We do not yet know what we have not discovered and trying to know the unknowable (prophesy) leads to pessimism. A Malthusian catastrophe ends up being wrong because it does not predict knowledge that resulted in efficiency of food production. Similarly the pessimism of energy economics is error laden because it can not predict what new discoveries we will make in social and political systems or new defenses.

Why does prophesy lead to pessimism? Trying to make a prediction based on knowledge bounded by what is currently known, then extrapolating, will result in plenty of examples to be pessimistic about. The problem with these kinds of predictions is that it’s based on unknown knowledge which can change the course of things entirely.

See also:

• Trends are not explanations and trends are prophecies if they involve the prediction of knowledge
• Techno-optimism is rational
• The Beginning of Infinity
• Artificial intelligence garners intense fear and pessimism

A good churn rate for a B2B company serving small and medium businesses (SMB) and mid-market businesses (< 1000 employees) is 2.5% - 5.0% per month. A great churn rate is less than 1.5% per month.

A good churn rate for B2B company serving enterprise customers (1000+ employees) is 1-2% per month. A great churn rate is less than 0.5% per month.

Read What is good monthly churn from Lenny Rachitsky.

You can spot bad explanations similar to the way you can spot bad arguments using the Münchhausen trilemma.

For example:

• An argument such as “we are in a simulation” which requires proof of “who wrote the simulation” infinitely regresses making it a bad explanation
• An argument like “everything was designed by god in 7 days” is a bad explanation because it’s dogmatic and easy to vary. “Intelligent design” can be varied to match any prediction or evidence without further proof other than “because”

All problems are soluble with the right knowledge. That doesn’t mean we know the solution already, but that the pursuit of good explanations will lead to progress towards one. It also doesn’t mean that all problems are solvable—there exists undecidable problems too (like a mathematical proof that proves something is undecidable) but even that provides something soluble (the absence of a solution) and new knowledge can be created (what if this undecidable theorem were true?).

See also:

• Matter, energy, and evidence are all that’s needed for knowledge creation and therefore solving problems
• From the The Beginning of Infinity

The essence of problems is when two ideas come into conflict with each other. Sometimes that’s the conflict between an explanation and a better explanation. Other times it’s the conflict between the current state of being and what you want. Without conflict, there is no problem.

See also:

• From The Beginning of Infinity
• Problems are soluble

There’s a Finnish saying that the “dogs are barking but the train keeps going” meaning that people will always be talking about you but it doesn’t matter. There will always be haters and naysayers but they can’t do anything to you—the train does not consider anything else on its path.

See also:

• The man in the arena

Knowledge and technology go hand-in-hand but they should not be confused for each other. Technology is just one expression of knowledge. For example, lithium ion batteries are the culmination of knowledge spanning chemistry, physics, and geology—batteries are not the knowledge itself.

This is an important distinction because arguing against technology (e.g. techno-pessimism) often means arguing against the premise that new knowledge can be created (and therefore better technology).

Techno-optimists believe technology can solve the world’s most pressing problems. With the right knowledge, we can find solutions to climate change like abundant clean energy. Can we acquire the knowledge to build nuclear fusion reactors? Can we do it in time?

The Beginning of Infinity lays out a detailed argument about why we should be optimistic that we can. We’re already in the habit of transforming inhospitable environments into support systems (we wouldn’t survive a winter day in New York otherwise). We have a way of building knowledge that is error correcting and can build on itself generation after generation. In the fullness of time, all knowledge is attainable and can therefore be transformed into technology used to solve problems.

Techno-pessimism is a parochial error. One must take the position that we lack the ability to make technological solutions to climate change or that it’s not possible in time. The only solution is to limit what we collectively do (e.g. austerity measures and degrowth) but that requires a great deal of optimism that people will work together on an extremely unpopular premise (loss aversion).

There are many instances where technology (and technologists) went wrong—Facebook ruined democracy, nuclear power disasters, weapons, so on. But using this as a reason against techno-optimism is also a parochial error because it presumes that we won’t acquire the knowledge to solve these problems (technology is an expression of knowledge, not knowledge itself).

See also:

• More generally speaking, defaulting to optimism is rational
• Degrowth and austerity is a form of cynicism that things will stay the same
• I don’t agree with their views often, but some inspiration drawn from this tweet by Sam Altman

It can be difficult to empathize with others without direct experience. Those who are not sensitive to noise and are good at ignoring others are seldom aware of their own noise and nuisance.

If you’ve never noticed an annoying neighbor before (especially while in tight living quarters), it’s likely that you are the annoying neighbor.

As products and services become commoditized, distribution and companies that help distribution become more important. Marketing and branding is one way to grow, but finding channel partners that already have a relationship with the target market is more effective.

I suspect that’s why sources of revenue for mature companies shifts to channel partnerships over time and why platforms like Shopify (platform close relationships with businesses) and Stripe (platform that helps others distribute a capability) are growing so quickly.

See also:

• In 7 Powers parlance, platforms for distribution are a combination of economies of scale (they can reach more per dollar than marketing directly) and process power (a product or service that builds ongoing relationships)

The user is complaining that our boat is leaking through the windows, it’s unstable, and too slow. Sometimes you have to remember that some users will never be happy with your product because they decided to take an airplane into the water.

I heard this indirectly from Geoff Belknap.

See also:

• Choose boring technology, but don’t expect a good tool to work in every situation
• Product debt and tech debt happens when you try to make people happier using your plane as a boat

In a thought experiment from The Beginning of Infinity, the author introduces a universe traveling device. During a set interval, you hold the button you go from universe 1 to universe 2 for one minute then on to universe 3 for 30 seconds and so on until you release it and are taken back to universe 1. By the time two minutes is up, you will have traversed the infinite set of universes. If the instrument could take readings along the way, you have a way to measure infinity.

