# Vercel Projects at AI Tinkerers > Canonical HTML: https://aitinkerers.org/technologies/vercel > Markdown URL: https://aitinkerers.org/technologies/vercel.md > Technology record last updated: 2026-09-18T15:13:57Z > Generated: 2026-09-21T03:41:11Z Vercel is the Frontend Cloud: a unified platform for building, deploying, and scaling modern web applications, including Next.js, with performance-focused global infrastructure. Vercel delivers a frictionless developer experience for the modern web, focusing on the 'Develop, Preview, Ship' workflow. As the creator and maintainer of the Next.js framework, Vercel offers first-class support for full-stack React applications, alongside other popular frameworks like SvelteKit and Nuxt. Its core value is instant, Git-based deployment (e.g., automatic preview environments for every pull request) and automatic scaling via serverless functions (Edge Functions) and a global Content Delivery Network (CDN). This infrastructure ensures high performance, low latency, and zero-configuration scaling for applications used by companies like Apple and IBM. - Official technology site: https://vercel.com - Public AI Tinkerers demos and talks: 48 - Result page: 1 of 2 ## Recent Public Talks and Demos ### [AI for Feels, Not Just Tasks](https://la.aitinkerers.org/talks/rsvp_d3x3AU8Ehzk) Glad to present how I'm going about building this emotional gps for AI - basically a tool that helps you get emotional clarity in 5 minutes. It's not therapy - it's in between group chat and therapy. Users type in what's hard to say. The app using AI shows images for visual projection to surface emotional patterns, and then it reflects back what could really be going on, what you actually want and what you're prepared to do about it. Happy to present a demo of the working product, then go into the file architecture, my workflow and unit economics for API calls. - Event context: Aug 16 - AI Tinkerers LA: Beauty, Bytes, and Venice Beach Vibes 🌊✨🤖 — Los Angeles - Public talk page: https://la.aitinkerers.org/talks/rsvp_d3x3AU8Ehzk ### [SEO Delphi / AI SEO Agents](https://seattle.aitinkerers.org/talks/rsvp_SABLX9RPvCQ) SEO Delphi: an autonomous SEO and growth engine for advisor.guide, a financial advisor directory built on public SEC Form ADV data (300k+ advisor profiles). It's a fleet of ~20 Vercel cron jobs plus Claude agents, split into layers: (1) data sync pulls SEC/Form ADV, 13F, and AUM data into Postgres; (2) sensing reads Search Console daily, scrapes Google ranks vs competitors (Wealthtender, SmartAsset, WiserAdvisor) via Serper, and mines AI-citation gaps where ChatGPT/Perplexity cite competitors but not us; (3) deciding ranks "what to write today" from Reddit/news/SpyFu signals, finds the single biggest funnel leak, and logs every shipped change to an experiments ledger so a later cron measures it; (4) acting sends claim-outreach email to unclaimed advisors getting profile views, and drives agent-written content through a scored writing rubric; (5) reporting posts everything to Slack as the "seo-delphi" bot, with a morning pulse split into "humans need to do" vs "what the agents did." I'll show live: the cron code, the Slack feed, real Search Console and rank data, and the experiments ledger. - Event context: GTMxAI Engineering July - Seattle Tech Week — 2026-07-30 — Seattle - Public talk page: https://seattle.aitinkerers.org/talks/rsvp_SABLX9RPvCQ ### [Researching agent memory](https://columbus.aitinkerers.org/talks/rsvp_9_U1zLJVobc) What started as a conversation to understand agent memory frameworks turned into a directory website and a fully autonomous self learning researcher and reporter. - Event context: AI Tinkerers - Columbus July Meetup — 2026-07-06 — Columbus - Public talk page: https://columbus.aitinkerers.org/talks/rsvp_9_U1zLJVobc ### [From Dashboards to GTM Action Loops](https://boston.aitinkerers.org/talks/rsvp_k0m7uHbc2O8) We built a GTM insight reporting agent on Squadbase for RevOps, CS, and Marketing teams. It monitors dashboards, finds meaningful changes, investigates the cause, and turns the result into a short report with recommended next actions. The report is not the end