At time of writing, the 2024 Bitcoin Halving looms near. The block subsidy will be slashed in half and miners will see a substantial decrease in mining revenue. As margins shrink, miners will feel pressure to reassess their operations. Creative methods will be sought to optimize infrastructure and maintain margins. For some, there will be opportunities to expand in the fallout. The question is, how to accomplish these objectives in the face of constrained resources? The digital Philosopher’s Stone has once again found its allure.

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Formation & Agility

A general leads an army through standardized commands and equipment, but adapting to the enemy and terrain secures victory. Likewise, a profitable miner ought to make use of standardization while also engaging in opportunistic tactics. The trick to surviving and even flourishing after the Halving is to blend the strength of standardization with the flexibility of a programmer in the lab. To better understand this, let us turn to military history for inspiration. In doing so, the reader will also find a framework for understanding the mining strategies and tactics that follow.

Prior to Roman domination, the phalanx was arguably the most powerful military formation in existence. It was the backbone of the Macedonian army, which conquered much of the known world when led by Alexander the Great. The Romans themselves used a phalanx formation in their early conquests before inventing its successor, the manipular legion.

A phalanx consisted of hoplite soldiers equipped with long spears, typically 13 to 23 feet long, and round shields. They were assembled into tight rows that created a wall of shields and spears toward the enemy. This formation enabled multiple rows of men to participate in the front-line conflict. Hoplites in the back could thrust their spears toward the enemy while the front row held the line, shields at the ready. This formation was extremely powerful when opponents were forced to engage head-on. Phalanx contemporary and Greek historian Polybius wrote of them, “...when the phalanx has its characteristic virtue and strength nothing can sustain its frontal attack or withstand the charge…”

However, the phalanx was not without weakness. The sides and rear of the formation were vulnerable since the formation could not adapt quickly. This meant that faster moving light infantry or cavalry could disrupt the enemy phalanx formation, giving their own phalanx the upper hand in their frontal assault. Battles of this time were usually decided by flanking maneuvers. The phalanx was only strong if its formation was maintained.

Then came the Roman manipular legion. It was a hybrid formation that blended the strengths of a phalanx with the versatility and tactics of fast-moving troops. It consisted of groupings of men called “maniples.” Though called the “triple line” formation, there were four lines of men (compared to the phalanx single line) and there were spaces between each maniple. This formation allowed pressed Roman warriors at the front to retreat for support. The retreat would also entice hoplites at the front to give chase, disrupting the phalanx formation.

The first line was composed of velites (“fast men”). They wore light armor and were equipped with javelins that could be used to antagonize the enemy from a distance. If the velites became pressed, they could quickly retreat into spaces between the second line, the hastati (“spearmen”). If the enemy withdrew to reform, the velites and even hastati (who also had javelins) would rush forward in pursuit. Lendon writes of them, “The velites seem to have fought individually as an irregular swarm, without officers or standards of their own…” (Soldiers & Ghosts p. 179). 

If the hastati became pressed, they could similarly fall back between the principes (“first men”). If the enemy hoplites at the front chased after the hastati, they would find themselves separated from their phalanx formation and surrounded on three sides. If this was not enough for the Romans to win the day, the velites, hestati and principes could fall on the triarii (“third men”). 

The triarii were the legion’s most experienced soldiers. They were equipped similarly to the hastati and principes, except that their spears were longer, similar to those of the phalanx. If the enemy did manage to press through the hastati and principes (all the while being antagonized by the velites) then they would suddenly face Rome’s best troops, well rested and equipped to hold a phalanx formation. Lendon writes, “When the triarii finally came into action the Roman legion could aptly be described as a phalanx.” (Soldiers & Ghosts p. 181)

The manipular legion allowed Rome to rise from a fledgling city-state to become the dominant world power of its day. This trajectory was made clear at the battle of Pydna, where Romans engaged the Macedonian phalanx head-on in the flat lands. Lendon writes,

