinkerers.org/talks/rsvp_SRDHdkG1fCM)

I built an IoT-based energy monitoring and optimization platform developed with Next.js, designed to collect, process, and visualize real-time data from distributed devices and edge computing systems. During the live demo, I will showcase the working platform, including the web dashboard, real-time device communication workflow, system architecture, Dockerized deployment structure, source code organization, MQTT/WebSocket data flow, logs, and the integration between embedded devices and the visualization platform. I will also present the repository structure and the overall data processing pipeline running in a functional environment.

- Event context: AI Tinkerers Pereira: Builders Session - Engineering Week Edition — 2026-05-21 — Pereira
- Public talk page: https://pereira.aitinkerers.org/talks/rsvp_SRDHdkG1fCM

### [AI for people who still print their email: how we put a 25-tool agent in front of 50-year-old accountants without a single hallucinated delete](https://poland.aitinkerers.org/talks/rsvp_d3AEfot6ruQ)

Numonis is an accounting SaaS in Spain and Portugal where the primary users are 40–60-year-old SMB owners and accountants, and we shipped a pydantic-ai conversational agent with 25+ tools (invoicing, documents, banking, P&L, tickets) as the main interface. Live demo: I run a demo of the system's features all over one typed SSE stream. Between beats I flip to DevTools to show the raw frames so the wire protocol is visible end to end.

- Event context: AI Tinkerers Poland #3 - Meetup in Wrocław — 2026-05-06 — Poland
- Public talk page: https://poland.aitinkerers.org/talks/rsvp_d3AEfot6ruQ

### [Coding is Solved. Next Up: Figure Out How to Plan](https://seattle.aitinkerers.org/talks/rsvp_-1Uv6ETOTq8)

I built an Agent-Native Google Docs to review, edit, and share plans in Markdown

- Event context: AI Dev Tools Track - Seattle — 2026-05-06 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_-1Uv6ETOTq8

### [ViteVoyage](https://lausanne.aitinkerers.org/talks/rsvp__1PvyFZ3DEs)

AI powered travel planner

- Event context: AI Tinkerers Lausanne April 2026 Meetup — 2026-04-30 — Lausanne
- Public talk page: https://lausanne.aitinkerers.org/talks/rsvp__1PvyFZ3DEs

### [\[UW Data Science Club x HFF\] ParcoursLab: A Human-Centered Approach To Course Recommendations](https://toronto.aitinkerers.org/talks/rsvp_hbsKwKccnH8)

ParcoursLab is an academic co-pilot that saves students and academic advisors time by building a course plan that respects degree requirements and pre-reqs while also taking into account your goal, desired skills, extracurricular interests, and crowd-sourced student ratings. We use AI to automate the manual bookkeeping of reading through dozens of course descriptions and checking prereqs/eligiblity. However, despite this, the platform aims to be transparent, human-centered, and hallucination-free by retrieving course skills from a human-curated skills database (ESCO), providing you with justifications for each of its selection, and allowing you to update your plan conversationally. In the linked demo, the student picks "Computer Science" as their major and "bioinformatics" as their goal. They also mention their interest in Music and Art. Our platform fetches your degree requirements and lays out your required courses (e.g. algorithms, operating systems) using ASAP/ALAP scheduling. Your goal is used to derive a set of desired skills (e.g. biochemistry, machine learning), matched against the ESCO database, which in turn guides a search for the ideal electives. We perform course recommendation using an LLM on a UWaterloo dataset deterministically distilled based on prereqs and augmented with student ratings. We also find you school clubs that match your major, goal, and extracurricular interests (e.g. Waterloo iGEM, Visual Arts club). Courses can be dragged around, and prereqs are enforced. You can chat to replace courses. Adding a desired skill manually will add a course to your schedule that fulfils that skill. Lastly, the user can generate a printable AI summary that they can take to a meeting with an academic advisor for final human guidance.

- Event context: AI Tinkerers Toronto - April 2026 - hosted by Shopify — 2026-04-29 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_hbsKwKccnH8

### [Ask the Oracle Before You Decide : Simulating the Future with LLM Agents](https://toronto.aitinkerers.org/talks/rsvp_VTeGGfFVq8g)

Pythia is an LLM-powered simulation engine that models how individual cognitive biases and crowd psychology interact to shape real-world decisions, before those decisions are made. For the demo: you give it a scenario (a market move, a policy choice, a personal decision under pressure), and it spins up a cast of behaviorally-distinct AI agents, each carrying a named bias like Loss Aversion, FOMO Drive, or Anchoring and drops them into a live crowd field. You watch opinion dynamics unfold tick by tick. At a critical moment, one agent is sent to the Temple of Learning: their behavior is evaluated, their rules are amended, and they re-enter the simulation. Run over run, the system gets more accurate. The visualization shows all of it : the crowd state, the agent trajectories, the oracle's intervention, the improving accuracy curve.