of the workflow. A team member can open it, review the dashboard, check the agent trace, and keep digging into the source data with the same context. In the demo, I will show a dashboard change, the agent’s SQL/TypeScript investigation, the cause analysis, and the final report that helps a GTM team decide what to do next. - Event context: AI Tinkerers Boston: GTM Agentic AI Launch — 2026-06-29 — Boston - Public talk page: https://boston.aitinkerers.org/talks/rsvp_k0m7uHbc2O8 ### [Autodrain content marketing](https://poland.aitinkerers.org/talks/rsvp_js_ge_CRaCs) https://drain.fabryka.ai ( backend for the codesota.com content marketing ) from 0 to 30k users without marketing spend - Event context: AI Tinkerers Warsaw: GTM Engineering Track — 2026-06-24 — Poland - Public talk page: https://poland.aitinkerers.org/talks/rsvp_js_ge_CRaCs ### [Revolutionalizing audiobooks with AI](https://dubai.aitinkerers.org/talks/rsvp_WNyvbI0-h8Q) 75000+ Audiobooks narrated to you through the power of AI. Will start with completely explaining the product along with a working demo of the app. A user chosen book (from the 75000+) book catalogue being narrated live with AI. - Event context: AI Tinkerers Dubai - May Demo Day — 2026-05-23 — Dubai - Public talk page: https://dubai.aitinkerers.org/talks/rsvp_WNyvbI0-h8Q ### [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 ### [TriCoach](https://boston.aitinkerers.org/talks/rsvp_HM-11Iww8A0) I built an app to help me train for my triathlon. It provides a daily dashboard with everything I need to do, along with an AI coach that adapts to my progress, needs, and effort levels. - Event context: AI Tinkerers Boston: March 2026 Meetup — 2026-03-30 — Boston - Public talk page: https://boston.aitinkerers.org/talks/rsvp_HM-11Iww8A0 ### [Vibe Closing - Building a Virtual CRO](https://seattle.aitinkerers.org/talks/rsvp_sLyy5fqVjLw) A virtual CRO. We used agents to do deep research across a company’s financials, CRM, and product data to identify which GTM experiments to run. - Event context: AI Tinkerers Seattle: GTM Track — March — 2026-03-26 — Seattle - Public talk page: https://seattle.aitinkerers.org/talks/rsvp_sLyy5fqVjLw ### [Solving Cold Start GTM with Claude Code (and Zero Headcount)](https://seattle.aitinkerers.org/talks/rsvp_saEaMuqlges) Loupe is a luxury watch market intelligence and tool platform designed for collectors and dealers. With a one-person team and Claude Code, we ship SEO landing pages, Instagram content (carousels, reels, stories), editorial guides, across 22+ watch brands, all from CC. In this demo, I'll walk through the actual workflows: how a single CLI session can research a topic, query Supabase for watch data, generate templated visuals with Puppeteer, compose ffmpeg reels with Ken Burns and transition effects, and push a finished landing page and associated Instagram reel to production. Leveraging Claude Code with custom slash commands, custom MCP integrations, and a growing skills library that turns repetitive GTM work into repeatable pipelines. I'll show the real session transcripts, the messy iterations, and the parts that broke. Leveraging this method, we've grown from 0 to 100 followers in a week. - Event context: AI Tinkerers Seattle: GTM Track — March — 2026-03-26 — Seattle - Public talk page: https://seattle.aitinkerers.org/talks/rsvp_saEaMuqlges ### [Spatial Intelligence for Sustainable Design](https://denver-boulder.aitinkerers.org/talks/rsvp_DtvytQ2NOCs) I built a water wise planning tool that water companies can offer to their customers to guide them through creating an accurate landscape plan and plant list and be connected to local installers and rebate opportunities - Event context: AI Tinkerers Denver Meetup - March 25, 2026 — 2026-03-25 — Denver - Public talk page: https://denver-boulder.aitinkerers.org/talks/rsvp_DtvytQ2NOCs ### [ModelWar: Core War for Agents](https://nyc.aitinkerers.org/talks/rsvp_wHEPK9Prm0k) Core War is a programming game first developed in 1984 where two programs written in an assembler-like language called redcode battle in a virtual computer core. Point your agent (claw-like, custom, Claude Code, Codex, whatever) at