“Despite Roman bravery, ground and equipment favored the Macedonians, and they steadily pushed the Romans back. Finally, the Macedonian’s very success was their undoing. Their advance met more or less resistance at different points, and so some parts of the phalanx pressed forward and some held back. Their progress also took them onto higher and less regular ground which interrupted the exact dressing of their ranks. … As the phalanx came apart the Roman advantage turned into a slaughter. More than twenty thousand Macedonians were slain and only a handful of Romans.” (Soldiers & Ghosts p. 208 & 209)

On flat ground and in true form the phalanx could push back the Roman legions for a time. Once faced with uncertain terrain and disrupted form, the phalanx fell. Let the reader lift this lesson from the pages of history: do not optimize for ideal conditions, learn to thrive in chaos. History has shown there is strength in highly ordered systems, but dependence on order alone during changing circumstances creates great weakness. Just as the Macedonians pushed forward onto uneven ground at the battle of Pydna, some miners are running stock firmware into the Halving.

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ASIC Phalanx vs. ASIC Legion

In times of plenty, an ASIC army is raised by purchasing, building, and deploying infrastructure. Bear markets are a war of attrition. Hash rate clashes against hash rate, until the “enemy” margins are vanquished and they are forced to capitulate. 

Many ASIC armies today operate like the phalanx did. Their “commanders” consider each machine to have one power draw and hash rate. They imagine revenue to be a linear function, changed only by the number of machines online and the tides of hash price. They suppose the “battle” can only be won by fighting for high uptime and low power costs. Of course all farms can benefit from high uptime and low expenses. However, there exist tactical advantages in adopting a manipular strategy. Let’s take a closer look.

As Cathedra has explored the art of the possible, it was discovered that an air-cooled S19J Pro can reach into the 21 J/T (joules per terahash) range without any hardware modifications. Since peak values in the lab rarely manifest in practice, we will leave a buffer and assume an efficiency of 23 J/T under ideal conditions (54ºF or less). Knowing this creates an array of viable configurations for each miner. This flexibility allows us to operate our data centers as a manipular legion.

We first define four “lines” of efficiency that act in a similar way to the four lines of the manipular legion. To the velites, hestati, principes and triarii we assign the efficiency values of 34, 30, 26 and 23 J/T, respectively. As hash price declines, miners can “retreat” to a more profitable efficiency, thereby improving fleet-wide profitability. This flexibility also offers an advantage when hash price is increasing. As the Roman velites could antagonize a retreating phalanx, so too can we chase higher hash prices by up-clocking. Historically, network difficulty has trailed large run-ups in Bitcoin price. The manipular ASIC legion can quickly capitalize on this imbalance.

As with any strategy, there are secondary effects and tradeoffs to be considered. At industrial scale, Bitcoin miners need to be aware of demand charges. Many utilities issue demand charges based on the 15-minute interval of greatest power use during a billing period. If power consumption varies from this peak, the difference becomes the basis for a demand charge in addition to charges for generation and delivery. Since down-clocking ASICs causes them to use less power, an ASIC operator who frequently changes ASIC settings during a billing period may be surprised to find that their effective cost per kilowatt-hour is higher than expected. 

Thus, down-clocking miners connected to the grid can create a counter force in the retreat to better efficiency. Operators in this context should implement down-clocks at the end of a billing period to avoid peak demand charges. Conversely, up-clocks should be enacted at the beginning of a billing period. Otherwise, the preceding month will effectively be billed at a higher rate.

In other scenarios, an operator may have inflexible power purchase agreements or may have leased infrastructure to generate their own power. In this context, simply down-clocking will not be beneficial. Costs will remain unchanged while revenue takes a hit. This scenario calls for a different strategy.

The Testudo

Roman warriors were quite familiar with being pressed in battle, but some situations called for an extreme defensive posture. To assail highly fortified positions under an onslaught of arrows, javelins and rocks, or to simply retreat in desperate situations, maniples needed to minimize losses. For this purpose, the Romans developed the “testudo” formation, which in Latin means “tortoise.” It consisted of legionaries forming close ranks with their fellow soldiers and interlocking their rectangular shields (each called a “scutum”) at regular intervals overhead and on the sides as needed. 

