# LangGraph Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/langgraph
> Markdown URL: https://aitinkerers.org/technologies/langgraph.md
> Technology record last updated: 2026-09-18T15:13:55Z
> Generated: 2026-09-20T23:36:10Z

A low-level orchestration framework for building long-running, stateful, and cyclic multi-agent systems using a graph-based architecture.

LangGraph is the specialized, low-level runtime for developing complex AI agents, extending the LangChain ecosystem to handle intricate, stateful workflows. It models the agent's logic as a directed graph: nodes represent actions (LLM calls, tool use), and conditional edges dictate the flow, enabling critical features like cycles (loops) for iterative reasoning. This graph-based approach ensures durable execution, allowing agents to persist through failures and resume operations. Key capabilities include comprehensive memory management via a shared state object and built-in human-in-the-loop functionality (interrupts) for external oversight. This robust framework is trusted by production teams at companies like Klarna and Replit for deploying scalable, resilient agent architectures.

- Official technology site: https://langchain.com/docs/langgraph/
- Public AI Tinkerers demos and talks: 67
- Result page: 1 of 3

## Recent Public Talks and Demos

### [Wittgenlab, creando un framework para evaluar llms](https://bogota.aitinkerers.org/talks/rsvp_DQbVYpY7uWA)

Wittgenlab surgió de la busqueda de crear un framework que permitiera evaluar de forma efectiva los agentes y modelos desplegados, usando conocimiento de varios papers y la experiencia construí una solución que es la base para evaluar modelos y que cada dia crece más, además de open source

- Event context: AI Tinkerers Bogotá - Julio 24 — Bogotá
- Public talk page: https://bogota.aitinkerers.org/talks/rsvp_DQbVYpY7uWA

### [Implementing a multi-agent blog post writer using Microsoft Agent Framework](https://boston.aitinkerers.org/talks/rsvp_i1qCN9asMtA)

This application demonstrates concepts covered in over 30 blog posts on Microsoft Agent Framework and related technology. The app generates meaningful blog posts on virtually any topic. The Blogger agent coordinates, the Research agent goes out to the web to bring back relevant information, the Author agent writes a draft post and the Reviewer agent evaluates the post and approves or sends it back to the Author for improvement. I will demonstrate live code and cover a variety of related topics such as Logging, OpenTelemetry, Middleware, token usage limits, and long-term memory approaches in Microsoft Agent Framework

- Event context: Back from Summer: AI GTM Builders — 2026-09-03 — Boston
- Public talk page: https://boston.aitinkerers.org/talks/rsvp_i1qCN9asMtA

### [Teaching an Agent to Behave Like a Data Scientist: A Statistical Harness for Tabular ML](https://amsterdam.aitinkerers.org/talks/rsvp_dYE4vQbTMCM)

We built QAgent, an agent that plans and acts like a human data scientist. Coding harnesses such as Claude Code treat data science as a coding problem and miss the nuances: checking for bias, treating data leakage, and ultimately producing results that look correct but rest on flawed methodology. QAgent fixes that with a harness built for data science: the right interface to the data, and constraints that unlock principled data science capabilities in LLMs.

- Event context: AI Tinkerers Demo Night: Agents in Various Forms — 2026-09-03 — Amsterdam
- Public talk page: https://amsterdam.aitinkerers.org/talks/rsvp_dYE4vQbTMCM

### [Turning real business SOPs into rules an agent can actually follow](https://da-nang.aitinkerers.org/talks/rsvp__ey6nXp67PY)

We built a harness for AI agents that execute real-world business operations from human-written SOPs. The system separates execution into three planes: Policy turns natural-language operating procedures into goals, guidance, authority boundaries and guardrails; Execution plans and coordinates long-running work across AI, humans and tools while adapting to changing real-world state; and Quality evaluates execution against the governing standard and operational evidence. Live, I’ll show the working system from SOP interpretation through adaptive execution and run evaluation.

