# Node Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/node
> Markdown URL: https://aitinkerers.org/technologies/node.md
> Technology record last updated: 2026-02-23T02:30:10Z
> Generated: 2026-09-23T07:34:56Z

Node.js is a high-performance JavaScript runtime built on the V8 engine for executing scalable network applications.

Ryan Dahl launched Node.js in 2009 to rethink server-side concurrency. It utilizes an event-driven, non-blocking I/O model to manage thousands of concurrent connections on a single thread. The system runs on Google's V8 engine (C++) and provides access to npm (a registry with over 2 million packages). Companies like Netflix and LinkedIn use it for its speed and scalability: it remains the top choice for real-time data streaming and microservices.

- Official technology site: https://nodejs.org
- Public AI Tinkerers demos and talks: 99
- Result page: 1 of 5

## Recent Public Talks and Demos

### [Sandbox Only When the Agent Actually Needs It](https://barcelona.aitinkerers.org/talks/rsvp_xawovJcxMTM)

A production agent runtime that stays lightweight for normal requests, then automatically provisions a Daytona sandbox when a tool needs filesystem, code or shell access. In the live demo, the same agent handles one request without isolation and a second complex task by creating the sandbox, transferring the required files, running the isolated tools, returning the output and releasing the environment.

- Event context: AI Tinkerers Barcelona - September Demo Night — 2026-09-17 — Barcelona
- Public talk page: https://barcelona.aitinkerers.org/talks/rsvp_xawovJcxMTM

### [I Let an AI Avatar Introduce Me On Stage.](https://tokyo.aitinkerers.org/talks/rsvp_EAeb_RAMdGM)

I built a browser-based stage controller that made a 3D AI avatar walk on and deliver the opening introduction at the Perxona Tokyo Hackathon on August 8 — instead of introducing myself, I let the avatar do it. It performs a two-minute bilingual monologue with eighteen hand-placed gestures and no repeats, then swaps its face, voice and room live on keyboard cues, and finally lip-syncs to a voice clip my own laptop synthesised offline with no cloud call. It is a single Express server and one vanilla-JS page — no build step, no framework. Live I'll show: the working system, driven by number keys the way it ran on the day. Then the cue script — the gesture tokens and how they resolve at runtime against whichever character is on stage.

- Event context: AI Tinkerers Tokyo - September 1st Meetup — 2026-09-01 — Tokyo
- Public talk page: https://tokyo.aitinkerers.org/talks/rsvp_EAeb_RAMdGM

### [From VPS to Discord: Self-Hosting an Agentic AI That Never Forgets](https://tiruchirappalli.aitinkerers.org/talks/rsvp_3BC_PPnf7m4)

I self-hosted OpenClaw — an open-source, persistent AI agent gateway — on a VPS and connected it to Discord, turning it into an always-on assistant that holds context across sessions instead of resetting every conversation. In the demo, I'll show the live system end to end: the VPS deployment and gateway configuration (systemd service, token-based auth, loopback binding secured via SSH tunnel), the onboarding flow that wires up the model provider and Discord channel, and a real conversation with the bot on Discord where it responds, remembers earlier context, and can trigger commands — followed by a quick look at the gateway logs and config files to show what's actually happening under the hood.

- Event context: AI Tinkerers Tiruchirappalli: Agentic AI Builders Meetup — 2026-08-29 — Tiruchirappalli
- Public talk page: https://tiruchirappalli.aitinkerers.org/talks/rsvp_3BC_PPnf7m4

### [PalliAssist: Transforming Palliative Care with Compassionate AI](https://mombasa.aitinkerers.org/talks/rsvp_lhA4geGRg08)

PalliAssist is an AI-powered palliative care companion that helps patients, caregivers, and healthcare providers manage symptoms, medications, appointments, and access trusted care guidance through compassionate, personalized support. During this demo, we'll showcase the working web application, walk through the complete patient and caregiver workflow, demonstrate how Gemma powers real-time AI conversations, explain our system architecture and RAG pipeline, highlight key sections of our codebase on GitHub, and show how the platform delivers intelligent, accessible, and privacy-conscious palliative care in low-resource settings.