When done properly, the formation resembled its namesake and was quite effective at shielding a maniple from projectiles. Whether in attack or retreat, the formation allowed a Roman legion to develop into an effective fighting position. However, the tight spacing required to make the formation a success impeded mobility.

For a Bitcoin miner, heavy resistance on the “battlefield” means high electricity prices and low hash price. In some situations, as margins are squeezed, down-clocking alone may not be sufficient to remain profitable. In other situations, down-clocking may not even be possible. It is here that we may draw inspiration from the testudo. 

A Tale of Two Sites

Consider the following scenario. Suppose a mining company is evaluating two of its data centers, each with 1,000 S19J Pro miners. The first site is subject to a take-or-pay power purchase agreement (PPA) with a cost of $50/MWh (megawatt hour). The second site is a hosting facility and charges $75/MWh. Both sites are running stock firmware, where each ASIC uses 3,000 watts and produces 100 TH/s. With today’s hash price around $60/PH (petahash), these sites are running at a profit.

Speculating a bit, suppose several months from now the Halving has occurred and hash price plummets to $40/PH. The losses incurred at the hosting facility are now overwhelming profits from the other site by three to one. Naturally, this scenario would inspire one to unceremoniously pull the plug on both hosting agreement and miners in kind. What has not yet been accounted for is the hosting deposit of, let’s say, $330,000. Terminating the hosting contract early would forgo the deposit. Since this represents a greater loss, machines will be left to bleed cash until the hosting contract expires or renewal is met with better conditions.

Back in the present, what can be done to mitigate losses should this bleak scenario come to bear? If these sites were each being operated as an ASIC legion, the triarii would be called upon. Each machine would be down-clocked from 3,000 watts to 1,500 and from 100 TH/s to 65. While this would not be enough to spare the hosting facility from producing a loss at $40 hash price, profits from ASICs running under the PPA are now more than enough for the company to remain cash-flow positive.

In discussing this approach with the hosting facility, suppose the request to alter machine clocks is rejected. The host is concerned with network security and is not incentivized to see reduced revenue due to selling less power. Besides, they have minimum offtake requirements. Looking back, recall that the other site also has a take-or-pay agreement in place. Down-clocking alone will not achieve the intended effect, since costs will not be reduced. The ASIC legion appears to have fallen, forced to operate as a phalanx on uncertain ground. In spite of this bleak outlook, there is a strong path forward.

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ASIC Testudo

The ASIC testudo is fundamentally an infrastructure play, made possible through down-clocking. It can be defined as increasing the number of operating ASICs per megawatt for a given machine type. Just as the Roman legions could succeed in retreat by pressing tightly together and forming the testudo, ASICs can take a similar form. 

Recall that when down-clocking to 23 J/T, power use dropped by half. Now suppose the hosting agreement is up for renewal prior to the Halving. The agreement could be allowed to expire and machines consolidated under the $50/MWh PPA. Since the total power of 2,000 ASICs running at 1,500 watts is the same as 1,000 running at 3,000 watts, the change will not incur any losses from the take-or-pay nature of the PPA. This allows ASICs from both sites to operate with greater efficiency and consolidates them on a lower average power cost. Even more stunning, this new configuration can produce positive cash flow at $30 hash price!

Not so fast. How exactly are all those machines simply going to find available rack space and cables to plug in? Some sites may have physical gaps between miners that can be filled and splitter cables can be used to provide power. If this is not viable to accommodate all the incoming machines, then additional infrastructure must be supplied. Fortunately, collapsing hash price is the perfect time to purchase fire-sale infrastructure. In addition, there will be ready capital to act on this, since the $330,000 hosting deposit will become available upon expiration of the hosting agreement.

Battle Ram

The testudo, while effective in retreat, is intended to develop into a position of strength. The Romans typically used the testudo formation to move troops and siege equipment like the battle-ram closer to a fortified enemy before attacking. Similarly, as mining conditions improve, the testudo could be an excellent strategy for tactical ASIC pre-orders. Machines could arrive before a new site is energized, placed in mobile containers (possibly Rovers), down-clocked, and used to increase profitability on existing sites rather than waiting around in storage. Furthermore, if the new site was designed in anticipation of this strategy, the containers could be transferred to the new site, up-clocked and begin mining quickly; without the delay of unboxing and racking the ASICs. Containerized solutions unlock the full potential of the digital Philosopher's Stone.