modelwar.ai and have it reach the top of the leaderboard! No Core War experience needed (but you’ll probably learn something!) - Event context: March Demo Day, hosted by Flowglad — 2026-03-18 — New York City - Public talk page: https://nyc.aitinkerers.org/talks/rsvp_wHEPK9Prm0k ### [From Idea to Deployed App in 15 Minutes — The PM-as-Director Workflow for Non-Coders](https://chicago.aitinkerers.org/talks/rsvp_L5Pnf9N6o1k) A fully functional web app starting from nothing but a product idea. I'll walk through the complete pipeline I teach creative professionals who've never written code: generating a production-grade PRD with Claude → prototyping in Google AI Studio → scaffolding and building in Firebase Studio/Lovable → running automated security checks with Vibe Audit (my open-source CLI with 39 security rules across 8 attack surfaces) → pushing to GitHub → deploying to Vercel. Every step is live code and terminal — no slides. The key insight: the PRD is the code direction. AI builds, you think. - Event context: AI Tinkerers Chicago: March Meetup ft. Programmers Inc. — 2026-03-17 — Chicago - Public talk page: https://chicago.aitinkerers.org/talks/rsvp_L5Pnf9N6o1k ### [Building Autonomous Websites](https://berlin.aitinkerers.org/talks/rsvp_kbMMJBcTVKU) An AI agent that designs, builds, and ranks entire websites autonomously. It creates pages from scratch, writes SEO-optimized content daily, tracks rankings across multiple countries, monitors competitors, and optimizes for both Google and AI search engines (GEO) — all running 24/7 from a single machine. No agency. No team of freelancers. One agent does the work of a developer, content writer, and SEO specialist combined. Depending on the time allocated, I will show how this bot can build an entire website from scratch, OR I will only show how it edits an existing website in real-time. - Event context: AI Tinkerers Berlin Meetup - March 11, 2026 — 2026-03-11 — Berlin - Public talk page: https://berlin.aitinkerers.org/talks/rsvp_kbMMJBcTVKU ### [Real-Time Web Scraping with AI Agents: No Puppeteer, No XPath, Just a Goal](https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_APx09m92Cf8) Traditional scraping breaks every time a site updates its HTML. I'll show a different approach: give an AI agent a URL and a plain-English goal, and it figures out the page on its own. Live on stage: a hotel search app that sends Booking.com and Agoda URLs to Tinyfish agents. Each agent autonomously navigates the real site, handles dynamic content, and returns structured JSON — no CSS selectors, no brittle DOM parsing. II'll also show the Tinyfish run dashboard live so you can watch the agent clicking through pages in real time. - Event context: AI Tinkerers Ho Chi Minh City: From Prompt to Agent — 2026-03-07 — Ho Chi Minh City - Public talk page: https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_APx09m92Cf8 ### [Get Shit Done: De idea a SaaS en producciĂłn en 7 dĂ­as con Claude Code](https://bogota.aitinkerers.org/talks/rsvp_Ibf98jRs5c4) Voy a mostrar cĂłmo construĂ­ KeepItX — una plataforma SaaS para captura colaborativa de fotos en eventos — en exactamente una semana usando el framework "Get Shit Done" y Claude Code como mi copiloto de desarrollo. Voy a hacer un walkthrough del cĂłdigo real: la arquitectura Next.js + Supabase, cĂłmo estructurĂ© los prompts y sesiones con Claude Code para maximizar velocidad, las decisiones tĂ©cnicas que tomĂ© (y las que deleguĂ© al AI), y el flujo completo desde el primer commit hasta tener usuarios reales pagando $99 por evento. Sin slides, puro cĂłdigo y terminal. - Event context: AI Tinkerers Bogotá: El Primer Meetup de 2026 — 2026-02-26 — Bogotá - Public talk page: https://bogota.aitinkerers.org/talks/rsvp_Ibf98jRs5c4 ### [Building Knobase: Personalized AI Tutoring with mem0 Memory, ZeroEntropy RAG, and Real-Time Content Safety](https://hong-kong.aitinkerers.org/talks/rsvp_cSLy04LtLvE) Context: Knobase powers personalized AI tutoring for 1,000+ students across various schools in Asia. The core insight we learned: teachers need AI agents they can configure and trust without writing code, and students need personalization