7 AI Brainstorming Tools for Different Ways of Thinking
There is no single best AI brainstorming tool. The better question is what you want to happen to an idea after the first conversation.
Some tools are good at producing possibilities quickly. Some help you organize what you already know. Others give you a visual space where unfinished thoughts can remain visible while you work on them.
If you are brainstorming with AI, the main difference is not which model you use. It is where the thinking lives.
The short answer
- ChatGPT — best for fast conversational brainstorming
- Claude — best for exploring a large amount of context in conversation
- Miro — best for collaborative visual brainstorming
- Notion — best for organizing ideas once you know their structure
- Obsidian — best for connecting ideas as a long-term knowledge base
- A whiteboard + chatbot — best if you want to build your own workflow
- Spoor — best for keeping an evolving idea, its references, and AI responses together on a persistent canvas
The important distinction is between generating ideas and developing ideas.
What makes a good AI brainstorming tool?
Brainstorming is rarely just asking a model:
“Give me 20 ideas.”
That is useful for getting started, but real brainstorming usually produces something messier:
- half-formed ideas
- questions
- contradictions
- screenshots
- references
- possible directions
- things that might be important later
- ideas that turn out to be wrong
A useful brainstorming tool should let you work with that mess without forcing you to decide too early what the final structure is.
This creates two broad approaches.
Generation-first
You ask the model for possibilities and evaluate the results.
Prompt → ideas → choose
This is fast and works well when you need a burst of possibilities.
Development-first
You keep the original material visible while repeatedly questioning, connecting, changing, and expanding it.
Idea → material → questions → connections → development
This takes more active participation, but it is useful when the idea itself is still changing.
Neither approach is universally better. They solve different problems.
1. ChatGPT — conversational brainstorming
ChatGPT is a natural choice when you want to think by talking.
You can throw out an incomplete thought, ask for alternatives, challenge an assumption, or simply keep asking “what if?”
It is particularly good at the first few minutes of a brainstorm, when you don't yet know what direction you want to take.
The limitation is the shape of the interaction.
A conversation is inherently sequential. One response follows another, so earlier possibilities gradually move out of view. If you end up with ten useful ideas, two screenshots, and three competing directions, keeping all of them visible requires some manual organization.
Best for: fast exploration through conversation.
Trade-off: the conversation is easy to continue, but harder to work with as a collection of separate ideas.
2. Claude — brainstorming with a large context
Claude is useful when your starting point is already substantial.
Instead of beginning with a blank prompt, you might give it a long brief, research notes, an existing draft, or a collection of background material and ask it to explore possibilities.
That makes it useful for context-heavy brainstorming.
The basic interaction is still conversational, though. If your process produces many independent ideas that need to be compared, moved around, or revisited later, the chat transcript is not necessarily the best workspace for that process.
Best for: exploring an idea when you already have a lot of context.
Trade-off: more context does not automatically create a spatial workspace for the ideas that emerge.
3. Miro — collaborative visual brainstorming
Miro approaches brainstorming from the opposite direction.
Instead of starting with a conversation, you start with a board. Sticky notes, diagrams, images, and other objects can be arranged spatially, which makes it particularly useful for workshops and collaborative sessions.
This works well when several people are contributing at the same time.
The limitation is that a visual board and an AI conversation are still somewhat different things. If you want a model to examine a particular cluster of ideas, you may need to move information between the board and the AI workflow.
Best for: collaborative workshops and visual ideation.
Trade-off: the board is spatial, while the AI interaction may still be separate from the objects you are arranging.
4. Notion — brainstorming after the structure becomes clearer
Notion works well when you already have some idea of how you want to organize the information.
You might create a page for a project, a database for research, or separate entries for different concepts.
That structure becomes useful once the brainstorm starts turning into something more organized.
But early brainstorming is often exactly when the structure is unclear.
You may not know whether something is a note, a category, a reference, a sub-project, or an idea worth keeping. A page-and-database system can therefore feel more natural after the shape of the project has emerged.
Best for: organizing ideas after their structure becomes clearer.
Trade-off: it can encourage structure before you know what the structure should be.
5. Obsidian — connecting ideas over time
Obsidian is built around notes and links between them.
That makes it useful for people who want their ideas to become part of a long-term personal knowledge base. Backlinks and linked notes make relationships between concepts explicit.
It is particularly strong when you already think in terms of documents, references, and a knowledge graph.
Brainstorming is a slightly different activity, though.
During an early brainstorm, you may want to put fragments, images, questions, and competing ideas next to each other without deciding what each one should become. A note graph can represent those relationships, but it does not necessarily provide the same kind of working surface.
Best for: long-term connected knowledge.
Trade-off: a knowledge graph and a brainstorming workspace are related, but they are not the same thing.
6. A whiteboard + a chatbot — build your own workflow
There is another surprisingly effective option: use a canvas such as tldraw or Excalidraw alongside your preferred AI chatbot.
You can put your ideas on one side and ask the model questions on the other.
This gives you the freedom of a visual workspace without committing to a specialized system.
The downside is the glue.