There are many strategies and tactics that can be employed with CathedraOS. A complete list of them would be outside the scope of this writing. We look forward to inventing new ones with you and would certainly entertain technical follow-up pieces if the reader has found value in these pages. Happy mining, friends!

To download Cathedra Bitcoin’s after-market firmware, CathedraOS, please visit our website at: cathedra.com/firmware

Isaac Fithian is Cathedra Bitcoin’s Chief Field Operations and Manufacturing Officer.

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The below was originally published as a tweet thread on February 10, 2023 to provide a glimpse into our process. Our thinking has continued to evolve, but as mining conditions deteriorate once more, we believe these lessons are more relevant than ever.

For this analysis, we used a S19J Pro 96T and focused only on underclocking the machine. Different operating environments will produce different results, but we used a water-cooled setup to better control the measurement temperature band. We then corroborated our findings using air-cooled machines in normal operating environments (as you will read below, the ambient temperature can have a large impact on achieved efficiencies). Let us begin.

We tested different voltage/frequency combinations in a grid pattern. In Figure 1, the red circles represent each of the test points, the X-axis is frequency, and the Y-axis is chip voltage. The resulting “heat map” or contours are the achieved efficiency levels, as measured by joules per terahash (J/TH). The dark purple regions mark the highest efficiency (lowest J/TH) and the bright yellow regions mark the lowest efficiency (the highest J/TH). The orange and yellow lines are the interpolated points of highest efficiency for each voltage/frequency combination. The orange line uses the watts measured at the plug (and all power draw from auxiliary systems) as the basis of calculation and the green line is the line of best fit. The contours were calculated using the plug watts.

There are certain pockets where sub-22 J/TH performance has been achieved. Achieving this efficiency is only possible by underclocking machines, reducing the power draw and thereby reducing the hash rate. This drop in hash rate is inevitable; however, the drop in power draw is disproportionately larger, which equates to more efficient utilization of the power being drawn.

Figure 2 below shows the achieved efficiencies at different frequencies (and corresponding maximum efficiency volt setting at each frequency). The X-axis displays various frequencies and the Y-axis shows the achieved J/TH. The purple line is the is the raw results using the power draw measured at the plug plug and the yellow line is using the estimated power draw from the firmware dashboard. The orange and blue lines are the polynomial regressions of the raw data.

A few observations:

• First, the dashboard under-reports the power draw of the machine. On average, the dashboard watts, using the stock power supply unit, is ~5% lower than the measured power across the different voltage/frequency combinations (with some exceptions).

• Second, there is a point of diminishing returns beyond which further decrease in frequency becomes counterproductive (i.e., less efficient).

• Lastly, this particular S19J Pro seems to have certain voltage/frequency combinations it likes better than others. We find pockets of outperformance wherever efficiency falls below the trendline; the machine performs disproportionately better at these settings.  

It is important to capture the nuance of the machine and its capabilities, but there are good general heuristics one can follow to achieve one’s desired result. For example, at a given frequency, there is an expected hash rate that the miner is capable of operating at. The following Figure 3 shows the results of the recorded hash rate/expected hash rate. The X-axis is frequency, Y-axis is voltage, and the contours are the resulting fractions of the recorded hash rate/expected hash rate at a given frequency. The blue line is the highest achieved efficiency line:

Generally, the best performance line follows the channel along the 99% of expected hash rate contour at each frequency. This indicates that there should be enough chip voltage applied so that 99% of the expected hash rate is achieved. Anything above that combination doesn’t yield any notably higher hash rate, but the power draw will continue to increase as chip voltage is changed.

There are a few ways to zero in on how one should operate their machines: namely, deciding which operational variables to prioritize—hash rate, power draw, or efficiency. Ordering those by importance will help develop the right strategy. This all depends on whether one is constrained on number of machines available, power, rack space, or operating cost.

