I just saw the Fibery 2.0 waitlist/teaser page here:
It’s exciting to see the use-cases for expanded AI and highlights demonstrated together for a specific context (Product Dev with feedback management). But I’m really left wondering if the implementation of these features has been done in a general-enough way (or at least a generalizable way in the near future) such that these very powerful capabilities could be utilized meaningfully in a variety of different contexts.
For example the “Suggested highlights” feature is quite a bit like the AI (and not-AI) “related pages”, “suggested tags”, etc. features that many PKM tools have added over the past 1-2 years. And while I know PKM is not now and likely never will be a Fibery focus, for “second brain for teams” it could still be quite applicable, among other non-product (or non-feedback) contexts (e.g. linking meeting notes to project planning, etc.).
So can these features be used in a more general way? If not, that would seem to be the beginning of a pretty dramatic departure of Fibery team away from powerful, flexible, generalized features that are only demonstrated and marketed with a specific use case, toward actual dedicated functionality (more niche) tool set. Not to be too dramatic but I think that for me would somewhat be the death of the Fibery dream in my mind. I hope that’s not the case and I’m just reading too much into it. But when I came to write this topic and find the right Category for it I was definitely struck by whether the name of this Category - “Second Brain for Teams” even made sense for Fibery anymore…
At any rate I would love to see some discussion about these plans. What does this community think of what’s being shown here (much of which has been shown before, but not all working together)? Will these features significantly improve your workflows as-shown? How else might you think you can or would want to be able to use them?
Can you elaborate on what the various parts of the waitlist page made you think that the features shown would be functionality dedicated to a niche (to the exclusion of other non-niche use cases)…
We don’t compromise generality in all our features and releases I hope. Our long term vision did not change much, we just picked narrower niche and coherent set of use cases to get a better traction for the next 2-3 years.
You will learn more soon, but speaking about Highlight it is just a database linked with polymorphic relations with Sources and Targets databases, so you can use it for various use cases, but we did not think deep about use cases outside Product Teams so far.
Primary: collect product feedback and link it to product backlog, this understanding priorities based on customer/lead properties, pain level, frequency, and other signals that important for your company
Primary: collect Interviews/Calls, extract highlights and categorize them by Tags/Insights, similar to what Dovetail does, for example, thus generating for your business (it can be any business, not product-related)
Secondary: collect information about competitors, extract highlights and connect them to Problems/Strong-Weak Areas/etc to do a competitor analysis.
Secondary: collect any information in any domain, highlight interesting pieces of text and generate clusters from them. This is very generic and I did not explore it well enough.
In the first release we decided to allow single Highlight database, but under the flag as experimental feature it is possible to add many. I think people will definitely find creative ways how to use it.
I had a quick look at the Fibery 2.0 announcement and this is my impression:
Introduction to Fibery 2.0’s Core Feature
Focus: The upcoming version seems to revolve around the new “highlights” feature, which I believe will be a game changer for the platform.
Significance: This feature introduces a paradigm shift in how we perceive and utilize data within Fibery. It appears to be the most significant update due to its potential impact.
Technical Insights and Theoretical Background
Relevance: My experience in collective intelligence and neural networks suggests that creating relationship entities, though technically challenging, is a pivotal development, especially for understanding and integrating superintelligence.
Paradigm Shift: The core idea is that the real value in data comes not from the data objects themselves but from how users experience and interact with the relationships between these objects.
Alignments: This shift aligns well with both the concept of a “second brain for teams” and broader principles found in quantum science (which I won’t detail here to keep the focus).
Technical Challenges and Evolutionary Path
Database Limitations: Current database structures are limited in their ability to represent the dynamic meanings encapsulated by these new relationship entities.
Potential Solution: A unified model might replace multiple databases or entity types to better support this new data ecosystem.
Future Directions and Implications
Trend Toward Fluid Atomic Entities:
Multiple Identities and Functions: Future developments aim at creating entities capable of assuming multiple identities and fulfilling various functions simultaneously.
Highlight Entity as a Precursor: The highlight entity, likely evolving into a more versatile relationship entity, serves as an example of these atomic entities.
System Evolution: The increasing fluidity in meaning and purpose suggests that future systems may consist solely of these relationship entities, which interrelate to form meaningful and valuable structures.
Looking at Fibery now, the potential is there for mass adoption but I think it needs to fully focus and promote its core value, and not much more. The broader Fibery tries to be, the more it will fail to compete with other apps. The actual value, as far as I see, is that it facilitates insight in collective intelilgence ecosystems that leverage relationships in new ways, and present that as Fibery its power as well as pioneering work. What I would recommend is to introduce a new terminology or at least a new term for the method it uses to see and handle relations and meaning of data and value. The name Fibery in itself does not convey clear meaning, but it can introduce terms, or at least one term, that can be put on the market a new concept and approach that is significant, especially when handling superintelligence. The challenge here, especially for Michael Dubakov, is to present this as simple as possible with clear use cases, which sets Fibery apart from any other system. Once the character and archetypal meaning of Fibery is clear, stick to that and remove features that don’t directly support that.
Sorry for the very late reply here! This is no longer relevant and probably just noise to reply to but… I hate loose ends. I have not been able to keep up on the forums here as much as I’d like, so I just caught up on the surprisingly rich discussion beginning here:
And it essentially covers and addresses all of the concerns I had, which evidently others shared as well. Since Fibery seems to have pivoted again more recently, like I said it’s all not really relevant anymore, but more importantly my fears about specialization were not actually part of what the team was doing. I would just say then, for any future such messaging/marketing/positioning experiments and updates, that finding the balance of communicating a given focus while pointing to and reiterating the underlying flexibility and the long-term vision will be key. In this case it seems several people were confused and concerned by the Product Feedback focus and some related feature rollouts framed as being oriented toward that market. It could happen again in the future and avoiding that with good messaging will help retain existing customers and get new ones IMHO.
Hopefully this has not been a totally useless notification for anyone watching the topic.