Beyond the Backlash: Clarifying Misconceptions About PKM

Navigate the PKM debate and find the right approach for you. This guide addresses common concerns and offers practical strategies for success.

Beyond the Backlash: Clarifying Misconceptions About PKM

In the Personal Knowledge Management (PKM) community, we're clearly experiencing a backlash.

There's a lot of critique and mocking of people who engaged in building their rather sophisticated PKM system.

This meme probably started it all.

Sam Matla's video was the next notable artifact.

Sam claims that for most people, time spent working on PKM system is a form of procrastination – something that interferes with the real work.

And, of course, there is also the recent Casey Newton's article.

Casey shares his experience and frustration with note-taking as a practice that is supposed to make people smart.

Sam and Casey look at the subject from different perspectives:

  • Sam from a productivity point of view.
  • Casey from the "better thinking" point of view.

I must admit that both Casey and Sam have some real spot-on observations.

The problem, though, is that they over-rely on anecdotal evidence and fall victim to WYSIATI & confirmation bias.

What You See is All There Is (WYSIATI) is a cognitive bias described by Daniel Kahneman in Thinking, Fast and Slow. WYSIATI claims that when presented with evidence, especially those that confirm your mental model, people usually do not question what evidence might be missing.

As a result, they give viewers/readers an oversimplified picture, which misses a few of the most critical factors.

Obviously, there's a possibility that both authors might purposely attempt to make their message blunt and more polarizing.

And judging by impressions, they clearly hit the nerve.

In this article, I will try to perform a rather objective analysis of the phenomenon both Casey and Sam touched on.

First, obviously, we need to frame this phenomenon.

Here is my take:

About 10 years ago we experienced the first wave of information overload & FOMO (Fear Of Missing Out). Knowledge workers felt the need to be connected to a never-ending stream of information. As Marshall McLuhan would put it:

Man, the food-gatherer, reappears incongruously as information-gatherer.

The hunt for information went through a massive explosion.

In 2014 Daniel Levitin in his book The Organized Mind wrote:

Just three hundred years ago, someone with a college degree in “science” knew about as much as any expert of the day. Today, someone with a PhD in biology can’t even know all that is known about the nervous system of the squid! Google Scholar reports 30,000 research articles on that topic, with the number increasing exponentially.

Today, the same search shows almost 80,000 results (including citations) for this topic.

And the rise is not only quantitative, it is qualitative too. The world around us is becoming more and more complex. Today, it is more difficult than ever to make sense of any nuanced subject, whether it is AI alignment or geopolitics.

In 2019, sophisticated tools like Roam, Obsidian, and Logseq were introduced as a part of the solution to this information problem. The fields of Tools for Thought and PKM promised us clarity, peace of mind, new insights, and enhanced thinking.

And it didn't stop there. Last year, we got Tana, which is even more advanced, and probably the most sophisticated and capable PKM system ever.

But there is a catch to it. All these tools have a learning curve, and to bring value, they require a substantial amount of effort to set up and maintain.

Some people (like myself) benefit a lot from Tools for Thought.

Yet, not all people feel this way.

Many people tried these tools, spent some time, and got burned out or demotivated.

Some people formed the expectation that if they do basic stuff (collect bookmarks & highlights, write something, make backlinks, etc) the tool will do the rest of the work. It will make them smarter and more productive.

This is consistent with the sentiment of Sam's video and Casey's article.

So this is the framing.

It raises a particular set of questions:

  • Is building and maintaining your PKM system worth the effort?
  • Can you really benefit from it?
  • Should you be more cautious before investing time and effort into PKM?
  • Should you aim for simpler solutions like Apple Notes?
  • Or should you go "whatever works" like Stephan Ango proposed?

Obviously, I won't be able to answer all these questions in this short article.

Yet I will prioritize and cover 3 important factors that should not be missed here. Also I propose a few hypotheses along the way.

Factor 1. Complexity of the Work

Sam's video contains some rather controversial judgments:

Personal knowledge management is not work.
Research is not work.

According to Sam: PKM and Research are at best an aid to work.

And at worst, a form of procrastination.

Sam frames doing research, thinking, taking notes, and optimizing the knowledge system as a way to be distracted from something he calls "real work."

This is probably the most problematic generalization in Sam's video: one person telling thousands of different people what they should regard as their work and what they should not. To prove his point Sam cherry picking anecdotal cases that confirm his statement.

I got an impression that Sam has a very narrow understanding of knowledge work, disregarding professions & occupations such as:

  • Researcher
  • Academic
  • Consultant
  • Analyst
  • Writer
  • Journalist
  • Professor
  • Creator
  • Lawyer

For many of those professionals, working with complex information, doing research IS THEIR WORK.

And a PKM system can be a centerpiece of this work.

But of course, not all people work with complex knowledge.

Sam provides an anecdotal case here: How his friend manages his entire business using just a set of messy Google docs.

It's unclear what his argument is trying to establish.

For some businesses, Google Docs is a perfect tool: not all businesses process complex information. Before computers became widespread, many businesses ran, literally, on sheets of paper.

It is important to separate running a business from working with knowledge, because not all businesses heavily rely on knowledge.

Hypothesis 1: The more complex work you do, the more you MIGHT benefit from building and maintaining a sophisticated PKM system (but not necessarily WILL)

Here is an analogy: Tesla creates the most sophisticated factories to produce the most sophisticated cars.

But imagine building a Gigafactory to produce dishwashers, instead of electric cars.

It's probably gonna be an overkill, right?