Figure 4 notes the hash rate as the contours in 1 TH increments where the X-Y axis are the same as above:

Similarly, the following Figure 5 shows the power draw in 25-Watt increments at each voltage/frequency combination:

In Figure 4, the hash rate contours are relatively vertical. This follows the observation that certain frequencies are expected to produce a certain TH. The bottom-right hand corner of Figure 4 exhibits that the hash rate becomes highly unstable and erratic if there isn’t sufficient chip voltage applied. In Figure 5, the power contours are diagonal. These two graphs combine to create Figure 1 (J/TH contours) in this series.

Lastly, there is one more variable to discuss—temperature. More specifically, board/chip temperature. The following Figure 6 shows the effects of temperature on the efficiency of the machine. The X-axis is noted chip temperature (C) and the Y-axis is the efficiency recorded at that temperature (J/TH). The three lines are measurements at three different frequencies (and associated maximum efficiency voltage). The blue line is the highest frequency in the series and the yellow line is the lowest. These points are highlighted in Figure 1 with green circles.

We observe that reducing chip temperatures is beneficial—up to a point. Lowering chip temperature to ~40C lowers the measured watt draw of the machine without affecting hash rate stability. However, below ~40C (or board temp of ~25C), the marginal power draw drop flattens and hash rate becomes unstable and erratic. As a result, the efficiency at the same voltage/frequency combination goes down. That said, by regulating the temperature down to this ~40C threshold, the operating efficiency of the machine can increase by 3-4 J/TH. Maintaining such low temperatures, however, becomes exponentially harder and generally results in higher capex to achieve consistently.

Measurements in each of the preceding graphs were taken at 45C (+/- 2.5C). The vertical line at 45C would be the J/TH plane exhibited (rotated 90 degrees to the side) in Figure 1. The original heat map efficiency contours would change if the measurement temperatures were to change. This illustrates the effects and importance of temperature management. It is also important to note that these results are dependent on the machine itself, the operating conditions, and machine type (e.g. S19, S19J, S19J Pro, S19 Pro, etc.).

We hope to have more news to share relating to firmware and our underclocking efforts in the near future. Until then: together, we win.

The History of Debt in Bitcoin Mining

Disclaimer: this series is biased toward western markets (specifically North America). While China was the Mecca of bitcoin mining long before industrial-scale projects arose in the US, the author and audience alike are likely more focused on the western hemisphere. As such, we will focus exclusively on the debt capital markets in North America, despite the fact that many similar products were offered in China and other countries.

In the 14 years since the Bitcoin network launched, we have seen bitcoin miners evolve from cryptography enthusiasts hashing with CPUs, to profit seekers investing in more and more efficient hardware (i.e., the lowest energy consumption per hash). From CPUs, miners quickly moved to GPUs, FPGAs, and finally to their own application-specific hardware, bitcoin mining ASICs.

In these early days, there was little to no debt financing available to bitcoin miners. The reasons were various:

1. The useful life of mining hardware was very short, with certain models remaining competitive for only 6 – 18 months before newer, more efficient models rendered them economically obsolete.

2. The short lifespan of ASICs paired with bitcoin’s price volatility led to highly volatile returns for mining investments, making assets and projects very difficult to underwrite.

3. Most lenders didn’t understand bitcoin or bitcoin mining. And with bitcoin mining being such a small market (annual mining revenue didn’t exceed $1 billion until 2017), there was little incentive for lenders to pay attention.

4. The “industry” was still immature; participants were aggressive, and often unprofessional. Many of the new mining companies and hardware manufacturers proved to be outright scams (I leave the reader to judge how much this has changed).

For the above reasons and others, bitcoin mining has tended to lag the rest of the “crypto” industry in terms of debt products. Debt has long been available for traders on offshore exchanges looking to lever up 100x on perpetual swaps, but it took until 2017 for bitcoin-backed debt to become available en masse to retail and institutional borrowers in the US. Retail bitcoin-backed debt was pioneered by companies like Unchained Capital and BlockFi, while trading houses like Genesis and Galaxy Digital provided the early collateralized debt products for institutions. In this era, most large bitcoin-backed loans were bespoke trades offered to hedge funds and sophisticated high net worth individuals, but the ultra-low interest rate environment and bitcoin’s utility as pristine collateral attracted more capital and lenders to the asset class. The price appreciation of bitcoin (“number go up”) also played a role, as more individuals and institutions looked to borrow against their bitcoin.

