會議的悖論
在這個我們可以傳訊息、共享文件、跨時區非同步工作的時代，你有沒有想過，為什麼我們還是要花好幾個小時開會？
答案觸及了人性的核心：我們與生俱來想要共同創造的驅動力。
當多個大腦匯聚時，我們會對齊目標和願景、在彼此的想法上延伸、集體挑戰假設，並創造出任何人單獨都無法達成的解決方案。這種協作方式不只是企業儀式——這是人類自然解決複雜問題的方式。
AI：強大但孤立
現在想想我們今天如何使用 AI。毫無疑問，AI 已經成為我們的個人生產力夥伴。但有件根本的東西不見了：人類最強大的問題解決超能力——協作。
儘管我們知道複雜挑戰需要多元觀點，我們卻把這些強大的工具限制在個人聊天視窗和個別工作流程中。但是，如果人類花這麼多時間開會共同創造，為什麼我們不設計讓 AI 與每個人協作，而是把它藏在各自的工具裡？
效能方程式不只是技術
雖然 AI 工具和模型到處都是，我們相信你也意識到 AI 有多有效仍然取決於你如何使用它。你的知識庫（現在 MCP 在這方面幫了很大的忙）結合你如何表達需求（提示詞）決定了你得到什麼。
我們相信，當 AI 應用於團隊而非個人時，會獲得更大的力量。團隊結合知識和技能，從 AI 獲得更多。每個成員帶來不同的專業知識和思考方式，讓 AI 運作得更好。當一個人在問 AI 的方式上沒看到某些東西時，另一個人會發現。團隊成員幫助補足彼此不知道的部分。這讓使用 AI 成為一個集體努力，每個人一起學習並獲得更好的結果。
前進的道路
AI 的未來在於我們將這些工具視為團隊成員，而不只是個人助手時，會運作得最好。我們想要打造的 AI 不只是幫助一個人獨自更快工作，而是讓我們的團隊協作更好。它們會保留人類團隊協作的特質，同時提升我們共同解決問題的能力。
The Paradox of Meetings
In an era when we can message, share documents, and work asynchronously across time zones, have you ever wondered, why do we still carve out hours of meetings?
The answer cuts to the heart of what makes us human: our innate drive to create together.
When multiple minds converge, we align on goals and vision, build on each other's ideas, challenge assumptions collectively, and create solutions none of us would have reached alone. This collaborative approach isn't just a corporate ritual—it's how humans naturally solve complex problems.
AI: Powerful but Isolated
Now consider how we use AI today. It is no doubt that AI has become our personal productivity companion. But something fundamental is missing: humanity's greatest problem-solving superpower—collaboration.
Despite knowing that complex challenges demand diverse perspectives, we've confined these powerful tools to personal chat windows and individual workflows. But, If humans spend so much time in meetings to co-create, why aren't we designing AI to collaborate with everyone instead of hiding in each of our tools?
The Effectiveness Equation is not just about Tech
While AI tools / models are everywhere, we believe you must also realized how effective AI is still depends on how you use it. Your knowledge base (now MCP helps a lot with that) combined with how you express what you need (prompts) determines what you get.
We believe AI gains even more power when applied across teams instead of individuals. Teams combine knowledge and skills to get more from AI. Each member brings different know-how and ways of thinking that make AI work better. When one person doesn't see something in how to ask AI, another person catches it. Team members help fill in what others don't know. This makes using AI a group effort where everyone learns together and gets better results.
The Way Forward
The future of AI will work best when we see these tools as team members, not just personal helpers. We want to build AI which not just helps one person work faster alone, but makes our teamwork better. They'll keep what makes human teamwork special while boosting how we solve problems together.
