Artificial Intelligence in MindManager: Prompting
Hello!
As long as AI systems don't have a direct and complete access to our brains, high-quality external interaction with them will remain essential: prompts! To truly harness the power of AI and produce sophisticated and tailored results for oneself or one's company, well-structured prompts must be written.
Prompting: The Key to Effective AI Interaction
Various prompt types exist, ranging from standard chatter to "Chain of Thoughts" and the more complex "Three of Thoughts" and others. Some require multiple communication steps, while others achieve good results even with zero-shots.
The more intelligent the AI and the better its working memory - and these are increasing rapidly -, the more effective zero-shot solutions become, but of course, only if we also act intelligently: Quality prompting is the key - detailed clear instructions and extensive contextual knowledge.
MindManager: A perfect Tool for Prompt Creation
It would be the perfect opportunity for MindManager to bundle its competencies and make them available in an expanded form!
Proposal:
- MindMap-to-Prompt Conversion: MindManager would be able to convert maps into prompts.
- Split-Screen View: The view could be divided into two window halves as desired:
a) One side would contain the map, allowing us to keep the structure in mind.
b) The other side would automatically display the prompt conversion. We could work in both halves, depending on what is currently more important. - Integrated AI Chat: There would also be an optional possibility to have a third window area for a chat with one of the AI models. Anyone who subscribes to such a model and has the API could use it directly in MM. The prompt that is created in our workspace could be sent to the chat at any time.
- AI Response to MindMap: The reverse direction is also conceivable: the AI's response could be converted into a map. Of course, both directions require various setting options to achieve useful results or visualizations.
- Linked Files Integration: Files linked to nodes or branches could be integrated into the prompt upon request. This way, the AI would not only take the map as a suggestion but also consider all the knowledge linked to it.
- Node Relation to Prompt Instruction: It would also make sense to consider how to convert relationships between nodes into specific instructions within the prompt.
- MindManager Element Integration: Other MindManager elements, such as formulas, could also be considered. They could also become part of prompts.
Conclusion
While refinement is necessary, the potential behind this concept is enormous!
Additional Thoughts
- Prompt Templates: Consider providing prompt templates for different AI models and tasks.
- Prompt Refinement: Allow users to refine prompts interactively, incorporating AI feedback.
- Community Collaboration: Facilitate community collaboration on prompt creation and sharing.
This proposal aims to enhance AI interaction by seamlessly integrating MindManager's mind mapping capabilities with prompt creation. By bridging the gap between structured visual thinking and AI prompting, this integration could empower users to generate more effective and creative prompts, leading to more sophisticated AI-generated results.
I kind of like this a lot! ;-)
I like this idea
What I forgot to mention in the proposal, which I took for granted, are the dimensions of effective zero-shot (direct inquiries without repeated interactions) prompts with sufficient AI working memory. I meant huge prompts consisting of several thousand or even millions of tokens, i.e., very detailed requests, instructions, and very extensive contexts - of course depending of the capabilities of the used model.
What a MindManager Graph or Map could do that normal prompting environments or pure text editors cannot do so well:
a) Concept or MindMaps are very efficient concept builder even for non linear modelling.
b) Their good visualization can offer us a quality/speed of overview we don't have in longer Texts.
c) MindManager already has the abbility to consider large amounts of Data in various forms and formats. We just need the ability to bundle and convert this information into professional AI ready (e.g.) Zero-Shot Prompts. We already have:
In extreme cases, this could mean entire "bookshelves" full of context information would be allowed to participate in this proces and become a Zero-Shot Prompt.
As you can see, I don't mean casual chatting with the AI or short texts that you can easily type directly into the chat anyway, but rather very extensive professional interactions where you want to achieve tailored results.
An AI cannot (yet) read minds, so at best it will deliver nice standard answers, if we do not sufficiently introduce it into our deeper concept or project world.
What I forgot to mention in the proposal, which I took for granted, are the dimensions of effective zero-shot (direct inquiries without repeated interactions) prompts with sufficient AI working memory. I meant huge prompts consisting of several thousand or even millions of tokens, i.e., very detailed requests, instructions, and very extensive contexts - of course depending of the capabilities of the used model.
What a MindManager Graph or Map could do that normal prompting environments or pure text editors cannot do so well:
a) Concept or MindMaps are very efficient concept builder even for non linear modelling.
b) Their good visualization can offer us a quality/speed of overview we don't have in longer Texts.
c) MindManager already has the abbility to consider large amounts of Data in various forms and formats. We just need the ability to bundle and convert this information into professional AI ready (e.g.) Zero-Shot Prompts. We already have:
In extreme cases, this could mean entire "bookshelves" full of context information would be allowed to participate in this proces and become a Zero-Shot Prompt.
As you can see, I don't mean casual chatting with the AI or short texts that you can easily type directly into the chat anyway, but rather very extensive professional interactions where you want to achieve tailored results.
An AI cannot (yet) read minds, so at best it will deliver nice standard answers, if we do not sufficiently introduce it into our deeper concept or project world.