- Event context: AI Tinkerers Da Nang: Inaugural Meetup — 2026-08-15 — Da Nang
- Public talk page: https://da-nang.aitinkerers.org/talks/rsvp__ey6nXp67PY

### [Evaluating Multi-Agent Systems Beyond the Final Answer](https://seattle.aitinkerers.org/talks/rsvp_lgxuusz0aeg)

I am building an evaluation framework for multi-agent AI systems that compares not only whether the system gets the right final answer, but how the agents collaborate to get there. In the live demo, I will show a small multi-agent workflow with a planner agent, worker agents, and a critic/evaluator agent, then walk through the code, traces, tool calls, handoffs, failure cases, and scoring logic used to evaluate each run. The framework captures the full agent trajectory: which agent took control, what tools were called, where context was passed or lost, how much the run cost, how long it took, and whether the final outcome matched the task goal. I will demo how the same task behaves under different setups, such as a single-agent baseline, a manager-agent architecture, and a multi-agent handoff design.

- Event context: Women in AI - Builders Track: Seattle Inaugural Meetup — 2026-07-15 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_lgxuusz0aeg

### [Vibe-Coded Plug-Ins](https://columbus.aitinkerers.org/talks/rsvp_6qoJy3Zx-eM)

I’ll live-demo a prompt-generated dashboard plug-in system: a user asks for a custom dashboard tile, the backend generates a vue component plus a typed props schema, live props are resolved through an agent with tenant-scoped tools, and the browser renders the result inside a sandboxed iframe

- Event context: AI Tinkerers - Columbus June Meetup — 2026-06-01 — Columbus
- Public talk page: https://columbus.aitinkerers.org/talks/rsvp_6qoJy3Zx-eM

### [Stateful agents with open-strix](https://raleigh.aitinkerers.org/talks/rsvp_obcR2zOygIM)

open-strix is a minimalistic open source stateful agent harness that leans on the Unix principle and uses cybernetics principles to build a tiny, solid, extensible core.

- Event context: AI Tinkerers Raleigh Meetup — May 6, 2026 — 2026-05-06 — Raleigh
- Public talk page: https://raleigh.aitinkerers.org/talks/rsvp_obcR2zOygIM

### [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

### [ibaAgent: Agentic time-series analysis.](https://nurnberg.aitinkerers.org/talks/rsvp_DcXjk1ibxVU)

I developed an agentic system using LangGraph to analyze high-resolution time-series data via natural language. Since high-resolution data is too token-intensive for LLMs, the agent operates "blind" by dynamically writing and executing Python analysis scripts to process data locally. This is supported by a specialized memory architecture that allows the agent to iteratively build an internal map of undocumented, messy data stores, and a rigorous Langfuse experiment pipeline used to tune hyperparameters and prompts for predictable reasoning and precise tool use. Currently transitioning from proof-of-concept to product at iba AG, my demo will showcase LangGraph traces of the agent’s execution and its self-correction within the Python environment. I will also highlight our Langfuse evaluation workflow and how the memory layer enables the agent to navigate complex data structures over time. I’m looking to exchange ideas with fellow tinkerers specifically on memory persistence, planning strategies, and robust evaluation for agentic workflows.

- Event context: AI Tinkerers Nürnberg: April Meetup — 2026-04-22 — Nürnberg
- Public talk page: https://nurnberg.aitinkerers.org/talks/rsvp_DcXjk1ibxVU

### [Adapting Reality - Building an agent to modify point clouds](https://nurnberg.aitinkerers.org/talks/rsvp__N7lhlFUMEI)

I'm presenting an agent and natural-language interface that understands and modifies 3D point clouds. Users can ask it to complete various tasks - identifying objects, segmenting regions, even moving elements - and it executes them directly on the point cloud data. The core challenge is getting an LLM to reason meaningfully over spatial 3D structures, which requires careful prompt engineering, tooling, and a structured scene graph as the agent's "world model" rather than raw point data. Getting reliable behavior meant running systematic evals: testing the agent across varied phrasings, ambiguous spatial queries, and edge cases like occluded or overlapping objects - then iterating on the tool definitions and system prompt until performance was consistent. The builder takeaway: treat your data representation as a first-class design decision - the right abstraction layer between the LLM and your domain data is what makes or breaks agent reliability.

