Although we try to avoid over-intellectualizing, some terms and concepts might be difficult to intuit at first glance. We invite you to click on the links for further reading. 

Skeptical Empiricism

To believe in the ethos of DeFi, is to believe in a completely open, trustless, and permissionless economy. This inherently presupposes a methodical view on all systems of power, money and governance, through the eyes of the skeptical empiricist. One who analyzes data and questions the very logic behind the ways in which it should be interpreted.

Amazing as the new paradigm gets, Web3 has not resolved the crippling challenges social technologies exacerbate. Instant gratification, sensationalism, misinformation and populism have plagued the internet since mass adoption of social media. Unfortunately, yet unsurprisingly, DeFi is far from immune to these viruses. The infrastructure for ideas on the web is still catered to popularity contests and it seems unlikely that will change anytime soon. The Googles, Facebooks and Twitters of the world are collecting profits en masse, which will sustain the roadblocks to nuance and depth in conversation. The skeptical empiricist is withering away, as the systemic slow-bleed of logic keeps leaking at an exponential pace, due to unevenly distributed information and tribalism.

The Monster of Clout

In the world of apes, degens and shills, there are innumerable opportunities for groups of people who’ve already “made it” to gain massive amounts of clout. 

For some, this clout is akin to being pegged to the number of followers’ wallet addresses they manipulate, with each new follower bringing in a new wave of exit liquidity. On the other hand, there are plenty of morally inclined actors in the space with great intentions who provide innumerable amounts of alpha. Sadly it seems the line between both remains blurred. This begs the question: who’s to trust?

Of course, DeFi is composed of brilliant developers, VCs and traders. Many are personal idols of mine. I admire them wholeheartedly. 

On the other hand, here\’s the harsh reality for the Full Fledged Fool who’s expecting to get spoon-fed: although there is a wealth of knowledge and alpha in the space, there are endless sneakish opportunities for anyone to get taken advantage of. Available alpha does not matter to you if you can’t distinguish it from bullshit. The concept of self-sovereignty should extend to the mind and in decentralized systems, your thoughts, opinions and investment decisions must be your own.


Starting now, we leave cults of personalities at the door. 

We have to stop and consider the following: your favorite trader probably won’t be tweeting out his catastrophic losses, this influencer’s farming strategy might be pure luck and luck runs out, that dev team probably did not just create “The Next God protocol”, VCs are net long and that bias potentially transfers over to most of their takes…and there’s a good chance most of them are dumping on you.


That being said, I believe in ‘DYOR’ but also recognize the lack of information on the metagame of learning in DeFi. How exactly should one go about doing his own research when DeFi consists of an amalgamation of economics, finance, culture, philosophy, social psychology, engineering, computing, memes…etc.?

We should lay a solid framework for thought, process and reflection to answer this question. Humans, unlike smart contracts, possess emotions that affect their judgment (affective judgments); which can, logically represent the main failure point in making sound, utility-maximizing decisions. It’s what makes us humans.

This is the main critique of what some people call the pseudo-science of economics. Revealing one of the founding problems smart contracts look to solve: How can we eliminate human subjectivity/error as much as possible?


This guide is intended to serve as a general mental exercise for researching investment opportunities.

Strategies and edges are widely contended in the space, which can be overwhelming for newcomers. For those who cannot afford to blow up their investment account: appropriating some sort of mental model before stepping into the dragon’s den of DeFi markets, Metamask-A-Blazin’ is mandatory.

This guide assumes the reader is like the majority of  users in this space; they are looking for a certain edge to act on and grow their wealth over time. This mental model can translate into action through trading, investing and yield-farming strategies. However, each of those activities deserves more introspection and further conceptual development that we will explore in future articles.


I argue the following to compose sure-footing: In the presence of emotional triggers such as gud coin go up and bad man do rug, we rarely make decisions based on the content of the information presented.

Because of the subjectivity of emotions and the absence of predictability that ensues, it seems fair to deduce the randomness present in economics, finance and most of all DeFi to be compounded and underestimated. These are complex systems programmed, managed and used by humans with innumerable layers of risk, and thus inherit human flaws both known and unknown.


How do we navigate this statement knowing that the subjectivity of human flaws can morph and move the “anchoring points” of models, using empirical data to fit different narratives of the divergent communities of DeFi?