- Event context: AI Tinkerers Toronto - April 2026 - hosted by Shopify — 2026-04-29 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_VTeGGfFVq8g

### [Multi-agent Claude Code at scale: building Parthas at Intercom](https://dublin.aitinkerers.org/talks/rsvp_qYginBx6EOk)

Parthas is a multi-agent orchestrator for Claude Code that coordinates parallel coding agents through software instead of agent-to-agent messaging. In this demo I'll run it live against a real codebase. I'll spin up several agents in isolated worktrees, show the permission queue and the web dashboard, and walk through the design principles that keep it fast without YOLO-ing your main branch.

- Event context: AI Tinkerers Dublin: Demo Night with Fin — 2026-04-28 — Dublin
- Public talk page: https://dublin.aitinkerers.org/talks/rsvp_qYginBx6EOk

### [The Autonomous Data Platform](https://denver-boulder.aitinkerers.org/talks/rsvp_trQMLCPz4zA)

Most tools make data teams more efficient. We've built a solution that makes them obsolete, by automating the data platform work end-to-end. Rather than specialized roles (e.g., data engineers, scientists, analysts), one expert manages a team of AI agents that handles the entire data workload, from building data pipelines, to dashboards, to analytics.

- Event context: AI Tinkerers Denver - April Meeting — 2026-04-27 — Denver
- Public talk page: https://denver-boulder.aitinkerers.org/talks/rsvp_trQMLCPz4zA

### [Agentic AI for Engineering Data Analysis](https://karlsruhe.aitinkerers.org/talks/rsvp_6navkmqO9Ss)

Our Onion project is an agentic AI system that helps mechanical engineers to analyse test-, fleet- and production data. In the demo I'll introduce the use case and its requirements. I'll also show some key components for the system: Data infrastructure to handle sensor data efficiently, how to shape context in the AI harness, role of UI/UX for engineers.

- Event context: AI Tinkerers Karlsruhe: April Build Night — 2026-04-23 — Karlsruhe
- Public talk page: https://karlsruhe.aitinkerers.org/talks/rsvp_6navkmqO9Ss

### [Your GTM Copy Only Reaches 32% of Buyers — Here's How to Measure It](https://seattle.aitinkerers.org/talks/rsvp_UuJIGqJNdf0)

COS is a content measurement engine that scores how well B2B sales and marketing copy resonates across all five buyer personality types (Big Five/OCEAN). It orchestrates 7 parallel analysis frameworks through a 24-module knowledge base (~38K lines of psychology research) to surface which buyer segments you're reaching and which you're missing. Live at cos.semalytics.com, free guest mode, no signup.

- Event context: AI Tinkerers Seattle: GTM Engineering — April Meetup — 2026-04-23 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_UuJIGqJNdf0

### [Building a Real-Time Terminal Messenger on LinkedIn's Private APIs with Bun, Ink, and a Git-Backed Message Store](https://seattle.aitinkerers.org/talks/rsvp_0AqXN-gxTTM)

Allman is a two-layer system for LinkedIn messaging from the terminal: a CLI that syncs, sends, and streams LinkedIn messages into a git-versioned file store, and a TUI that renders it as a full two-pane Ink/React terminal messenger with live updates, auto-backfill, and real-time presence. The demo shows the TUI in action — navigating conversations, composing replies, watching the status bar update as messages stream in over LinkedIn's SSE channel, and kicking off a sync that backfills an entire conversation history while showing live progress counts. Under the hood, the TUI never touches the network directly. Every write — sends, syncs, searches — shells out to the lilac binary, which is embedded inside the compiled TUI executable as a bundled asset. Every read — conversation list, message thread, slug lookup — goes straight to JSONL files on disk, so navigation is instant with zero subprocess overhead per keystroke. The key learning or takeaway is that private APIs, even when obfuscated, are easily reverse-engineered by coding harnesses. Claude Opus 4.6 processed the compiled LinkedIn binary overnight, completely autonomously.

- Event context: AI Tinkerers Seattle: GTM Engineering — April Meetup — 2026-04-23 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_0AqXN-gxTTM

### [Building an AI Cyber Threat Intelligence Dashboard](https://atlanta.aitinkerers.org/talks/rsvp_N1oUwQ-s0Q8)

I built an executive-focused cybersecurity dashboard that aggregates and analyzes threat intelligence from multiple sources to generate a concise, AI-powered daily briefing with verifiable source attribution. In the demo, I walk through the full pipeline—from ingesting data via RSS feeds, web scraping, and MalwareBazaar, to normalizing and enriching indicators, deduplicating and clustering signals, and finally generating a real-time “What’s Happening Today” brief. The system is exposed through backend APIs and a React interface where users can refresh feeds and regenerate structured incident summaries on demand.