You have to decide what gets copied from the chat. You have to preserve useful responses. You have to move information around. Eventually you may have a good board and a good conversation, but they remain two separate places.
Best for: people who want maximum flexibility and don't mind maintaining the workflow themselves.
Trade-off: the more your brainstorm grows, the more manual coordination it requires.
7. Spoor — when the brainstorm itself becomes the workspace
Spoor takes a different approach.
Instead of treating AI as a conversation that happens beside your work, Spoor puts the conversation inside the workspace where the work is developing.
Notes, screenshots, documents, references, and AI responses can exist as editable cards on the same infinite canvas.
You can select a group of cards and ask an AI persona to:
- challenge an assumption
- find a contradiction
- connect two ideas
- expand a weak concept
- reorganize a group of thoughts
- look at the same material from another perspective
The response becomes another piece of the canvas rather than another message buried in a transcript.
This matters when the brainstorm is no longer:
“Give me some ideas.”
and becomes:
“I have all these things. What do they have to do with each other?”
The canvas gives you a place to keep the unfinished state of the idea visible.
You can move things around, keep multiple directions alive, discard what doesn't work, and return to the project later without reconstructing the whole conversation.
Spoor is not necessarily the right choice for a five-minute brainstorm or a real-time workshop with twenty people. It is designed for a different situation:
You have an idea that is not finished yet, and you want to stay with it.
Which AI brainstorming approach should you choose?
| If you want to... | Consider |
|---|---|
| Generate possibilities quickly | ChatGPT |
| Explore a large amount of context | Claude |
| Brainstorm with a team | Miro |
| Organize ideas into pages and databases | Notion |
| Build a connected knowledge base | Obsidian |
| Design your own visual + AI workflow | Whiteboard + chatbot |
| Keep ideas, references, and AI responses together while they develop | Spoor |
There is no need to choose one tool for everything.
A useful workflow might even move between them: use a chatbot when you need rapid conversation, a knowledge base when information needs to become permanent, and a canvas when the relationships between unfinished ideas matter most.
The key question is not:
Which AI gives me the most ideas?
It is:
What happens to those ideas after they appear?
If they disappear into a chat history, the brainstorm ends when the conversation ends.
If they remain as objects you can inspect, connect, change, and return to, the brainstorm can become the beginning of something larger.
That is the kind of thinking space Spoor is built for.
7 种 AI 头脑风暴工具，对应不同的想事情方式
没有一种「最好的」AI 头脑风暴工具。更值得问的是：第一轮对话之后，这个想法要去哪儿。
有的工具擅长很快抛出可能性。有的帮你整理已经知道的东西。还有的给你一块看得见的空间，让还没成形的念头可以一直留在眼前。