Well, it’s hard. Very hard…but I’m not defeated. It’s understandably daunting to play the game when we discover that the rules constantly change and the players are always getting better. However, it’s not ALL random. There are links between metrics and logic that can be measured in effective ways and strategies that can dampen volatility and deliver high returns. You can achieve success by leveraging asymmetric bets in your favor.

I propose two frameworks of thinking to achieve our goal: an internal framework for the mind to keep our humanity in check and an external framework to apply on the subject matter we want to learn. The first requires to look inward and build an iron-clad logical mindset. The second looks to break-down systems, approaching them from different levels of complexity.

Is thorough introspection and systematic analysis overkill? We’ve all heard the countless stories of rags to riches from the classes of 2013 and 2017. Do we really need to do this much work to “make it”? Who knows…but you won’t get the answer to that question until after the opportunity has already passed. The age of throwing a dart at a list of projects and finding a ten-bagger is closing at a rapid pace. As a market matures, so do its participants. Institutions have entered the space and are slowly diluting the retail investor’s edge. Crypto as a whole is growing at an exponential pace and has democratized the access to financial instruments. Are we really going to rely on luck to decide our fate?

Building Our Kingdom Of Logic


We can’t negate the power of our own psychology in markets and decision-making based systems and that’s where we build the King’s Fortress, The Noble House. The even-keeled observer of oneself tends to build the strongest foundation for his fortress, on the basis of understanding his own limitations. What are our strengths? Why are we in crypto? Are we trying to play the game of DeFi passively or looking to step into the cupboard and travel to Narnia? Self-awareness & self-control are represented by the noblehouse of our kingdom and represent its nucleus. Our observations, experiments and strategies are all at the mercy of our will to operate our nucleus effectively.

Information filter

The walls of our kingdom represent the information filter that protects us from the thousands of daily, supposed alpha leaks that fog the brain and drown our thoughts in noise. There is such a thing as an overflow of alpha. After all, no one has infinite amounts of capital and brain bandwidth to deploy. Information for the sake of it, without knowing how to evaluate it and assimilate it, will simply exhaust your judgment and leave you vulnerable to making foolish decisions.

Theory testing

The farmlands are where we create our little science experiments and test our theories and observations by playing the different games of DeFi with a scientist’s mind. Observing new data, testing out new processes and recording the outcomes.


Each part of the kingdom relies on the health of the other. The Noble House understands its responsibilities to its fief and dictates the general direction of our kingdom. It can assess if our walls need fortification and can evaluate the state of our farmlands. We keep our farmlands outside of the walls, because we must, above all else, protect our nucleus and remain impartial when assessing crops and new strategies that will potentially help feed our kingdom. Our Noble House will lower the drawbridge to humble farmers and truce seekers, represented by sustainable alpha and data, free of hidden incentives or misinterpretation.


Noble House Construction

Daniel Kahneman, one of the founding fathers of behavioral economics, developed theories around utility which lead us to infer that cognitive biases and heuristics compose about ~95% of our decisions (reinforcing the affective judgments proposal of earlier). With this in mind, we can come to some form of consensus: it’s preposterous to consider social science laws to be absolute when they not only rely on human input but are also functions composed of human-dependent variables.

Kahneman describes the heuristically-intensive side of the brain as lazy. We look for shortcuts to make sense of the world and process information. It\’s imperative to build a self-reflective practice that allows us to think deeply about our decision-making

Self-awareness is hard-work because it leaves us vulnerable to our harshest critic, ourselves. Generally, humans hate being wrong. Interestingly enough though, the most successful investors and traders will generally say they feel the most confident in an investment or strategy when they completely pivot on a thesis, after realizing they were wrong. Society is engineered to reward being right. Unfortunately, in markets and in the face of randomness, there is no absolute truth. The game is ever-changing and so the goal is to be as close to the truth as possible– not to find the absolute truth. Because it doesn’t exist! Do you want to be right or do you want to make money?

An investment or trading strategy is a probabilistic theory and we need to be constantly looking to disprove it. It is extremely dangerous to contemplate HODLing or diamond handing any asset as a serious investment thesis because it implicitly disregards the possibility of our thesis being wrong.

Our conviction levels should be strong to invest into something but we should beware marrying our bags and preachers of such. This attitude will help tremendously in taking profits or cutting losers.


Fortifying the Walls

‍Fortifying the walls of your Kingdom of Logic should exemplify your ability to disprove theories. The scientific method is literally making observations, formulating a theory and attempting to disprove it until we have exhausted the potential invalidating points. Only then, will a theory be taken seriously.

