# Kimi Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/kimi
> Markdown URL: https://aitinkerers.org/technologies/kimi.md
> Technology record last updated: 2026-03-03T08:46:19Z
> Generated: 2026-08-26T18:19:31Z

Moonshot AI’s flagship LLM featuring a massive 2-million-character context window for deep document analysis.

Developed by Beijing-based Moonshot AI, Kimi excels at processing ultra-long-form content (handling up to 200,000 Chinese characters in standard use and 2 million in advanced testing). It serves as a high-performance research assistant capable of parsing dozens of complex PDFs, debugging expansive codebases, and maintaining coherent long-term memory during extended sessions. By leveraging its proprietary infrastructure, Kimi delivers precise data extraction and synthesis for power users who outpace the token limits of standard industry models.

- Official technology site: https://kimi.moonshot.cn
- Public AI Tinkerers demos and talks: 6
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Harness e Inferência: O que são, o que comem e como gerenciá-los](https://saopaulo.aitinkerers.org/talks/rsvp_h90U6SZeMDc)

Have you ever said "Good Morning to your AI?", Kimchi address the problem that you don't need to have the best model to answer you a simple Good Morning. Kimchi is an Open-source tool that allows you to manage the Harness, it gives you the control of all the aspects , since which is the best/cost efficiency model to execute every task.

- Event context: AI Tinkerers SP - Meetup de Junho — 2026-06-25 — São Paulo
- Public talk page: https://saopaulo.aitinkerers.org/talks/rsvp_h90U6SZeMDc

### [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

### [AI Launcher for old games on Mac OS (very millennial / boomer)](https://seattle.aitinkerers.org/talks/rsvp_jmXoHb_fAoc)

Cellar is AI pipeline based on Wine with the only goal – to launch an old games on your Mac. Launching old games on Mac is especially notorious business based on reading manuals, tweaking configs and it is not fun (at least for me). To help nostalgic newbies as I am, I made this tool – Cellar. It is a bundle of Wine and AI pipeline. You point it to the installation file and does everything for you: unpacks it, installs, creates a bottle and finds correct configuration to launch. Once the game is launched, successful config stored and you don't need AI anymore. Additionally, all Cellar agents have shared Wiki that collects all their experiences together – so that if one Cellar agent launched game correctly, another one will read about it. It currently supports Claude, Deepseek and Kimi.

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

### [My own version of OpenClaw focused on 24x7 development](https://columbus.aitinkerers.org/talks/rsvp_nJf4Q-0QtQA)

I wanted an AI that builds and tests 24x7 and only pings me when it actually needs input. The Continuous Executive Coding Agent is the answer: a PM2-backed executive loop running Agent SDK workers that pulls from a priority queue, breaks goals into steps and contracts, retries with different strategies on failure, and escalates through Gmail or Discord only when truly stuck. Everything runs under an immutable constitution. It's evolved through three stages. First, the executive loop itself, with the goals/steps/contracts hierarchy and an identity layer for email-in, Discord-out. Second, multi-vendor parity, so workers run on Claude, Codex, or Kimi K2.5, selectable per goal. Third, harness integration, where my plan-then-build pipelines (generic, EDS, study) plug in as meta-workers or still run standalone from a unified CLI.

- Event context: AI Tinkerers - Columbus April Meetup — 2026-04-06 — Columbus
- Public talk page: https://columbus.aitinkerers.org/talks/rsvp_nJf4Q-0QtQA

### [OpenClaw for a Equity Fund Manager](https://london.aitinkerers.org/talks/rsvp_5zTwf6Gljn4)

Personal set up of OpenClaw for everyday life and equity fund management. Custom skills (twitter monitoring, earnings previews reviews, database)

- Event context: OpenClaw Demo Night // 5th March — 2026-03-05 — London
- Public talk page: https://london.aitinkerers.org/talks/rsvp_5zTwf6Gljn4

### [Using AI to make the science behind Kabuki Syndrome more accessible](https://boston.aitinkerers.org/talks/rsvp_JYH_omkmLYc)