that remembers their learning style across sessions — not just generic ChatGPT wrappers that hallucinate or give direct answers when Socratic questioning is more effective. This talk is a technical deep-dive into how we orchestrate multiple AI systems to deliver that experience at scale, walking through five implementation layers: 1. Personalization with mem0 — A hybrid memory architecture combining mem0’s semantic vector search with a local confirmed-memories table in Supabase. As students chat, we extract preferences, learning styles, goals, and challenges via regex pattern matching and prompt scoring (confidence threshold ≥ 0.85). Students confirm these memories (“Yes, I’m preparing for IB exams”), and they’re injected into every subsequent chat. A 10th-grader studying physics gets reminders about their preference for step-by-step explanations; a university student preparing for finals gets context about their exam timeline. I’ll walk through  getContextualMemoriesForPrompt()  and how we merge local + mem0 results to build a per-student profile that persists across days and subjects. 2. RAG with ZeroEntropy — Teachers upload textbooks, lecture slides, problem sets, and institutional syllabi. Document ingestion pipeline: file upload → Supabase Storage → base64 encoding → ZeroEntropy with semantic chunking (chunk_size: 1800, overlap: 200). Collections are scoped per school ( school_{id} ) so students only retrieve content their teachers authorized. Retrieval uses topSnippets queries with metadata filtering by document/knowledge IDs, plus a parallel RAG agent that expands queries and aggregates deduplicated results. This means when a Harrow student asks “What’s Newton’s second law?”, the AI cites their specific uploaded physics textbook, not generic web content. I’ll show the filter-building logic and how we resolve documents through bot → knowledge → collective → document chains. 3. Real-Time Context API — Teachers can connect external data sources (Google Sheets of upcoming assignments, Notion databases of class resources, live sports scores for a journalism class analyzing data) via webhook-based context providers. On every message, we call registered providers, AI-process the response with token optimization (60-90% reduction), and inject it alongside RAG results. Example: A history teacher at ISF Academy configured a timeline of World War II events that updates the AI’s context window in real time, so students always get era-appropriate answers. I’ll trace the full flow from  chat.context_config  → provider webhook → context processing → system prompt assembly. 4. No-Code AI Chat Builder for Teachers — Educators configure role, tone, age group (elementary/middle/high school/university), complexity, subject, language, Socratic mode toggle (forces the AI to ask guiding questions instead of giving direct answers), citation preferences, and custom instructions — all stored as  custom_details  JSON. Organization-level master prompts override per-bot settings for school-wide safety policies. I’ll show how the system prompt is assembled in 10 steps: master prompt → bot intro → RAG context → memory context → custom instructions. A teacher creating a “Socratic Math Tutor” for 8th graders clicks 6 dropdowns and writes 2 sentences of instruction; the system generates a 2,000-token prompt behind the scenes that enforces age-appropriate language, refuses to solve homework directly, and cites only the uploaded textbook. 5. Education Safety Stack — Real-time prompt scoring (Clarity/Specificity/Task Definition/Context/Structure on a 0-100 scale) via a Supabase Edge Function runs on every student input. Content flagging across 7 categories (sexual content, bullying, profanity, racial bias, political sensitivity, harmful advice, PII detection) plus custom organization-defined flags (e.g., Harrow added “exam cheating detection”). A daily digest cron emails flagged messages to designated safety managers. Student interest keywords and learning purpose analysis are extracted as a side effect of scoring and fed back into mem0, creating a feedback loop where the AI becomes more personalized the more the student uses it. We’ve