With his work on epidemiology, David Hume, the father of Skeptical Empiricism introduced us to the problem of induction. That is, to make a general, ampliative inference from multiple self-reinforcing events.


John Stuart Mill popularized this with his work on the black swan problem: “No amount of observations of white swans can allow the inference that all swans are white, but the observation of a single black swan is sufficient to refute that conclusion.”

In Fooled by Randomness, Nassim Nicholas Taleb raises the black swan problem and introduces us to the power of outliers, and more importantly: their statistical relevance. If the one black swan appears, then we know for certain that all swans are not white. That is, 100% chance of the same outcome being recorded across all alternative outcomes. The word certainty implies a deterministic model of thinking.

Practically, investing and trading cannot be done deterministically. As a matter of fact, in most complex environments, with lots of variables and dependencies, it would be a fallacy to work with deterministic models. Even in high-level physics, models are composed of approximations and involve almost only probabilities. Although simulations of a rocket launch might approximate success in practically every outcome, there is never 100% certainty the rocket will perform as intended.

When DYOR, the number of positive, self-reinforcing points you can drum up does not matter. Invalidations are key. You should continuously look to evaluate pieces of information through deductive reasoning, searching for invalidations. If the theory can not be disproven, it is a strong theory.

The popularized twitter threads we are all guilty of relishing will often lay out all of the positive aspects of a crypto project and seldom contain invalidations to look out for. Reading those makes it extremely easy to fall victim to self-reinforcing biases.. We are human and all guilty of feeling some sort of exhilaration when someone else is reaffirming our own beliefs.

Contradictorily, some self-reinforcing theses propagate through enough market participants that they end up happening. This is the notion of reflexivity, popularized by one of the most successful traders of all-time: George Soros. Add in the network effects of memes and technology adoption and being on the wrong side of the trade of a reflexive asset could cost you dearly.

Misinformation or illogical assumptions can take lives of their own and you should acknowledge them if you can demonstrate their relevance **but in order for you to even make those observations, you need to build the intuition to recognize fallacies.

Farmland Innovations


History repeats itself. We rarely learn from our past mistakes, even less so those of other people. It’s not until you burn your hand on the stove that you recognize the danger it brings.

We could have a seemingly great idea that’s predicated from an investment strategy we’ve heard of but for most of us, it’s only by putting it to the test ourselves, that we can conclude if it’s of any value to us. If our goal is to become self-sovereign thinkers, having skin in the game is imperative.

Assume you hear about someone else’s investment where they decide to use “x” strategy because of “a, b, and c” variables and they obtain “y” positive result. “y” has the power to make you believe “a, b and c” are All-Truths.

You have been reading about the same “x” strategy before that person even made their investment and this gives it the necessary weight you need to go ahead and try it out for yourself. Keyword here is try. You end up putting in ~0.5-1% of your portfolio and lose it all because Tommy-Trades-A-Lot forgot about the “d” variable that invalidates the a, b and c variables. Realizing Tommy was a lucky Fool, you’ve just gained an Experience Point and that grew your skill set. If you repeat the same process over time, your logical skills will allow for way better odds than the Tommys of the world.

How do you evaluate skill versus luck in probability? Evaluate the power of alternative outcomes. To paraphrase Taleb again: if you have 9/10 chances of making $1 and 1/10 chances of losing $10k; the payout structure is ((9/10) x $1) – ((1/10) x $10k), which ends up being a negatively skewed payout structure of $-9.001.

Although you have a 90% chance of making money, the result of that 10%, makes that over time, those seemingly great odds will lead you to bankruptcy.

Now that we’ve built our mindset through our Kingdom of Logic, we need to figure out what to learn and how to do it, climb the informational totem pole.

Four Levels of Systematic Thinking


One thing is for certain, information asymmetry is real, even in DeFi.

Seasoned developers have an innate understanding of the mechanics of protocols, VC and prop traders can leverage their years of experience in other markets and institutions have teams of PhD’s combing through every nook and cranny of the space to find any leftover edge.

What do these groups have in common? Skilled human capital, specialized in particular tasks.

If you have limited experience trading, investing and programming, you have better odds at developing a competitive edge by concentrating your learning efforts where your strengths lie, so you can move up the knowledge curve quickly.

Personally, I like to breakdown a learning subject by treating it like a game you’d want to master: 


The Serf

This is where you’re learning the rules of the game you want to specialize in. Broadly defining different ecosystems, participants, concepts:

  • What is an LP?
  • What is impermanent loss?
  • What is dilution?
  • What is volatility?