Kabuki Syndrome is a rare disease affecting 1 in 32,000 births. There is currently no cure, but there is a fair clip of research being conducted and published every month. As a parent of a child with Kabuki, I have long struggled to read and comprehend the dense, jargon-filled academic papers that report on this research, despite my great curiosity. Due to the rarity of the condition, there is little to no journalistic reporting on these kinds of academic papers. I will share a project I'm working on that is intended to bridge that gap with AI, using the latest LLMs to craft stories more accessible to the broader Kabuki community. In the demo I will show how I use AI to break down the papers into their individual claims, then how I transform those claims, using multiple prompts and workflows, into easy-to-read plain english versions. These plain-english versions live in a UI that has two goals. One is to be polished and reader-friendly, up to the standard of a national magazine, with subheaders, pull quotes, etc. Another is to provide an inline interactive lens onto the original text of the article, with individual sentences that can morph to show the claims and sentences in the original paper they are based on.

- Event context: {Cancelled due to Blizzard Warning } AI Tinkerers Boston: February 2026 Meetup — 2026-02-23 — Boston
- Public talk page: https://boston.aitinkerers.org/talks/rsvp_JYH_omkmLYc

## Related Technologies

- [Claude](https://aitinkerers.org/technologies/claude) ([Markdown](https://aitinkerers.org/technologies/claude.md)) — 171 public demos
- [Codex](https://aitinkerers.org/technologies/codex) ([Markdown](https://aitinkerers.org/technologies/codex.md)) — 43 public demos
- [Gemini](https://aitinkerers.org/technologies/gemini) ([Markdown](https://aitinkerers.org/technologies/gemini.md)) — 187 public demos
- [APIs](https://aitinkerers.org/technologies/apis) ([Markdown](https://aitinkerers.org/technologies/apis.md)) — 19 public demos
- [CC](https://aitinkerers.org/technologies/cc) ([Markdown](https://aitinkerers.org/technologies/cc.md)) — 1 public demo
- [Claude Agent SDK](https://aitinkerers.org/technologies/claude-agent-sdk) ([Markdown](https://aitinkerers.org/technologies/claude-agent-sdk.md)) — 16 public demos
- [DeepSeek API](https://aitinkerers.org/technologies/deepseek-api) ([Markdown](https://aitinkerers.org/technologies/deepseek-api.md)) — 5 public demos
- [git](https://aitinkerers.org/technologies/git) ([Markdown](https://aitinkerers.org/technologies/git.md)) — 23 public demos
- [GPT-4](https://aitinkerers.org/technologies/gpt-4) ([Markdown](https://aitinkerers.org/technologies/gpt-4.md)) — 529 public demos
- [Harness](https://aitinkerers.org/technologies/harness) ([Markdown](https://aitinkerers.org/technologies/harness.md)) — 2 public demos
- [Kimchi](https://aitinkerers.org/technologies/kimchi) ([Markdown](https://aitinkerers.org/technologies/kimchi.md)) — 1 public demo
- [LangGraph](https://aitinkerers.org/technologies/langgraph) ([Markdown](https://aitinkerers.org/technologies/langgraph.md)) — 66 public demos
- [Next](https://aitinkerers.org/technologies/next) ([Markdown](https://aitinkerers.org/technologies/next.md)) — 186 public demos
- [Node](https://aitinkerers.org/technologies/node) ([Markdown](https://aitinkerers.org/technologies/node.md)) — 96 public demos
- [OpenAI](https://aitinkerers.org/technologies/openai) ([Markdown](https://aitinkerers.org/technologies/openai.md)) — 111 public demos
- [OpenAI API](https://aitinkerers.org/technologies/openai-api) ([Markdown](https://aitinkerers.org/technologies/openai-api.md)) — 518 public demos
- [OpenClaw](https://aitinkerers.org/technologies/openclaw) ([Markdown](https://aitinkerers.org/technologies/openclaw.md)) — 48 public demos
- [Opus 4](https://aitinkerers.org/technologies/opus-4) ([Markdown](https://aitinkerers.org/technologies/opus-4.md)) — 10 public demos