# Open Source Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/open-source
> Markdown URL: https://aitinkerers.org/technologies/open-source.md
> Technology record last updated: 2026-02-24T08:24:20Z
> Generated: 2026-09-21T21:48:43Z

Open Source is a development model: its source code is publicly accessible, allowing free use, modification, and redistribution under an OSI-approved license.

Open Source technology operates on a decentralized peer-production model, making the core source code transparent and universally accessible. This approach encourages open collaboration globally, driving rapid, community-led innovation (e.g., Linux, Git, Apache HTTP Server). The Open Source Initiative (OSI) sets the standard via The Open Source Definition (OSD), ensuring licenses permit derivative works and redistribution. Economically, this model is massive: a 2024 Harvard study estimated the ecosystem's demand-side value at $8.8 trillion, confirming its central role in modern global tech infrastructure.

- Official technology site: https://opensource.org
- Public AI Tinkerers demos and talks: 12
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Learn Anything by Doing: An Agent That Teaches, a Grader That Can't Flatter You](https://hong-kong.aitinkerers.org/talks/rsvp_9jqGP6qJZHg)

Carpenter is a tool for learning by doing: you tell your AI agent what you want to master, it drafts a course outline for your approval, renders Jupyter notebooks with practice stubs and quizzes — and the second you hit Run, you get an instant, honest per-case PASS/FAIL. The agent teaches; carpenter grades. The key trust move: grading is locked to an answer key the agent can't see at grade time (lesson verify against an authored reference solution), and the grading helper is structurally verification-only — it can never print expected. A pass is a real pass, not the AI being nice to you. Live demo, two beats. Beat 1 (the main event): from "I want to learn X" to a graded notebook in minutes — agent drafts the plan, I approve it, a rendered notebook appears (SQLite is the source of truth; notebooks are just views), I fill in a practice stub, Run, instant feedback, then progress summary showing exactly what's done and where I'm stuck. Beat 2 (the twist, short): this tool is itself built by the same kind of loop — I'll add a command via an agent and show the build refusing to compile until the docs and tests exist. The learning tool dogfoods its own philosophy.

- Event context: AI Tinkerers Hong Kong: August Meetup with OAX Foundation and GMAsia — 2026-08-31 — Hong Kong
- Public talk page: https://hong-kong.aitinkerers.org/talks/rsvp_9jqGP6qJZHg

### [Construindo Linr, um editor interativo de timelines com Deepseek rodando no Cursor](https://curitiba.aitinkerers.org/talks/rsvp_xqVhn6TV5MI)

O Linr é um editor online de timelines visuais - útil para checkpoints, milestones, diagramas, eventos historicos, registros de viagem, funil de vendas e afins. Configurei os modelos DeepSeek V4 dentro do Cursor usando o Cline como harness, porque o agente nativo do Cursor não aceita rotear para a API da DeepSeek. Com esse setup rodando, o Linr saiu do zero. Na demo ao vivo eu mostro, em três atos: O setup : por que o caminho obvio não funciona (o agente do Cursor recusa a chave externa) e como o Cline resolve isso dentro da mesma IDE. O coração: pego o Linr num estado inacabado e dou uma tarefa real ao agente rodando DeepSeek ao vivo - uma feature que falta ou um bug - e vocês veem o modelo construindo software de verdade, com o custo em dolar subindo na tela. O payoff: abro o app funcionando e mostro quanto custou, em tokens e em dólar, chegar ali.

- Event context: AI Tinkerers Curitiba: Encontro de Agosto (no EBANX) — 2026-08-26 — Curitiba
- Public talk page: https://curitiba.aitinkerers.org/talks/rsvp_xqVhn6TV5MI

### [LMStack - Development stack using local LLMs](https://seattle.aitinkerers.org/talks/rsvp_A8GvI03RSK8)

Writing real code with local LLMs is difficult. lmstack is a local stack for real development which puts your GPU to work on the right kind of tasks. LMStack introduces an infrastructure manager and a task classifier. Both of them work together to make sure local models are always at work. I've been using this stack for a month to build features on an open source project - Clawrium. LMStack show why the entire stack needs to be different when using local llms and what're the pitfalls of using standard tooling. What works and what to avoid.

- Event context: AI Dev Tools Track - Seattle - August 4 — 2026-08-05 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_A8GvI03RSK8

### [Building blocks for voice-to-voice AI](https://sf.aitinkerers.org/talks/rsvp_OaIp4wdokw0)

Building fast, reliable conversational voice bots on top of today's generative AI models and tooling requires combining a number of technologies. Major components include network transport, audio compression and processing, text-to-speech, multi-turn LLM inference, speech-to-text, tool use, and interruption handling. We'll start with a demo of a voice bot built with Open Source libraries running at 500ms voice-to-voice latency. Then we will do a lightning tour of the demo bot's components and 50 core lines of code.