- Event context: AI Tinkerers Atlanta: Community Demos & Technical Deep Dives — 2026-04-21 — Atlanta
- Public talk page: https://atlanta.aitinkerers.org/talks/rsvp_N1oUwQ-s0Q8

### [Using Storybook To 10X Frontend Dev With Coding Agents](https://singapore.aitinkerers.org/talks/rsvp_Rgvf7fv-1Qg)

Implemented Storybook in an open source project where Storybook became the main development surface for frontend work. Experimented and over time, developed a heavily storybook driven approach for frontend development that works really well with frontier coding agents. Demo points: - Intro to storybook - Why storybook makes sense today with coding agents - Key benefits: Cleaner code structure, improved coding agent results, significantly less manual QA - How to use storybook descriptions to provide live intent to the coding agent - How to set up a long running task with feedback to solve a complex frontend problem

- Event context: AI Tinkerers Singapore: The Agentic Future & Dev/Eng Workflows — 2026-04-21 — Singapore
- Public talk page: https://singapore.aitinkerers.org/talks/rsvp_Rgvf7fv-1Qg

### [From AI Slop to Beautiful: Automated Frontend Redesign with TinyFish + Claude](https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_JSBl9hedRKQ)

A pipeline that takes any ugly AI-generated frontend, researches what best-in-class websites in your industry actually look like using TinyFish’s deep web research, generates a design brief from those findings, and then dispatches a Claude agent to rewrite the UI — all ending with a GitHub PR you can review and merge. One command turns a generic AI-generated site into something that looks like a real product.

- Event context: AI Tinkerers Ho Chi Minh City: AI Coding Agents & Orchestrators — 2026-04-18 — Ho Chi Minh City
- Public talk page: https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_JSBl9hedRKQ

### [Make Vibe Coding Actually Ship](https://manchester-nh.aitinkerers.org/talks/rsvp_7TM9RW-g9VM)

I built ForgeOS, a simple system for turning AI-generated ideas into working software through a structured, repeatable loop. In this demo, I’ll show how a single feature goes from idea → defined requirements → built code using multiple AI tools without losing context or control.

- Event context: AI Tinkerers Manchester (Bedford), NH - April 2026 Meetup — 2026-04-15 — Manchester NH
- Public talk page: https://manchester-nh.aitinkerers.org/talks/rsvp_7TM9RW-g9VM

### [What Happens When You Put an AI Dev Team on a Mac Mini?](https://chicago.aitinkerers.org/talks/rsvp_lY6IQju70NA)

I built a local AI agent development team on a Mac Mini to support software development for HausHavn, a real estate workflow platform. Instead of using AI for one-off prompts, I set up separate agents with clear roles across architecture, coding, QA, product analysis, documentation, and project management. The demo shows how I orchestrate those agents through real development work, including task handoffs, code review, GitHub issues, Notion sync, release QA, and the messy lessons of making agents useful as process infrastructure, not magic.

- Event context: AI Tinkerers Chicago: April Meetup ft OneTwoLoop — 2026-04-14 — Chicago
- Public talk page: https://chicago.aitinkerers.org/talks/rsvp_lY6IQju70NA

### ["From Noise to Signal: How a Team of AI Agents Turns Global Supply Chain Chaos into Actionable Intelligence"](https://st-louis.aitinkerers.org/talks/rsvp_EasqleNNKLg)

We built a supply chain intelligence platform that deploys a coordinated team of four AI agents to scan thousands of global news sources and instantly surface the events, risks, and patterns that matter most to traders, analysts, and executives. Demo context: Imagine you're a commodities trader. You need to know everything relevant about aluminum and tariffs — right now. Instead of spending 10 hours manually combing through 50+ news sources, you ask a single question. Within seconds, four AI agents divide the work: one decides which data domains to search, one plans the analysis strategy, one constructs precise database queries, and one synthesizes everything into a structured intelligence brief — complete with sources you can verify yourself.

- Event context: AI Tinkerers St. Louis: April 2026 Meetup — 2026-04-14 — St. Louis
- Public talk page: https://st-louis.aitinkerers.org/talks/rsvp_EasqleNNKLg

### [What did we learn from the March 31st Claude Code Source Leak?](https://seattle.aitinkerers.org/talks/rsvp_P82HqL1GQaM)