Yet this doesn't mean that we don't need dishwashers, or that they do not bring value to people.

Same thing with PKM: you benefit the most from a sophisticated system if you’re doing complex knowledge work. Let's say you are an academic researcher on the frontline of a medieval history field or an analyst from a commercial Think Tank who helps large companies make billion dollar decisions.

There's another side of it: enthusiasts, hobbyists, life-long learners. Even if they don't work with complex stuff, they simply enjoy building cool structures and maintain their PKM system.

And sometimes they do it on a very high level.

And vice versa: there are people who are doing exceptionally complex work without any engagement with PKM/Tools for Thought.

This leads us to the second factor:

Factor 2. Psychology of Individuals

Obvious fact: People are wired differently

  • There's no single way to be smart or creative.
  • There's no single right way to produce great results.
  • There's no single right way to manage knowledge.

The tools you use must be aligned with the way you work.

Otherwise, you will probably suffer.

In my opinion, both Sam and Casey make a reasoning mistake here: "If you have not benefited from a tool/practice/method, the problem is the tool"

But the fact is, if you have not benefited from a tool/practice/method, maybe the problem is that that's not the right tool for you.

Now, how can you establish that you're more prone to PKM?

One solution is to use OCEAN/BIG-5.

The Big Five categorizes personalities into five traits: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. Each trait is a spectrum, from low to high. It offers insights into behavior and interpersonal dynamics.

A trait called Conscientiousness highly influences people's tendency to be well-organized.

Conscientious people tend to enjoy structuring information and creating information architectures.

So what Sam called procrastination can be a modus operandi for a person: it is the way their mind functions.

In the same way, there are people who are low on the conscientiousness scale.

They tend to work in more "messy" environments and thrive in chaotic conditions.

Hypothesis 2: Conscientiousness scale might partly explain why Sam's friends, whom he mentioned in a video, are successful without a good structure and PKM system. Same thing I can hypothesize about Newton.

Being lower in conscientiousness scale doesn’t automatically make people worst at what they do (entrepreneurs, writers, journalists). Yet it influences their working style a lot.

BIG-5 can be a pretty useful tool in determining level of structure you might benefit from.

So if your PKM system does not bring you value, you might want to take the BIG-5 test and learn your conscientiousness scale.

Here is the simplified 2 by 2 matrix, that represents 2 factors: Conscientiousness and Complexity of the work. Finding where you are on this "map" might give you an interesting insight about your experience with PKM.

Factor 3. Methods & Models You Use

Casey beautifully illustrates what happens if you do not use any PKM methodologies/frameworks and simply go free-flow with apps.

When I had an interesting conversation with a person, I would add notes to a personal page I had created for them. A few times a week, I would revisit those notes.
I waited for the insights to come.
And waited. And waited.

That's about as reasonable as collecting spare car parts in your garage and waiting for the new car to emerge there spontaneously.

Using complicated tools like Obsidian or Tana without any framework or methodology is, at best, significantly less effective. At worst, it can be damaging to your work and lead to hours wasted, and you end up with a pile of messy pages/nodes with no structure and zero meaning.

When there are no constraints, it's easy to get overwhelmed by too many different information flows and possible structures.

To get the most value out of your PKM system, you need to be committed to learning and implementing a PKM framework/methodology. Sam would probably call it an even more sophisticated form of procrastination, right?

There's another element here: today, PKM is evolving. So, methods are changing.

PKM moves...

FROM: the analog skeuomorphic approach of notes, pages, and zettels.

TOWARDS building a computation-first knowledge environment.

Casey also mentions this by quoting Andy Matuschak:

The goal is not to take notes — the goal is to think effectively. [...] Better questions are 'what practices can help me reliably develop insights over time?' [and] 'how can I shepherd my attention effectively?

There are 3 characteristics of emerging methodologies you need to consider today:

They are computation-first
They give you a way to fully utilize the computation medium (knowledge graph, object-oriented ontologies, LLMs).

They are deliberate
Focused not on note-taking but on the end goal: forming better explanations & understanding, building a better sense of the world.

They are non-linear
They do not employ a linear flow but rather provide a set of models and principles you apply.

In the second Collider podcast with Stian Haklev we discuss how these methods are emerging with higher and higher Tana adoption. The podcast will be out soon.

There are a three emergent PKM methodologies worth considering:


A research project by Rob Haisfield, Joel Chan, and Brendan Langen. Exploring data structures and interfaces that support synthesis and innovation in a decentralized discourse graph.


The word algorithm usually implies linearity, but ALGORITHMS OF THOUGHT can be non-linear as well.

The approach, by Lukas "Cortex Futura" Kawearu, focuses on procedures for thinking through a problem or situation to solve it.


The methodology I'm developing now. It is based on the idea of breaking the domain into atoms using the MECE principle. And then use the structure as a scaffolding to form a better understanding.

That's a Wrap!

Obviously, the 3 factors I proposed are not the only ones that influence your PKM experience:

  • Complexity of your work
  • Your individual traits (like OCEAN/BIG-5)
  • Your motivation to learn techniques & tools

We can think of more: goals, related skills, or the right choice of the tool.

Yet I would argue that these 3 are definitely worth considering if you’re planning to invest time and effort into your PKM system, or if you are trying to assess why your PKM experience hasn't yielded the desired results.


Andrew Altshuler is a researcher turned consultant & educator. He helps people & businesses to transform the chaos of information into an efficient, AI-optimized knowledge system. Recently Andrew launched a course: "Advanced Knowledge Systems in Tana." You can find more about Andrew's work at:

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