See also:

• If the universe is not infinite maybe this works because of non-trivial topology
• Using such a device you could jump to universality instantly because you could collect all information instantaneously

The Turing-test is rooted in the idea that a human can judge whether something is an Artificial Intelligence merely by the behaviors it exhibits during the test. In reality, a judgment of whether or not it’s a genuine AI requires an explanation of how it works.

Taking the position that the Turing-test is accurate assumes that, given enough responses to fool a human judge, knowledge was automatically created. It’s more likely that no knowledge was created at all and a passing Turing-test is the manifestation of existing knowledge—that of the developer that programmed it. Determining if AI is genuine is to separate it from the developer which a Turing-test can’t do.

See also:

• Human intelligence is a special case of artificial intelligence but we lack the knowledge of how consciousness and creativity works which is why we can not produce AI.
• Computers are universal objects and simulators so if we had the right knowledge, we should be able to make the jump to universality.
• The Beginning of Infinity

Many people don’t find compliance to be a particularly interesting area to work on. For some, it’s an incredibly rewarding experience to take a bureaucratic nightmare and make it simple for anyone. Working on compliance products is like reading Kafka but you get to fix it.

See also:

• The most effective people care a lot
• It requires a great deal of optimism to take on these problems

The jump to universality has two phases. Before universality, one needs to create specialized objects. For example, Roman numerals would need to add a new symbol to raise the maximum value or adding a pictogram to a language to represent a new word. After universality, one need only customize or configure a universal object. For example, printing a different book on a movable type printing press, sending an email to someone new, or inventing a new word with the same alphabet.

See also:

• The Beginning of Infinity

Computers can be programmed to do anything a model of computation can express. You don’t need to buy a new computer to run Microsoft Word and buy another computer to run Slack. The jump to universality in computers opened up an infinite set of possibilities via software.

See also:

• Programming languages are also “universal objects” capable of representing any program if they are Turing complete. Even though they are just abstractions over a physical process that happens on a computer chip, abstractions are real.

Given the choice between taking responsibility for lack of success in a given arena and blaming others for keeping you down, many will choose to blame others. There is comfort in a narrative that it’s not you, but some external conspiracy to keep you from what you were entitled to.

See also:

• Twitter thread about how Stripe and YC are mafia bosses became a big viral meme
• A narcissistic tendency is to blame others rather than take responsibility
• Another example that the easiest person to fool is yourself

In 2021, 5.4 million applications for new businesses were filed. This rise in entrepreneurial activity coincides with the Great Resignation and the COVID-19 global pandemic where people are re-evaluating their relationship with work.

See also:

• Growing startups are a microcosm of an economy, their successes and failures will be a good indication of how the future economy will perform
• With so many new businesses getting off the ground, selling to startups has never been better

A common pattern for launching products and companies is to start with an invite-only beta. There will be users that sign up that are a better fit or have a more burning need for your product. Giving them a way to skip the line can help you filter for the right kind of user and take advantage of their current attention. For example, “reply to this email if you need to do {important indicator of demand} right away and we’ll bump you up the list”.

The reductionist view of science is that all high-level behavior consists of the underlying lower-level behavior and should be analyzed into components to fully understand. However, good explanations can be self-contained and sufficient without needing an explanation of every low-level detail. For example, you can have a theory of how water boils that doesn’t need to predict movement of individual atoms.

See also:

• Rejecting explanations because they do not explain the lowest-level behavior is like the inverse of parochial errors, going so deep that nothing can be explained
• Multiple explanations at different levels of emergence is not inconsistent and abstractions are real
• The Beginning of Infinity

A reductionist argument against an explanation might be that it is incorrect because there are multiple explanations of the same phenomena. If good explanations are hard to vary, how could there be multiple explanations? This argument doesn’t take into account that multiple explanations can exist at different levels of emergence and this is not altogether inconsistent.

See also:

• The Beginning of Infinity

The real world and it’s behaviors are extraordinarily complex. To theorize and create good explanations necessarily requires some encapsulation of ideas through abstractions. It is possible to understand a phenomena by understanding abstractions and similarly, it is possible to create new explanations by building on top of them.

Knowledge can grow because abstractions are real. It’s not as if every child going to school must learn all underlying knowledge in order to add to it. It’s also not as if explanations are implicitly wrong if all the lower-level behavior is not explained first.

See also:

• Seeking good explanations is error correcting so if abstractions end up being wrong, better ones can be found
• The Beginning of Infinity

The selloff and resulting crash in cryptocurrency prices on Jan 21, 2022, which wiped out over $1 trillion from the major coins, showed that cryptocurrency behaves like any other risky asset in the market. The plummet coincided with a stock market decline, nullifying the point that cryptocurrency is some sort of bastion from traditional markets.

See also:

• Stocks tend to go down when bond yields go up as risk-averse investors can get safer returns
• This cryptocurrency decline could get worse with looming federal funds rate hikes

Economists and financial analysts often assume high interest rates are associated with tight monetary conditions and, conversely, low interest rates are associated with easy money. In reality they indicate the opposite because of the supply side of credit.

For example, with low interest rates, there needs to be willing providers (banks providing loans), but low interest rates implies low returns. That’s why there is a positive correlation between interest rates and actual credit issued—there is greater supply when interest rates go up because of better returns.

Milton Friedman’s interest rate fallacy says that lower interest rates are indicative of “tightening money” rather than “easy money”.

Read Milton Friedman’s Interest Rate Fallacy in Monetary Mechanics.

See also:

• Lowering the federal funds rate causes all asset classes increase in value
• The stock market boom during the pandemic is due to increased savings
• Nobody grades an economist