- Event context: AI Tinkerers – Mombasa Chapter Launch · 22 August 2026 — 2026-08-22 — Mombasa
- Public talk page: https://mombasa.aitinkerers.org/talks/rsvp_lhA4geGRg08

### [Don’t Just Build an App: Build a Playground - Designing flexible, high-growth ecosystems that scale seamlessly.](https://orange-county.aitinkerers.org/talks/rsvp_FR1uOvCMPCI)

Oddjob lets you spin up teams of AI agents that plan and execute multi-step work as missions, cycles, and pipelines — extracting knowledge, running research, generating documents and datasets, and completing tasks end to end. It can build and deploy working software and mini-apps on demand through App Forge, stand up org and team structures through Org Forge, and turn a document template into a live form agent that captures a structured schema automatically. It grounds every agent in your own data with retrieval-augmented generation, a knowledge graph, and reusable templates, and routes work through configurable LLM providers with automatic failover to a local model when a provider is unavailable.

- Event context: AI Tinkerers Orange County: Tuesday, July 21, 2026 at Centercode — 2026-07-22 — Orange County
- Public talk page: https://orange-county.aitinkerers.org/talks/rsvp_FR1uOvCMPCI

### [PinMe: Teaching AI Agents to Deploy Frontends in One Command](https://orange-county.aitinkerers.org/talks/rsvp_lTngvw_LXU8)

PinMe is a deployment CLI that lets developers and AI coding agents deploy websites with a single command. In this demo, I'll show how PinMe turns a local project into a live website, how AI agents use it, and how we built a deployment workflow that works reliably without configuration. I'll walk through the CLI architecture, agent workflow, deployment pipeline, and a live deployment in 5 minutes.

- Event context: AI Tinkerers Orange County: Tuesday, July 21, 2026 at Centercode — 2026-07-22 — Orange County
- Public talk page: https://orange-county.aitinkerers.org/talks/rsvp_lTngvw_LXU8

### [Being a dungeon master for agents](https://columbus.aitinkerers.org/talks/rsvp_bciO_4-2f2c)

I built a system where you can DM a contiguous story for agents, describing their light attributes and DM for them entirely via voice. Built with Svelte and node/express

- Event context: AI Tinkerers - Columbus July Meetup — 2026-07-06 — Columbus
- Public talk page: https://columbus.aitinkerers.org/talks/rsvp_bciO_4-2f2c

### [From AI Prospect Memos to a Scored Warm-Intro Queue](https://poland.aitinkerers.org/talks/rsvp_k0DCDscxWlA)

I built a dogfood workflow on top of graph.one that connects AI-assisted company qualification to a relationship-graph work queue. I'm the founder of graph.one, but this demo is about the internals of the build, not a product pitch. It starts in Prospector: a Node CLI pipeline that creates frozen public-source packets, runs AI-generated prospect memos, validates structured outputs, and stores decisions in append-only JSONL ledgers. The handoff is a qualified-company record. Intro Queue then takes a relationship-graph org-path export with organization identity, relationship owner, optional connector, target person/role, and strength fields. It caches the export in SQLite, collapses duplicate and noisy paths into scored route options, groups selected routes by connector, tracks per-company outcomes, and surfaces fallback routes as a human action queue. In the demo I'll follow one fully synthetic target company from source packet to memo to graph path row to scored route option to failed route/fallback. The queue output is a person-centric ask docket for a human operator; there is no send pipeline. I'll use fully synthetic graph data and redacted schema/log excerpts only.

- Event context: AI Tinkerers Warsaw: GTM Engineering Track — 2026-06-24 — Poland
- Public talk page: https://poland.aitinkerers.org/talks/rsvp_k0DCDscxWlA

### [Automatiser vos déploiements Scalingo avec MuleRun : Un guide étape par étape](https://paris.aitinkerers.org/talks/rsvp_5OXy7e9VKVA)

Ce tutoriel démontre comment utiliser MuleRun, votre agent de développement propulsé par l'IA, pour automatiser entièrement la création, la configuration et le déploiement d'une application Node.js avec mise en cache Redis sur le PaaS Scalingo. Au lieu d'écrire manuellement du code, d'exécuter des commandes CLI et de déboguer les déploiements, vous apprendrez à orchestrer l'ensemble du flux de travail en utilisant de simples prompts en langage naturel dans MuleRun.