- Event context: AI Tinkerers Nürnberg: April Meetup — 2026-04-22 — Nürnberg
- Public talk page: https://nurnberg.aitinkerers.org/talks/rsvp__N7lhlFUMEI

### [Anita: A Proactive Synthetic Organism](https://cologne.aitinkerers.org/talks/rsvp_10X8PdiOc28)

Anita is a proof-of-concept architecture for building proactive AI agents that perceive and act on their own, instead of waiting for a prompt. Inspired by the Synths from the TV series "Humans" and by the OpenClaw project, the architecture is modeled after biological organisms: receptors perceive continuous streams of stimuli and react to them. The agent has "organs", "senses", a central "nervous system", and declarative "reactions". The key goal is extensibility, not just by the developer, but by Anita herself. In the demo, I'll fire stimuli into the running system and show how perceptions flow through reactions and produce actions.

- Event context: AI Tinkerers Cologne 4: Live Technical Demos — 2026-04-16 — Cologne
- Public talk page: https://cologne.aitinkerers.org/talks/rsvp_10X8PdiOc28

### [Stop the Confident BS: Reflective Retrieval Agents and Human-in-the-Loop Interrupts](https://cologne.aitinkerers.org/talks/rsvp_LyKSpKSeRVQ)

We built a reflective agent prototype that evaluates its own retrieved context and halts for human clarification before it hallucinates. In the live demo, we'll first break a standard one-prompt RAG setup to show how it confidently gives answers when faced with poorly defined context. Then, we will query our prototype, showcasing the live execution. You will see the agent evaluate its context, hit an uncertainty threshold, trigger a Human-in-the-Loop (HITL) interrupt to ask for missing parameters, and finally generate a factually grounded answer.

- Event context: AI Tinkerers Cologne 4: Live Technical Demos — 2026-04-16 — Cologne
- Public talk page: https://cologne.aitinkerers.org/talks/rsvp_LyKSpKSeRVQ

### [Sentinel - AI Document Intelligence for Regulated Teams](https://dc.aitinkerers.org/talks/rsvp_dme7MO875dE)

Sentinel is an AI document intelligence agent that helps regulated teams review complex documents faster by cross-referencing them against trusted evidence, surfacing risks and obligations, and producing outputs that are fully traceable and defensible.

- Event context: AI Tinkerers x Softengi - DC Metro Meetup - April 9th, 2026 — 2026-04-09 — DC
- Public talk page: https://dc.aitinkerers.org/talks/rsvp_dme7MO875dE

### [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

### [Niuwn AI: Building an AI Twin That Speaks As Me to Strangers](https://bremen.aitinkerers.org/talks/rsvp_BIo4d4pBN0I)

I built a system where anyone can create a conversational AI version of themselves, not a chatbot that answers questions about you, but one that talks as you in first person to anyone who visits a shareable link. Think of it as replacing your static CV or LinkedIn profile with something people can actually have a conversation with. The core idea is a two-agent architecture. One agent (the Curator) works with you privately; you talk to it, upload your CV, share your blog posts, import your LinkedIn export and GitHub profile. It interviews you like a thoughtful journalist, asks follow-ups, spots gaps, and organizes everything into a structured knowledge base. The second agent (the Twin) is what visitors see. It reads from that knowledge base, speaks in your voice, respects boundaries you've defined, and gracefully handles things it doesn't know instead of hallucinating. What makes the system interesting technically: the entire knowledge base is plain Markdown files, transparent, editable, and version-controllable. Retrieval uses memsearch for hybrid BM25 + vector search over those markdown files, which turns out to work really well for professional data where you need both semantic understanding and exact matching on names, dates, and technologies. The two agents have strict asymmetric access, the Curator writes, the Twin only reads, which keeps the trust boundary clean and makes prompt injection defense on the public-facing side much more manageable. The system is built with GDPR in mind, owners can view, edit, or delete anything their Twin knows, and visitors are informed upfront that conversations may be reviewed by the owner. During the Live demo, I'll teach the Twin something new on stage and let the audience interrogate it.

- Event context: AI Tinkerers Bremen — 2026-03-25 — Bremen
- Public talk page: https://bremen.aitinkerers.org/talks/rsvp_BIo4d4pBN0I

### [Meet Reachy: Bringing AI Agents and Robots to Life](https://montreal.aitinkerers.org/talks/rsvp_W5uswbok9N0)

Reachy Mini is a voice-enabled and vision-capable AI robot that can see, speak, remember, reason through graph-based orchestration, use Databricks, and control a computer or external tools in real time.