This technical analysis, presented by Daniel Motles of Qumulo in April 2026, dissects the architecture and leaked details of Claude Code. Claude Code is a Bun-native TypeScript application with a React and Ink terminal UI, functioning as a productized agent operating system. The system is composed of 1,902 source files totaling 512,685 lines of code. Its technical stack includes the Anthropic SDK, MCP integrations, and native tools for Git, Shell, and LSP. A major finding is the discovery of KAIROS, an always-on autonomous daemon that runs heartbeat prompts every 30 seconds to identify tasks, fix errors, and manage memory consolidation. Other unreleased features include Ultraplan for deep thinking via remote Opus variants, Coordinator Mode for spawning sub-agent forks, and an internal Undercover Mode that strips AI signals from public commit histories. The system utilizes a heavyweight persona driven by a massive system prompt and a four-tier MD memory system covering users, feedback, projects, and references. To preserve context window space, Claude Code uses deferred tooling and a local LRU cache to prevent redundant token consumption. Local search is handled by a parallelized Rust-based engine called RipGrep (rg). The analysis concludes that the engineering "plumbing"—the tools, memory, and safeguards—constitutes the product's primary competitive moat. While the leak has spurred open-source clones, it has also raised enterprise concerns regarding release hygiene and intellectual property safety.

- Event context: AI Dev Tool Track — Seattle Meetup - April 13th, 2026 — 2026-04-14 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_P82HqL1GQaM

### [Building Gemini Local Hub: Stateful Agentic Loops & Real-Time Thought Streaming](https://seattle.aitinkerers.org/talks/rsvp_rsrQ2Yl2vyg)

I’ll be doing a live code walkthrough of Gemini Local Hub, a local-first orchestration layer I built around @google/gemini-cli-core. We will dive straight into the Next.js App Router codebase to look at how I transformed stateless LLM CLI interactions into persistent, low-latency "warm" sessions using a Global Singleton pattern. I'll also demonstrate the architecture behind the asynchronous agentic pipeline (handling both automated "YOLO" tool execution and manual human-in-the-loop validation), and how I split the streaming channels to capture and render real-time model reasoning ("thought blocks") without polluting the primary UI state.

- Event context: AI Dev Tool Track — Seattle Meetup - April 13th, 2026 — 2026-04-14 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_rsrQ2Yl2vyg

### [Agentic Kanban: Making AI workflows behave like real teams](https://dublin.aitinkerers.org/talks/rsvp_p1H2f1yO4iM)

Agentic Kanban is a system that uses a Kanban-style interface to coordinate multiple AI agents as a structured workflow rather than a single loop. Instead of one agent doing everything, tasks move across a board and are picked up by role-specific agents (e.g. research, execution, QA), enabling iteration and review. In the demo, I’ll show how a high-level goal is broken into tasks, how agents collaborate through shared state, and how outputs are refined across multiple steps. The focus is on making agent systems behave more like real teams, including where this approach works and where it still breaks.

- Event context: AI Tinkerers Dublin Meetup — Baseline, April 9, 2026 — 2026-04-09 — Dublin
- Public talk page: https://dublin.aitinkerers.org/talks/rsvp_p1H2f1yO4iM

### [Replacing Analysts in commodity trading](https://zurich.aitinkerers.org/talks/rsvp_i8MtV8raWAE)

Informatiom system built to deliver what traders want in LNG / Gas speculative decisions. - Visualize Fundamentals - Machine Learning models - Automate processes (anomalies alerts, analyze competitors, check auctions) - Data architecture automation - News embeddings and semantic analyzes (check what moves the market) - Monitoring users for automated feedback

- Event context: AI Tinkerers Zurich April 9th — 2026-04-09 — Zürich
- Public talk page: https://zurich.aitinkerers.org/talks/rsvp_i8MtV8raWAE

### [Calendar Club](https://columbus.aitinkerers.org/talks/rsvp_PguV58U8t70)

Ambient deep-research agent that discovers in person events and automatically syncs them to the user’s calendar. Built with LangGraph, the agent runs a multi-step research workflow, asking clarifying questions and gathers feedback during the middle of the research. Finally the result is rendered as agenda of the next week’s related events to sync with the users calendar.

- Event context: AI Tinkerers - Columbus April Meetup — 2026-04-06 — Columbus
- Public talk page: https://columbus.aitinkerers.org/talks/rsvp_PguV58U8t70

### [Fly, Snap, Know: Wiring Drone Data into a Predictive, Prescriptive Security Platform That Responds Before You Do](https://johannesburg.aitinkerers.org/talks/rsvp_KeOgSIP594M)

DroneQRF is a drone operations platform built around one principle: the pilot's only job is to fly. Everything else is handled in the background. The Drone Pilots capture snapshots mid-flight; the platform does the rest — AI analysis of imagery, real-time parsing of flight telemetry and plans to predict potential issues and prescribe corrective actions, ingestion of deployment and fleet health monitoring, and a live dashboard giving full situational awareness across all active drones and sites. Nothing interrupts the mission. Intelligence surfaces automatically after combining these data points, before it becomes a problem.

- Event context: AI Tinkerers Johannesburg: Inaugural Meetup — 2026-03-31 — Johannesburg
- Public talk page: https://johannesburg.aitinkerers.org/talks/rsvp_KeOgSIP594M

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