processed 16,000+ messages since December 2025 with this stack in production. ** Code walkthrough will focus on the chat route orchestration (~3,700 lines) that ties all five layers together in a single request lifecycle. No slides — just live code, architecture diagrams on a whiteboard, and real examples from our production deployment. - Event context: AI Tinkerers Hong Kong & GBA: Using AI as a Superconductor for Learning — 2026-02-26 — Hong Kong - Public talk page: https://hong-kong.aitinkerers.org/talks/rsvp_cSLy04LtLvE ### [Design-by-Transparency: Fixing Authority Before Execution](https://tokyo.aitinkerers.org/talks/rsvp_LoFqvnKwFjs) Design-by-Transparency treats governance as a design-time concern, not a post-hoc explanation. This demo shows a small, working example of how intent, authority, and stop conditions can be explicitly fixed before execution, so AI systems cannot act beyond what was deliberately allowed. Rather than focusing on model performance or prompts, the demo highlights how execution boundaries are designed, enforced, and audited upstream — before agentic behavior reaches real-world systems. The goal is to make AI behavior predictable by design, not explainable after failure. - Event context: AI Tinkerers Tokyo - Toranomon Meetup - February 19, 2026 — 2026-02-19 — Tokyo - Public talk page: https://tokyo.aitinkerers.org/talks/rsvp_LoFqvnKwFjs ### [Hoist the Flag and Win Demos](https://belgrade.aitinkerers.org/talks/rsvp_tc3tizG5lRg) See how using feature flags can help you quickly customize your product experience and bring instant customization to your sales pitch. - Event context: AI Tinkerers Belgrade Opening Meetup with PostHog — November 27, 2025 — 2025-11-27 — Belgrade - Public talk page: https://belgrade.aitinkerers.org/talks/rsvp_tc3tizG5lRg ### [AI curated whatsapp memories](https://cologne.aitinkerers.org/talks/rsvp_dB69j5KZsew) A whatsapp clone with only the best messages between you and a loved one. A python script uses an LLM (Gemini 2.5 Flash) to sort through the messages until only the best ones are left. You can then reread the best messages in the UI and have enjoy a bit of nostalgia :-) The talk will consist of a presentation of the functionality first before diving into the code and the decisions that I made during development. Technical Details: The python script does the following: 1. Read the exported Whatsapp chat history. 2. Split the chat history into chunks, one per day. 3. For each chunk, extract the messages and the metadata (date, time, sender). 4. Send each chunk to the LLM to filter out the messages that are memorable according to a prompt. Extraction is done with structured output. 5. Save memories to a database. The web app constisting of fastapi and nextjs reads the database and shows the messages it in the UI. The web app has basic CRUD capabilities to further curate the messages. Challenges: It was challenging to find an LLM with the right balance of intelligence, speed and cost. After some experimentation I settled on Gemini 2.5 Flash because of it's exceptional value for money. It's reasoning is powerful enough to extract meaningful messages while being cheap and fast even when processing an extensive message history. Another challenge during development was to teach the model exactly what constitutes a memorable message vs. a merely cute one. I've used prompt engineering with few shot examples to increase the quality. I tested the quality by vibe checking only. In a more serious project I would have created a data set and used automated evaluation to test the quality reliably. - Event context: AI Tinkerers Cologne – Inaugural Meetup — 2025-11-05 — Cologne - Public talk page: https://cologne.aitinkerers.org/talks/rsvp_dB69j5KZsew ### [IA mĂ©dica multimodal: análisis de imágenes medicas y conversaciĂłn clĂ­nica](https://pereira.aitinkerers.org/talks/rsvp_l47r_0l5jY4) El Medical Imaging Diagnosis Agent es una aplicaciĂłn web diseñada para asistir en el análisis preliminar de imágenes mĂ©dicas utilizando inteligencia artificial a travĂ©s de la API de Google Gemini. Esta herramienta permite a profesionales de la salud y estudiantes de medicina