MoonshotAI
Featured
Kimi-K3
Kimi K3 is an open-weight, 2.8T-parameter native multimodal agentic model with a 1M-token context window, designed for frontier coding, knowledge work, and reasoning tasks.
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It provides a structured, end-to-end framework for discussion quality—covering pre-meeting alignment, process control, faithful externalization, shared modeling, and action follow-through—with full chapters, practical templates, and AI-era considerations.
Who it is for
- Meeting facilitators and moderators
- Team leaders and managers in complex organizations
- Consultants and coaches who support organizational collaboration
- Knowledge workers seeking better meeting outcomes
Use cases
- Preparing meeting goals, roles, and boundaries before discussions
- Controlling information, topics, time, and emotional order during meetings
- Converting conclusions into accountable actions and verifiable results
- Building shared mental models in teams through structured clarification and modeling
Strengths
- Clear step-by-step methodology from pre-meeting to post-meeting action
- Includes multiple practical templates and an operational SOP
- Offers both full-length chapters and condensed practice documents
- Explicitly connects organizational habits to AI-era business modeling
Considerations
- Primarily a knowledge framework rather than a software tool or automated solution
- Content is in Chinese, which may limit accessibility
- Approach is experience-based without empirical validation provided in the README
README quick start
认知对齐：复杂组织中的高质量讨论方法
从目标对齐、过程控制、忠实外化，到共同建模与行动闭环。
这个项目沉淀一套关于复杂组织如何建立共同认知的方法体系。
核心问题：为什么很多会议结束后，大家听到了同样的话，却没有形成同样的理解？
核心方法：
- 讨论前：明确背景、目标、角色和边界。
- 讨论中：控制信息、议题、时间和情绪秩序。
- 认知对齐：先忠实外化，再共同澄清，最后结构化建模。
- 行动闭环：将结论转化为责任、时间和可验证结果。
核心原则
先忠实还原，再共同澄清，最后形成判断。
完整版（章节串联阅读）
《高质量讨论的构建方法 · 从目标对齐到共同认知》完整版按章节拆解为可串联阅读的 Markdown 文档，也可直接下载 PDF 完整版：
📖 进入章节导航 →
| 章节 | 内容 |
|---|---|
| 01 | 一个工作习惯：为什么这样的动作如此少见 |
| 02 | 讨论之前：目的、产出、角色、边界 |
| 03 | 过程控制：发言顺序、跑题分流、四种秩序 |
| 04 | 从模糊到清晰：忠实外化、澄清、建模 |
| 05 | 清晰化与防御：态度传递与心理安全 |
| 06 | 业务建模：对象、动作、角色、流程 |
| 07 | 现场操作手册：会前、会中、会后怎么做 |
| 08 | 组织与AI：个人习惯变成组织能力 |
| 09 | 结语：帮助一群人看见同一个现实 |
附录：一页会议定义模板 ｜ 会后共同模型模板 ｜ 讨论质量自检
实践文档（精简版）
- docs/01-完整报告.md：完整方法论
- docs/02-会议实战SOP.md：会议执行流程
- docs/03-白板与会议记录模板.md：可复用模板
- docs/04-典型案例库.md：实践案例
- docs/05-AI时代的业务建模.md：AI时代关联
维护原则
这个项目采用持续演化方式维护：新增观点优先补充完整体系，不用摘要替代完整版。
Description
复杂组织中的认知对齐与高质量讨论方法
Related repositories
Similar projects matched by category, topics, and programming language.
lopopolo
Featured
harness-engineering
Harness Engineering is a methodology for improving coding agent outputs by carefully crafting the environment around them—providing curated context, tools, and executable constraints that encode an organization’s nonfunctional requirements and cumulative lessons.
slvDev
Featured
esp32-ai
A 28.9 million parameter language model runs on an $8 ESP32-S3 microcontroller entirely on-device, generating simple stories at about 9.5 tokens per second.