用 AI 头脑风暴，差别通常不在用哪个模型，而在思考落在哪里。
简短结论
- ChatGPT — 适合快速、对话式的头脑风暴
- Claude — 适合带着大量上下文，在对话里往下探
- Miro — 适合多人一起的视觉头脑风暴
- Notion — 适合结构已经清楚之后，把想法收进页面和数据库
- Obsidian — 适合把想法连成长期知识库
- 白板 + 聊天机器人 — 适合自己拼工作流
- 雪泥 Spoor — 适合把还在变的想法、资料和 AI 回复，一起留在同一张持久画布上
关键区分是：生成想法，还是发展想法。
什么算好用的 AI 头脑风暴工具？
头脑风暴很少只是问模型：
「给我 20 个点子。」
起步可以这样，真正的头脑风暴通常更乱：
- 半成品念头
- 问题
- 互相打架的说法
- 截图
- 资料
- 可能的方向
- 以后也许重要的东西
- 后来证明是错的想法
好用的工具，是让你能跟这些乱摊子共事，而不强迫你过早决定最终结构。
于是大致有两种做法。
生成优先
你向模型要可能性，再从结果里挑。
提示词 → 点子 → 选择
快，适合需要一波可能性的时候。
发展优先
原材料一直看得见，你反复追问、连接、改、扩。
想法 → 材料 → 问题 → 连接 → 发展
更费参与，但想法本身还在变的时候，往往更合适。
两种没有绝对高下，解决的是不同问题。
1. ChatGPT — 对话式头脑风暴
想靠说话把事情想开，ChatGPT 很自然。
你可以扔一个不完整的念头，要替代方案，挑战一个假设，或者一直问「如果呢？」
尤其适合头脑风暴的头几分钟：方向还没定。
限制在交互的形状。
对话天生是一条线。一条回复接着一条，早先的可能性会慢慢滑出视野。如果你有十个有用念头、两张截图、三个互相竞争的方向，要把它们同时摊开，就得另外组织。
适合： 用对话快速探路。
代价： 对话很好继续，但很难当成一堆彼此独立的想法来摆弄。
2. Claude — 带着大上下文头脑风暴
起点已经很厚的时候，Claude 有用。
不是从空白提示开始，而是给它长 brief、研究笔记、已有草稿或一堆背景，让它帮你探可能性。
这适合上下文很重的头脑风暴。
基本交互仍是对话。如果过程里冒出许多需要比较、挪动、以后再看的独立想法，聊天记录未必是最好的工作台。
适合： 已经有大量上下文时，继续探一个想法。
代价： 上下文多，并不自动变成想法可以摆开的空间工作区。
3. Miro — 协作式视觉头脑风暴
Miro 从相反方向入手。
不是从对话开始，而是从一块板开始。便利贴、图、图片可以空间排布，适合工作坊和多人同时贡献。
几个人一起往上扔东西时，这很合适。
限制是：视觉板和 AI 对话仍常常是两件事。想让模型盯某一簇想法，往往要在板和 AI 之间搬信息。
适合： 协作工作坊和视觉发散。
代价： 板是空间的，AI 交互仍可能和你正在摆的物件分开。
4. Notion — 结构清楚之后的头脑风暴
你已经知道信息大概怎么收的时候，Notion 顺手。
可以为项目建页、为研究建数据库、为不同概念建条目。
头脑风暴开始变成更有组织的东西时，这种结构才真正有用。
但早期头脑风暴，恰恰是结构还不清楚的时候。
你可能还不知道某样东西是笔记、分类、资料、子项目，还是值得留下的念头。页面加数据库，往往在项目形状已经冒出来之后才更自然。
适合： 结构变清楚之后整理想法。
代价： 容易在你还不知道该是什么结构时，就先逼出结构。
5. Obsidian — 把想法连成长期网络
Obsidian 围绕笔记和笔记之间的链接。
适合希望想法进入长期个人知识库的人。反向链接让概念之间的关系显式。
你已经习惯用文档、资料和知识图谱思考时，它很强。
但头脑风暴是略有不同的活动。
早期你可能想把碎片、图片、问题、互相竞争的念头并排放着，还不决定每一块会变成什么。笔记图谱可以表示那些关系，却不一定提供同一种工作台面。
适合： 长期、相互连接的知识。
代价： 知识图谱和头脑风暴工作区相关，但不是同一件事。
6. 白板 + 聊天机器人 — 自己拼工作流
还有一种出奇有效的办法：tldraw、Excalidraw 这类画布，配上你常用的 AI 聊天。
一边放想法，一边问模型。
你得到视觉工作区的自由，又不必绑死在某个专用系统上。
麻烦在胶水。
你得决定聊天里什么该拷出来。得保住有用的回复。得搬来搬去。最后也许板也好、对话也好，它们仍是两个地方。
适合： 要最大灵活、不介意自己维护工作流的人。
代价： 头脑风暴长得越大，手工协调越多。
7. 雪泥 Spoor — 当头脑风暴本身变成工作区
雪泥走另一条路。
不是把 AI 当成工作旁边的一场对话，而是把对话放进事情正在发生的那块工作区里。
笔记、截图、文档、资料和 AI 回复，都可以作为可编辑卡片，待在同一张无限画布上。
你可以选中一簇卡片，请一个 AI 人设去：
- 挑战一个假设
- 找出矛盾
- 连接两个想法
- 展开一个弱概念
- 重组一堆念头
- 从另一个角度看同一批材料
回复会变成画布上的又一块，而不是埋进对话记录的又一条消息。
这在头脑风暴不再是：
「给我一些点子。」
而变成：
「我已经有这些东西。它们彼此有什么关系？」
时尤其要紧。
画布让未完成的状态可以一直看得见。
你可以挪、让多个方向同时活着、丢掉不行的、过几天回来也不用把整场对话重建一遍。
五分钟的头脑风暴，或二十人的实时工作坊，雪泥不一定合适。它针对的是另一种情况：
你有一个还没做完的想法，而且你想跟它待在一起。
该选哪一种 AI 头脑风暴方式？
| 如果你想…… | 可以考虑 |
|---|---|
| 很快生成可能性 | ChatGPT |
| 带着大量上下文往下探 | Claude |
| 和团队一起头脑风暴 | Miro |
| 把想法收进页面和数据库 | Notion |
| 建相互连接的知识库 | Obsidian |
| 自己设计视觉 + AI 工作流 | 白板 + 聊天机器人 |
| 想法、资料和 AI 回复一边发展一边待在一起 | 雪泥 Spoor |
不必为所有事选同一个工具。
有用的工作流甚至会在它们之间移动：需要快速对话时用聊天；信息要变成长期资产时用知识库；未完成想法之间的关系最要紧时用画布。
关键问题不是：
哪个 AI 给我的点子最多？
而是：
点子出现之后，会发生什么？
如果它们消失在聊天记录里，对话一结束，头脑风暴也就结束了。
如果它们仍是你可以检查、连接、改、再回来看的物件，头脑风暴可以变成更大一件事的开头。
雪泥就是为这种思考空间做的。
Related
- How to Develop an Idea with AI Without Letting AI Take Over / 怎样用 AI 发展一个想法，而不把主导权交给 AI
- AI Writing Tools: When AI Should Help You Think, Not Just Write / AI 写作工具：什么时候该让 AI 帮你想，而不只是帮你写
- All guides
- Spoor home
- Community canvases