- Event context: AI Tinkerers - San Francisco - August 2024 Meetup — 2024-08-22 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_OaIp4wdokw0

### [momentum - ensure code correctness at every git push](https://sf.aitinkerers.org/talks/rsvp_kVITxR9pLHE)

momentum is a code auditor that analyses the necessary code behavior and tests it at every git push to ensure the code is ready for production.

- Event context: AI Tinkerers - San Francisco - Summer Edition - July 2024 — 2024-07-12 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_kVITxR9pLHE

### [Guided question refinement - A better approach to repetitive online quesitonairres?](https://seattle.aitinkerers.org/talks/rsvp_Jwgq6QeeXBY)

Have you ever had to fill out a long questionnaire or survey and end up finding yourself saying the same thing over and over again for each question? I think there's a simple way to really improve the UX of user surveys using LLMs without changing too much about how they're written. Join me as I show off a hastily written and kind of working system that can answer questions on a user's behalf, or prompt the user for more information when needed.

- Event context: AI Tinkerers Seattle - June 2024 — 2024-06-07 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_Jwgq6QeeXBY

### [Bolna](https://bengaluru.aitinkerers.org/talks/rsvp_3yPJ5QnuWNU)

Bolna is the end to end infra to build, deploy and manage human-like voice AI agents. We provide a single API for voice conversational orchestration, taking care of human-like nuances (such as interruption handling, background noise detection etc.) to ensure high-quality low-latency conversations. Our orchestration is open-source and modular, allowing users to use open-source models for better pricing.

- Event context: AI Tinkerers - Bangalore Inaugural - RSVP REQUIRED — 2024-06-02 — Bengaluru
- Public talk page: https://bengaluru.aitinkerers.org/talks/rsvp_3yPJ5QnuWNU

### [LLM.f90 - Minimal Large Language Model Inference Framework](https://toronto.aitinkerers.org/talks/rsvp_o5j_P1vjl_Q)

This is a zero-dependency LLM inference framework written in Fortran. The motivation was to have a compact, fast, framework that can run modern LLMs that is easy to understand and modify. It's written in Fortran because the language provides numpy-style matrix manipulation in a fast, compiled language. Currently supports Llama, Phi, and a few other models. This is an open source project.

- Event context: AI Tinkerers - Toronto - May 2024 Meetup — 2024-05-30 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_o5j_P1vjl_Q

### [Secret Llama](https://nyc.aitinkerers.org/talks/rsvp___4rEgVBC30)

Free and fully private chatbot that runs entirely within your browser.

- Event context: AI Tinkerers NYC May 2024 Meetup — 2024-05-22 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp___4rEgVBC30

### [Cross-training models on multiple providers](https://seattle.aitinkerers.org/talks/rsvp_Z0XdL4RVkyw)

OpenPipe is releasing an open-source library to streamline the process of fine-tuning an LLM on any provider with minimal effort. We've personally benefited from the open-source community in numerous ways, and we'd like to show developers how easy it is to use the latest tools to save massive amounts on compute costs.

- Event context: AI Tinkerers Seattle - April 2024 Meetup — 2024-04-26 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_Z0XdL4RVkyw

### [Kids Create: ToyGeniusLab AI Toys](https://seattle.aitinkerers.org/talks/rsvp_ok4j_nq7IT0)

ToyGeniusLab invites kids into the magical world of AI, enabling them to design and personalize their very own talking toy. Through an intuitive app, kids are guided step-by-step to craft their toy's unique personality traits and behaviors. Once their creation is complete, parents can bring the toy to life using recommended portable Bluetooth speakers and microphone sets, housed within a custom-printed toy figure. ToyGeniusLab not only fosters creativity but also introduces children to the basics of AI and technology, making learning both fun and interactive. NOTE: Planning to make the repo public on the day of the demo. Please see the demo video.

- Event context: AI Tinkerers Seattle - February 2024 Meetup — 2024-02-29 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_ok4j_nq7IT0

### [Blablabeats](https://sf.aitinkerers.org/talks/rsvp_meV9I9OJw40)

Live sitcom sound track

- Event context: 🤖🔄🧠 AI Tinkerers SF - August Meetup — 2023-08-10 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_meV9I9OJw40

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