- Event context: Hackathon IA Agentique : (GDG + Alumni) x EPITA — 2026-06-17 — Paris
- Public talk page: https://paris.aitinkerers.org/talks/rsvp_5OXy7e9VKVA

### [How We Built AI Agents That Buy Media Across 10+ Ad Platforms](https://seattle.aitinkerers.org/talks/rsvp_6LZbpmkAStQ)

Synter is an agentic AI platform that autonomously manages paid media campaigns across Google, Meta, LinkedIn, TikTok, Reddit, X, and Microsoft Ads. I'll demo the live system: how agents create campaigns, adjust bids, allocate budgets, and generate ad creatives in real time — no human clicking required. We'll look at the agent execution loop, the MCP server that lets Claude and Cursor control ad accounts directly, and the cross-channel dashboard that unifies data from all platforms.

- Event context: GTM / Growth Track - Seattle — 2026-05-27 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_6LZbpmkAStQ

### [Pull-architecture agents: how I forced myself to do growth work](https://valencia.aitinkerers.org/talks/rsvp_-p7b50BEZW0)

A multi-agent system that manufactures pull for the growth work — writing, conference follow-up, CRM hygiene, responding to news — that I'd otherwise skip when product and ops eat my week. Seven agents across five repos, two APIs, and two websites (one fully autonomous), all driven from the only two surfaces I actually live in: my terminal and Mattermost. The demo walks a live pass through the rig: a LinkedIn contact lands in our self-hosted CRM, an article draft gets pushed to a website, a post-conference follow-up gets queued — every action is a curl command an agent emits, with circuit breakers I can tighten in the moment or across the long arc.

- Event context: AI Tinkerers Valencia May Meetup — 2026-05-26 — Valencia
- Public talk page: https://valencia.aitinkerers.org/talks/rsvp_-p7b50BEZW0

### [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

### [Generative AI for Fun and Little Profit](https://columbus.aitinkerers.org/talks/rsvp_1wLkd0piSTc)

Musebot - a Discord bot that integrates with ComfyUI and Ollama to act as a chatbot that can also generate images, music, and video on consumer hardware.

- Event context: AI Tinkerers - Columbus May Meetup — 2026-05-04 — Columbus
- Public talk page: https://columbus.aitinkerers.org/talks/rsvp_1wLkd0piSTc

### [Methodologies for the Optimization of Developers' Workflow with AI Agents](https://pereira.aitinkerers.org/talks/rsvp_9_pwCnocOjU)

This repository is an architectural and educational guide designed to enhance Artificial Intelligence agents through the implementation of Plugins, MCP servers, and Custom Skills, built upon an open‑source software that enables fast connections between MCP servers and OpenCode. The workflow for software development has changed significantly with the arrival of artificial intelligence. However, the advances have been very rapid and numerous, making it difficult to keep up. For quite some time, I have observed that new tools and approaches constantly emerge, and most people —myself included— struggle to keep pace. Many resort to vibe coding, obtaining only average results. In response to this phenomenon, I identified that there are different ways to improve the daily use of agents. That is why I created this repository, conceived from the perspective of a student for other students. The goal is to leverage the wide variety of agents with powerful free tiers and explore how to enhance them, whether free or paid, through different methodologies. The ultimate aim is to move beyond vibe coding and instead embrace a more solid practice: becoming an AI Engineer.

- Event context: AI Tinkerers Pereira: Innovando con IA desde el SENA — 2026-04-30 — Pereira
- Public talk page: https://pereira.aitinkerers.org/talks/rsvp_9_pwCnocOjU

### [Lixpi is a visual, node-based workflow engine for building AI image and video generation pipelines](https://toronto.aitinkerers.org/talks/rsvp_SxMp4PNqTxU)

Lixpi is a visual, node-based workflow engine for AI image and video pipelines an infinite canvas where spatial arrangement is the workflow. Instead of writing a workflow DSL or fighting a linear chat prompt, you drop documents, images, and AI chat threads onto the canvas and draw edges between them. The edge graph directly drives context extraction, dependency chains, and execution order for the underlying models. In the demo I'll show live character-consistent image generation via "artifact piping" (one generated image fanned out as edge-context into multiple downstream threads), mid-conversation model switching between OpenAI / Anthropic / Google, and progressive image streaming rendered into the node in real time.