Personally, I don't think any of this functionality really belongs in MindManager. Emulating a natural language interface will get out of date very quickly - just a few months if "prompt engineering" is included.
A better approach would be to lobby the AI vendors to import and export native OPML from the level below natural language. MindManager and other mind mapping products already handle OPML.
Converting OPML to and from knowledge is the crux of this and will need the power of AI to deal with inference and context. If it is buried in a proprietary interface it will be a less robust implementation that does not evolve.
Personally, I don't think any of this functionality really belongs in MindManager. Emulating a natural language interface will get out of date very quickly - just a few months if "prompt engineering" is included.
A better approach would be to lobby the AI vendors to import and export native OPML from the level below natural language. MindManager and other mind mapping products already handle OPML.
Converting OPML to and from knowledge is the crux of this and will need the power of AI to deal with inference and context. If it is buried in a proprietary interface it will be a less robust implementation that does not evolve.
I understand your point about needing a clever approach to keep up, and I agree that adhering to my exact proposal isn't "crucial" ;-) The key is to unlock the emerging potential of AI.
Development Environment: Truly professional prompts can be so extensive and complex that a very capable development environment is essential. Usual AI chats fall short of what I consider to be an appropriate platform for this purpose.
Existing Potential: MM is already a theory builder, organizer, and visualizer with which we are well familiar and often use. We wouldn't have to learn much new, and the tools are very good. This already offers a strong foundation as a development environment.
So on the one hand, we need access to AI capabilities. On the other hand, even if it's just a matter of simply printing something out or exporting it as a Word document, we need (and already have) support, ensuring all the necessary elements are there and well-presented. Large Prompts will likely also need some specific curation.
Review Environment: Complex prompting is less about appearance and more about the structure and quality of the content. Especially when starting large orders that you might even pay for, you don't want to begin with a flawed prompt. Therefore, a dedicated review environment would be ideal. This would allow us to meticulously assess the prompt's suitability for our needs and make any necessary edits before utilizing it.
I understand your point about needing a clever approach to keep up, and I agree that adhering to my exact proposal isn't "crucial" ;-) The key is to unlock the emerging potential of AI.
Development Environment: Truly professional prompts can be so extensive and complex that a very capable development environment is essential. Usual AI chats fall short of what I consider to be an appropriate platform for this purpose.
Existing Potential: MM is already a theory builder, organizer, and visualizer with which we are well familiar and often use. We wouldn't have to learn much new, and the tools are very good. This already offers a strong foundation as a development environment.
So on the one hand, we need access to AI capabilities. On the other hand, even if it's just a matter of simply printing something out or exporting it as a Word document, we need (and already have) support, ensuring all the necessary elements are there and well-presented. Large Prompts will likely also need some specific curation.
Review Environment: Complex prompting is less about appearance and more about the structure and quality of the content. Especially when starting large orders that you might even pay for, you don't want to begin with a flawed prompt. Therefore, a dedicated review environment would be ideal. This would allow us to meticulously assess the prompt's suitability for our needs and make any necessary edits before utilizing it.
I think it would be great to have a discussion space where ideas and tests can be shared. For me, the value that AI actually brings to the process is a bigger question than the mechanics of automation. This value can easily be taken for granted in the stampede, but is the difference between something "cool" and something that is used and improved over the long term.
I think it would be great to have a discussion space where ideas and tests can be shared. For me, the value that AI actually brings to the process is a bigger question than the mechanics of automation. This value can easily be taken for granted in the stampede, but is the difference between something "cool" and something that is used and improved over the long term.
i'll suggest you people have a look on NotionAI,
see how others already have implemented.
being late is not too bad, you could learnt from others, and then ADAPT!
i'll suggest you people have a look on NotionAI,
see how others already have implemented.
being late is not too bad, you could learnt from others, and then ADAPT!
I totally agree. Just do it! As a long-time fan of MindManager, which I've loved for almost decades, I'm thrilled that it's now also available on macOS (my favorite OS at the moment).
I managed to automate it in a surprisingly simple way on both platforms, Windows and macOS, using Python and connected it with all major AI LLMs.
Despite the fact that MindManager has become a Swiss Army knife for all kinds of purposes, I'm still very connected to the original mind-mapping idea - enriched with AI powers.
I totally agree. Just do it! As a long-time fan of MindManager, which I've loved for almost decades, I'm thrilled that it's now also available on macOS (my favorite OS at the moment).
I managed to automate it in a surprisingly simple way on both platforms, Windows and macOS, using Python and connected it with all major AI LLMs.
Despite the fact that MindManager has become a Swiss Army knife for all kinds of purposes, I'm still very connected to the original mind-mapping idea - enriched with AI powers.
Have a look at the MindManager add-In FileLinker with the AI-Convertor
FileLinker - Simply work more effectively (filelinkerenterprise.com)
I'm using it daily
Have a look at the MindManager add-In FileLinker with the AI-Convertor
FileLinker - Simply work more effectively (filelinkerenterprise.com)
I'm using it daily
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