- Event context: AI Tinkerers Montreal - March Demo Night — 2026-03-24 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_W5uswbok9N0

### [Agentic Data Science Patterns](https://berlin.aitinkerers.org/talks/rsvp_JY4fRVGs-2g)

Compare agentic patterns for data science workflows, e.g. tool use vs. code sandbox for plotting.

- Event context: AI Tinkerers Berlin Meetup - March 11, 2026 — 2026-03-11 — Berlin
- Public talk page: https://berlin.aitinkerers.org/talks/rsvp_JY4fRVGs-2g

### [AI en la agricultura](https://pereira.aitinkerers.org/talks/rsvp_WXoTAF62jr8)

We will present a multi-agent system that interacts with farmers via WhatsApp and a platform with AI agents supporting analytics.

- Event context: Cambio de paradigma AITINKERERS PEREIRA 2026 — 2026-02-26 — Pereira
- Public talk page: https://pereira.aitinkerers.org/talks/rsvp_WXoTAF62jr8

### [Finance Agent Evals - How to implement evals to a financial agents using A2A protocol](https://bogota.aitinkerers.org/talks/rsvp_5aCGjZcNjqA)

I’ll be presenting the project developed during the 'Papers' program, where we built an Analyst-Judge agent system via A2A. We will see how the Judge system initiates an evaluation scenario and engages the Financial Analyst agent. This agent asynchronously answers questions using different reasoning models, passing the results back to the Judge to compare the responses across all questions and models.

- Event context: AI Tinkerers Bogotá: El Primer Meetup de 2026 — 2026-02-26 — Bogotá
- Public talk page: https://bogota.aitinkerers.org/talks/rsvp_5aCGjZcNjqA

### [SnowFlow AI - go from documents to database in a flash!](https://dc.aitinkerers.org/talks/rsvp_kHTl-P8QmqQ)

An AI-powered financial document processing platform that automatically extracts, analyzes, and structures financial data from various document formats, and ingests it into Snowflake. Built for financial data processing workflows.

- Event context: AI Tinkerers - DC Metro Meetup - February 24th, 2026 — 2026-02-24 — DC
- Public talk page: https://dc.aitinkerers.org/talks/rsvp_kHTl-P8QmqQ

### [Building a Stock Market Research Agent with LangGraph](https://st-louis.aitinkerers.org/talks/rsvp_a06ZanAIgII)

I’m demonstrating Infera, an app that automates stock market due diligence. Instead of manually looking up tickers, Infera takes a list of companies (e.g., UBER vs. LYFT), pulls real-time data via Yahoo Finance, profiles leadership, and generates a ranked Markdown report with comparative radar charts.

- Event context: AI Tinkerers – St. Louis Meetup: February 4, 2026 — 2026-02-04 — St. Louis
- Public talk page: https://st-louis.aitinkerers.org/talks/rsvp_a06ZanAIgII

### [How We Made Specs Executable](https://seattle.aitinkerers.org/talks/rsvp_dkhHjJTdS2o)

We'll demo how to create a great spec using spec driven development and show how they can be executed from the web without ever opening Claude Code or your IDE.

- Event context: AI Tinkerers Seattle: January Meetup — 2026-01-31 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_dkhHjJTdS2o

### [Claude Code as an api](https://la.aitinkerers.org/talks/rsvp_1gHBwmYPbT4)

Show how to work with an open sourced version of claude code for use with ollama to generate runnable code

- Event context: January 29th - LA AI Tinkerers Meetup & Demos (w/ Special Guest Alibaba WAN) — 2026-01-30 — Los Angeles
- Public talk page: https://la.aitinkerers.org/talks/rsvp_1gHBwmYPbT4

### [Autobots - Loblaws Supply Chain agent](https://toronto.aitinkerers.org/talks/rsvp_ACqtABSgI0I)

Autobots is an autonomous AI agent system that manages supply chain exceptions (such as inventory shortages) for Loblaws. It proactively emails vendors to inquire information, consumes their replies, and updates internal database without human intervention. Built on LangGraph, the AI agent parses unstructured vendor emails, categorizes the topic, and dynamically determines the optimal next step to resolve issues automatically.

- Event context: AI Tinkerers Toronto - January 2026 Meetup at Google! — 2026-01-29 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_ACqtABSgI0I

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