- Event context: AI Tinkerers Toronto - April 2026 - hosted by Shopify — 2026-04-29 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_SxMp4PNqTxU

### [Hive Mind vs Solo Agent: A Live Race to See If Multi-Agent Coordination Actually Beats Working Alone](https://montreal.aitinkerers.org/talks/rsvp_ytH2ELCp8bo)

A live head-to-head race pitting a single Claude Code agent against a ruflo Hive Mind, a "Tactical Queen" coordinating 4 specialized workers (architect, coder, tester, reviewer), both solving the same Python coding challenge in real time. The challenge is to build a sliding window rate limiter from scratch, including implementation, tests, and 80%+ coverage. A custom real-time scoreboard dashboard (Node.js + SSE) watches both workspaces simultaneously, streaming logs and tracking progress as files appear, tests run, and coverage is measured. When both sides finish, an automated evaluation scores them on a 100-point rubric (implementation, test pass rate, coverage, edge cases, time). It's a controlled experiment to answer the question: does multi-agent swarm coordination actually produce better code faster than a single focused agent?

- Event context: AI Tinkerers Montreal - April Demo Night — 2026-04-22 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_ytH2ELCp8bo

### [New AI visibility tool made 99% with vibe coding](https://valencia.aitinkerers.org/talks/rsvp_UStdYlRZtOI)

I built Crecerank, a tool designed to boost your brand’s visibility across the AI landscape. Crecerank is a brand monitoring platform that helps you understand the "why" behind every AI recommendation. We analyze exactly why an AI (like ChatGPT) chooses your competitor over you and identify the specific variables driving that decision. By focusing on the Latin American market and using human-behavior simulations, we deliver real, transparent data. With 64% of people now using AI to guide their buying decisions, the cost of being invisible is too high.

- Event context: AI Tinkerers Valencia April Meetup — 2026-04-21 — Valencia
- Public talk page: https://valencia.aitinkerers.org/talks/rsvp_UStdYlRZtOI

### [Independent Agents to Hive Mind - agent/chatbot/human collaboration via hiveWiki.ai](https://upstate-ny.aitinkerers.org/talks/rsvp_l5dVgas09AQ)

Wiki-based agent collaboration tool accessed by chatbots and agents via MCP - and by humans via the wiki artifact. Other systems try to workflow agents like employees. I'll demonstrate Claude Chat, a human, and Cursor Agent collaborating as experts using a shared, human-usable context to design and deploy a feature.

- Event context: AI Tinkerers Upstate NY: Agents and Automation — 2026-04-14 — Upstate NY
- Public talk page: https://upstate-ny.aitinkerers.org/talks/rsvp_l5dVgas09AQ

### [Building an end-to-end agentic coding workflow in sandbox](https://seattle.aitinkerers.org/talks/rsvp_A0CI_bsvMlY)

I’ll do a live technical walkthrough of an AI-assisted developer workflow that turns a task into code changes, tests, and a PR-ready diff. I’ll show the actual implementation: task orchestration, sandboxed execution, tool-calling, retry/failure handling, and human-in-the-loop checkpoints. This is a code-only demo (no slides), including what broke, what was hacked together, and what made the workflow reliable enough for daily use.