obtener un análisis inicial de imágenes mĂ©dicas y mantener conversaciones contextuales sobre los hallazgos. La aplicaciĂłn combina capacidades de análisis de imágenes con un sistema de chat inteligente que mantiene el contexto de análisis previos, proporcionando una experiencia integrada para la interpretaciĂłn asistida de imágenes mĂ©dicas. - Event context: 🔥 AI TINKERERS - PEREIRA🤖 De tareas a sistemas inteligentes: la revoluciĂłn de la automatizaciĂłn 🔥🤖 — 2025-10-30 — Pereira - Public talk page: https://pereira.aitinkerers.org/talks/rsvp_l47r_0l5jY4 ### [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 ### [Vibe Security with Aikido Zen](https://nyc.aitinkerers.org/talks/rsvp_cyqsrUkrJL8) I'll be securing a vibe coded app full of vulnerabilities with a runtime application firewall. - Event context: NYC October Demo Day — 2025-10-02 — New York City - Public talk page: https://nyc.aitinkerers.org/talks/rsvp_cyqsrUkrJL8 ### [Building a “Performance Marketer in a Box” with LangGraph and Vercel](https://nyc.aitinkerers.org/talks/rsvp_mO2HPaI9P-Y) I’ll walk through how I hacked together the latest version of Camcorder AI, a “performance marketer in a box.” You’ll see how I wired up a LangGraph agent in TypeScript to handle complex marketing workflows and deployed it with Vercel AI SDK 5. I’ll plan to show the guts: the agent graphs, state management, prompt chaining, and how the runtime ties everything together. - Event context: NYC October Demo Day — 2025-10-02 — New York City - Public talk page: https://nyc.aitinkerers.org/talks/rsvp_mO2HPaI9P-Y ## Related Technologies - [Next](https://aitinkerers.org/technologies/next) ([Markdown](https://aitinkerers.org/technologies/next.md)) — 186 public demos - [Supabase](https://aitinkerers.org/technologies/supabase) ([Markdown](https://aitinkerers.org/technologies/supabase.md)) — 90 public demos - [TypeScript](https://aitinkerers.org/technologies/typescript) ([Markdown](https://aitinkerers.org/technologies/typescript.md)) — 205 public demos - [Claude Code](https://aitinkerers.org/technologies/claude-code) ([Markdown](https://aitinkerers.org/technologies/claude-code.md)) — 214 public demos - [OpenAI](https://aitinkerers.org/technologies/openai) ([Markdown](https://aitinkerers.org/technologies/openai.md)) — 112 public demos - [Python](https://aitinkerers.org/technologies/python) ([Markdown](https://aitinkerers.org/technologies/python.md)) — 662 public demos - [React](https://aitinkerers.org/technologies/react) ([Markdown](https://aitinkerers.org/technologies/react.md)) — 219 public demos - [Cursor](https://aitinkerers.org/technologies/cursor) ([Markdown](https://aitinkerers.org/technologies/cursor.md)) — 65 public demos - [Gemini](https://aitinkerers.org/technologies/gemini) ([Markdown](https://aitinkerers.org/technologies/gemini.md)) — 188 public demos - [Claude](https://aitinkerers.org/technologies/claude) ([Markdown](https://aitinkerers.org/technologies/claude.md)) — 173 public demos - [OpenAI API](https://aitinkerers.org/technologies/openai-api) ([Markdown](https://aitinkerers.org/technologies/openai-api.md)) — 520 public demos - [ChatGPT](https://aitinkerers.org/technologies/chatgpt) ([Markdown](https://aitinkerers.org/technologies/chatgpt.md)) — 83 public demos - [Clerk](https://aitinkerers.org/technologies/clerk) ([Markdown](https://aitinkerers.org/technologies/clerk.md)) — 4 public demos - [GitHub](https://aitinkerers.org/technologies/github) ([Markdown](https://aitinkerers.org/technologies/github.md)) — 74 public demos - [Cloudflare](https://aitinkerers.org/technologies/cloudflare) ([Markdown](https://aitinkerers.org/technologies/cloudflare.md)) — 17 public demos - [Firebase](https://aitinkerers.org/technologies/firebase) ([Markdown](https://aitinkerers.org/technologies/firebase.md)) — 23 public demos - [Langfuse](https://aitinkerers.org/technologies/langfuse) ([Markdown](https://aitinkerers.org/technologies/langfuse.md)) — 13 public demos - [LangGraph](https://aitinkerers.org/technologies/langgraph) ([Markdown](https://aitinkerers.org/technologies/langgraph.md)) — 67 public demos ## More Results - Next: https://aitinkerers.org/technologies/vercel.md?page=2