After spending the past few years in Notion to which I was thoroughly committed, I’ve started to look around at other spatial note-taking tools in an effort to move to a more fluid knowledge development system that facilitates deeper synthesis and allows me to capture and process knowledge in the flow of my work. One of the challenges with Notion is deciding what it is I’m writing and where it should go at the outset.

Whilst that sounds like a strange problem the reality is, when I’m working on a project and come across new research insights or maybe a new article sparks a provocative question in me that doesn’t relate to any particular project (let alone what I’m working on in that moment), I’m not sure where to file it. By the time I’ve worked out which Notion database it should go into (whilst also questioning whether I’ll ever find it again) I’m wondering if it worth capturing and many times by this point I’ve lost the thought and most definitely lost my flow of work. The context switching was killing me. It’s often when I’m researching something else and my mind is wandering that I come across little nuggets or find that ideas emerge without a home.

It’s not until I’ve gotten deeper into really understanding not just what’s possible in terms of a personal knowledge development and research workflow, but how my brain works specifically with said workflow . . that I started to realise I need more. Like the design of any system, I started to map out the most important parts of the process in my mind. It is by no means complete or even close to perfect, but it’s what I have thus far.

I was intrigued by tools like Obsidian, Capacities and Tana which enabled more visible connections from one knowledge piece to another more easily. I’ve been trialling Tana for only a week or so now, and so far am enjoying the process.

I initially started out with a preconfigured Tana tagging system based on the Atomic note taking theory. In fact, a paragraph in this article by the mindful teacher really stood out for me . . .

Spotting Patterns

After following this process for a while, you will inevitably see common themes emerging in your notes. It might be the fact you’re not getting enough done because you keep waking up too late. You might keep noticing an idea from that book you’ve been reading occurring in different areas of your life. This is all the perfect stuff for you to be writing about in your notes.

Things start to get interesting now.

If you see any kind of recurring theme, there’s a high chance that there’s some kind of overarching principle at play — one that can be used to your benefit in the future.

The Mindful Teacher

So I started my Tana journey utilising the SN(A)CK System which unifies Sources, Notes, (Atomic) Creation, and Knowledge in one setup. The base was configured by a Norwegian economics student Theo Køppen founded on Niklas Luhmann’s Zettelkasten framework. Theo’s framework provided a terrific start in understanding the way you can create tags and super tags within the Tana framework and I’ve started to customise it to see how I can supercharge the discovery and resurfacing of knowledge connections in a bid to make the knowledge I collect more useful, as well as creating the opportunity for more serendipitous connecting of dots.

The biggest shift in exploring Tana was shifting the way I thought about knowledge blocks. Tana employs a hierarchical structure of bullet points and every piece of information you input is called a node. The real super power of Tana comes in the form of supertags. Tana supertags which basically allow you to add in meta data for each tag that creates context and links between different types of knowledge nodes. The best way to think about supertags is to define them as ‘something that is an X’. The ‘X’ is the supertag. You set up parent supertags and then child supertags under them which inherit their content and are thus searchable individually or as a complete category.

You can see below 👇 the Tana supertags I’ve set up for each knowledge node within the tagging system.

My Tana Supertag Structure

• something that is a SOURCE (with multiple child tags like book, article)
  And with something like sources, I can indicate at the point of inputting the source whether or not it’s a primary source which helps a lot later when I’m going back to dive deeper or cross-check information.

  
  

• something that is a KNOWLEDGE node (with child tags like area, topic, concept, framework, mental model)

  
  

• something that is an original created FUTURES OUTPUT (with child tags like research project, content outline, new signal, emerging trend or force of change).

  
  

• something that is a NOTE (adjusting Theo’s framework — this could be an original thoughtstarter, an atomic note)

  
  

• something that is EVIDENCE (with child tags like data point, outlier POV)

Tana’s supertags basically allow you to configure the default information you want to capture for each type of node. Plus I can configure the default things I’d like to capture for a source, and then I can add an additional tag for the source > child tag ‘book’ such as quote and author.

Below is an example of the first draft of my knowledge and research tagging structure; it’s by no means a final workflow, more than likely the first draft of many, but it’s a starting point to see how each knowledge ‘node’ as Tana calls it, is interrelated to each other and what a more useful and output-focused knowledge development workflow might look like 👇

Futures Research Tagging System

You can see an example of my #source supertag below. You can also see that I can relate it to other knowledge or original content I’ve created (whether that’s a piece of actual content or just a research question or a signal I’m tracking). You don’t have to fill in everything every time but one thing I have noticed, is that the more I devote some time to processed the knowledge I’m capturing — the more it’s useful. If I can’t be bothered processing a certain piece of knowledge or something I’ve captured, then I review whether or not it’s worth keeping in Tana. This whole process by the way is pretty quick (especially with Tana’s built in AI capability which I’ll come to later) so it’s not as much heavy lifting as it sounds.

Tana Supertag Parent Category > Research Sources

@Cortex Futura has a series of great articles and videos on the Tana system on their website that were also incredibly helpful in these early stages.

Tana Supertag Parent Category > Futures Research Content

You can see below that just like the ‘sources’ tag structure, my ‘futures content’ creation tagging structure (which refers to primary content that I am developing myself not content I find) also has a similar structure 👇

And under that parent tag of ‘futures content’, I also have child tags for:

• futures content > futures research project

• futures content > futures research questions

• futures content > futures content outline

• futures content > futures provocation note

• futures content > futures trend note

• futures content > futures force of change

• futures content > futures weak signal

Then when you dig into a child such as futures weak signal, there are some additional tags that help to identify those nodes 👇

Again remember I’m not filling this out all the time every time, but am I devoting some intentional time to processing research sources, thoughtstarter ideas or (research) or (provocative) questions that emerged out of context in the flow of other work. Regularly.

And the more you input into your system, Tana’s AI can help you to fill in some of the gaps. Often Tana’s AI is not super accurate in this context yet, but sometimes it’s helpful in starting off my thinking and the more information you already have — the more likely it is to suggest relates nodes that should be connected to the new node you’re inputting.

I’ve altered it pretty significantly to match my own futures research needs but the framework works along the same lines. If you’re starting out in Tana there are a load of terrific pre-configured frameworks or Tana templates which give you a good head start in finding your way around the system.

It’s still early days but so far I’ve been pretty impressed; especially with the native AI plugin which has opened up a world of functionality. After all, a lot of what I’m doing is research and the AI’s ability to atleast suggest a bunch of topics, keywords or research sources has proven to be a good start in starting to map a new domain without much prior knowledge. More on that later.

Maps of Content (MOC)

My only disappointments thus far are the lack of visual knowledge graphs, not a biggie but I’m a visual person so it was kind of disappointing. It’s the drawcard for many who like the idea of tools like Obsidian or Capacities.io which in particular has a beautiful interface . . . the plugins are limited to in terms of inputting sources — Feedly, Readwise, some of the early users have hacked connections together but it’s not as easy as other systems.

I haven’t used Capacities.io much but plan to dive into the that and see what they offer too. Still, the AI knowledge and research workflow in Tana is so unexpectedly good that it would be hard to walk away from that I think.