- Event context: AI Dev Tool Track — Seattle Meetup - April 13th, 2026 — 2026-04-14 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_A0CI_bsvMlY

### [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

### [Lazy Marketing v3: From Meeting to Content Pipeline in Zero Click](https://seattle.aitinkerers.org/talks/rsvp_TtXOReDjy68)

Most of us have 10+ meetings a week full of insights worth sharing — but turning those into content never happens. Marketing Machine fixes that by wiring together Claude, Gemini, Slack, Google Sheets, and the LinkedIn API into a fully automated content pipeline. A Read.ai transcript hits a webhook. Claude extracts the best marketing hooks and expands them into on-brand LinkedIn posts using a 100+ line brand-voice prompt. You pick and refine posts entirely inside Slack with buttons and modals — no separate app needed. Gemini generates an accompanying image. Approved posts queue up in Google Sheets and auto-publish to LinkedIn on a schedule. In this demo, I'll walk through the full loop live — from raw meeting transcript to a published LinkedIn post — and dig into the prompt engineering, multi-model orchestration, and Slack-as-a-UI patterns that make it work. Built with Node.js, Express, and APIs anyone can sign up for. No GPUs, no fine-tuning, no ML infra required.

- Event context: AI Tinkerers Seattle: GTM Track — March — 2026-03-26 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_TtXOReDjy68

### [\[UofT\] AI-Powered Self-Assessment: Transforming How Students Understand What They Know](https://toronto.aitinkerers.org/talks/rsvp_KTr4NgGJt9c)

Our presentation will introduce a web-based platform designed to help students improve their learning through structured self-assessment. The system is based on Cognitive Structure Analysis (CSA), a method that focuses on identifying the concepts a student understands rather than simply checking whether they can produce the correct answer on a test. Research conducted by MyEdMaster across multiple countries and subject areas shows that students who use CSA can improve their academic performance by an average of 1.5 to 2.5 letter grades. We will demonstrate how our platform allows students to access CSA self-assessment templates, evaluate their understanding of key concepts, and identify gaps in their knowledge. Once these gaps are identified, students can focus their studying on the areas where they need the most improvement. The website also supports classroom use by allowing teachers to register classes and receive aggregated reports that highlight student learning needs, helping guide instruction. Additionally, we will discuss how AI-powered tools integrated into the platform can assist students by simplifying self-assessment, generating study prompts, and improving accessibility. Overall, the project aims to provide a scalable, user-friendly tool that empowers students to better understand their own learning and study more effectively.

- Event context: AI Tinkerers Toronto - March - hosted by Mozilla! — 2026-03-25 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_KTr4NgGJt9c

### [What If Humans and Agents Had a Portable Cryptographically-Chained Ledger (Single source of truth)](https://nyc.aitinkerers.org/talks/rsvp_nTFADbAUdbI)

I built an MCP server that captures relevant context (Incidents, Decisions, Product Governance, etc.) into a cryptographically chained ledger — think blockchain-style hashing applied to a product development context window. I'll walk through the actual implementation: how the MCP hooks into Claude Code and Cursor, how context gets hashed and chained across sessions, how a voice agent or slack bot reads against the ledger to route decisions to the right person. The goal is that the MCP is always running in the background, capturing the most important context across meetings, tools, etc.; so building with teams and agents can match the speed of using the tools themselves.

- Event context: March Demo Day, hosted by Flowglad — 2026-03-18 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_nTFADbAUdbI

### [Budget by Chatting: Building a multi-channel AI-powered expense tracker](https://upstate-ny.aitinkerers.org/talks/rsvp_tB4HZsZid7I)

SetForMoney is a household budgeting web app. Users text "groceries 45 Sams Club" to Telegram, WhatsApp, SMS, or a web chat and an LLM model parses the amount, matches the category, and detects intent from raw natural language. Three things worth looking at under the hood: 1. The prompt architecture that handles expenses, questions, commands, and gibberish from a single parsing call, with fuzzy category matching that recovers from typos. 2. Channel-aware response formatting: same AI brain, different output constraints (SMS under 300 chars vs. rich web formatting). 3. Silent feature request detection: the chat assistant answers users normally while flagging unmet feature requests behind the scenes, then a nightly job clusters them into a demand-ranked product roadmap. Live production demo.

- Event context: AI Tinkerers Upstate NY: March Meetup — 2026-03-10 — Upstate NY
- Public talk page: https://upstate-ny.aitinkerers.org/talks/rsvp_tB4HZsZid7I

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## More Results

- Next: https://aitinkerers.org/technologies/node.md?page=2