The Knight

This is where you’re learning how-to-play the game according to the rules. Broadly approaching DeFi relationships between dependent variables without abstracting at all:

  • Why is there a correlation between impermanent loss and volatility?
  • Why does dilution occur in LPs when the price of underlying assets go up?

The Lord

This is where you discover the Meta of Defi. Learning about hidden subgames within the game and where the rules are hidden and constantly change. Taking into consideration more complex dependencies and abstracting more. Thinking dynamically. The introduction to understanding the effects of the thinking participant.

  • Knowing that supply dynamics and volatility have an influence on impermanent loss and dilution:
  • What set of behaviors would be reflected in liquidity pool X?
  • What set of decisions would liquidity provider Y make?
  • How does the subsequent actions of Y influence X again?
  • Are there any alternative outcomes in behavior for both LP X and actor Y?
  • Would an alternative outcome in X provide a whole new set of alternative outcomes for Y?

The King

This is where you are learning how-to-write your own rulebook (theses) and repeating the preceding process to create a never-ending feedback loop of scrutiny. As King, you develop the know-how to build the most logical methodology that works for you. It’s the application of known or new theories and the methodologies to challenge “the developed consensus” on a subject.

For example: Applying the Theory of Reflexivity to Liquidity Providing Dynamics.

  • If we acknowledge the glaring information asymmetry in DeFi, in addition to general human fallibility, it can be argued that in the face of uncertainty/volatility, reflexivity in asset pricing will extend itself in Liquidity Pool dynamics and impact as well.

Reflexivity in a nutshell:

Price moves → change in perception → price moves more → more changes in perception →(…)

  • How does reflexivity challenge our notions of LP dynamics, impermanent loss, dilution?
  • How does the very nature of the blockchain, the accessibility of information and the architecture of LP smart contracts, challenge the concept of reflexivity?
  • How can we accurately measure the distribution of information in markets? Is it possible?
  • How can we accurately measure the mean amounts of bias, subjectivity and human error for each decision in markets?

If you look back up and down the four levels, you’ll see each level builds upon the previous one’s concepts and broadens. At the very top of the upside-down pyramid, the King presents the widest surface area of knowledge. However, he also presents a greater amount of questions. Being that the top of the knowledge chain is unknown territory, those questions are often the unanswered ones. For the the King to reign over the perils to his Kingdom of Logic, he is self-summoned to the responsibility of mastering the art of asking the right questions.

In the end, it’s up to us to decide how to go about it. Some people like to inundate their brains and try to piece it together as they go, some people like to start small before they go big. In the end, real learning and researching is about asking good questions. Effective DYOR is about developing our ability to constantly ask the right questions.

It takes a King to make a Kingdom of Logic and a Kingdom of Logic to make a King

Having the self-awareness to control our own biases and human flaws, deciphering which information is important and recognizing alpha all start with a logical framework. This framework can be applied practically by testing our knowledge which allows us to keep our work honest, inhibits our arrogance and creates a deeper, richer sense of confidence in our abilities and skill-set.

We are not trying to eliminate our flaws. That is impossible. We are  to find a work around and set a stop-loss on them, through structure and discipline. Your portfolio does not care how it got so fat or skinny; however, it is paramount for you to care if you want to keep feeding it profits sustainably. Find something you like in DeFi that you’re good at and become the best you can be at it.

I encourage anyone that is starting their journey to keep at it. It is hard to be meticulous. I suspect many of the greatest investors of our time often experience the Dunning-Krueger effect more than once. I can personally say throughout the process of writing this guide, I’ve encountered this feeling almost throughout. It’s easy to lay down principles of logic, but to follow them is another story.

I look forward to hearing how you guys go about DYOR! You can reach out in the fool’s guide thread on Discord or ping me on Twitter: @0xToli if you want to talk about anything.

We have, in my opinion, one of, if not the best community in all of DeFi. We want to create a place where we can learn and grow from each other; where all of our community members can become self-sovereign; of the mind and the wallet.

Let’s keep asking the right questions.

Reading list

Some books that have been sourced.

They have personally enlightened me and changed the course of my thinking:

  • The Alchemy of Finance by George Soros
  • Fooled by Randomness by Nassim Nicholas Taleb
  • Thinking Fast and Slow & Noise, A Flaw in Human Judgment by Daniel Kahneman
  • The Intelligent Investor by Ben Graham
  • The Market Wizards series by Jack Schwager

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