In the mining world, the 2017/2018 era also saw the first publicly traded bitcoin miners, with the likes of Riot Blockchain (which pivoted from a pharmaceutical technology company to bitcoin mining in 2017), DMG Blockchain, Hive Blockchain (which pivoted from a minerals exploration company in 2017), Hut 8, and Fortress Blockchain (now Cathedra Bitcoin) leading the charge. Others soon followed, with Bitfarms going public in 2019 and Marathon Digital completing its pivot in 2020 (after an initial bitcoin mining pilot in 2017). Outside of public markets, this era also saw the rise of then-private, “institutional” bitcoin miners in North America like Argo, Compute North, Core Scientific, Griid, Greenidge Holdings, and others.

These companies were primarily financed with equity; however, debt financing for bitcoin miners also began to emerge. In 2018 Galaxy Digital issued a $16m term loan to Hut 8 to finance new mining infrastructure, collateralized by bitcoin and infrastructure. The year 2018 also saw the founding of Arctos Capital and Blockfills, early pioneers in ASIC-backed debt in North America. Shortly thereafter DCG and Galaxy Digital both spun up their own mining businesses each with their own financing products for miners (Foundry (2019) and Galaxy Digital Mining (2020)).

From 2019 through 2020, a variety of smaller debt transactions were executed, as capital-deprived miners sought whatever forms of financing they could during the bear market. The lower velocity of the bear market also provided lenders the opportunity to fine-tune their structures, underwriting, and servicing capabilities.

The growth of debt during this period was enabled by a variety of factors:

• Commoditized hardware. The 2018 crash drove many hardware manufacturers out of business (or at least atrophy into insignificance). By summer 2019, the hardware market was dominated by Bitmain, Canaan, and MicroBT. This greatly simplified the buying and selling of machines, with “rigs” becoming increasingly fungible. These manufacturers released roughly similar machines (in terms of efficiency) on roughly similar timelines.

• Longer ASIC lifespans. The Bitmain Antminer S9 was first released in 2016 but was still in wide use up until the 2020 halvening (arguably, it still is). This suggested that ASICs were now investible for the long-term, and that step-changes in hardware efficiency were perhaps a thing of the past. Tangentially, these first two factors also led to an increasing focus on power costs in mining, as access to the latest hardware no longer provided a durable competitive advantage.

• The growth of mining in North America. Due to its permissionless nature, anyone can mine bitcoin anywhere in the world. However, the United States and Canada’s robust capital markets, abundant energy, and respect for property rights led to a meaningful increase in mining investments here from 2017 onward. This growth accelerated in 2021 following a bitcoin mining ban in China, as miners sought refuge in the regulatory environment of North America.

• Near-zero interest rate environment. As mining became more and more common in the epicenter of the global financial system, pockets of yield-starved capital salivated at the prospect of 8 – 30% debt (despite the obvious risks).

• Industry “maturation.” The emergence of the aforementioned “institutional” mining companies gave the sense that this was now a real industry that could be trusted with credit. Many of these companies were run by converts from the 2017 bull run, bringing with them corporate sensibilities and relationships from other industries. Many thought the days of Shenzhen “chicken shack” mining were over, the network instead to be dominated by “Big Box Miners,” with hyperscale data centers built atop freshly waxed floors.

• Number go Up (“NgU”). After bouncing back from the bottom of $3k in Q4 2018, it became increasingly clear that bitcoin was here to stay. And the rally in 2019 gave many hope that they would see the moon once again (soon™).

By the end of 2020, bitcoin mining debt capital markets had expanded to include a variety of competing lenders (Foundry, Galaxy Digital, NYDIG (which acquired Arctos), BlockFi, and others) offering a variety of debt products.

The foundations were laid. So, when bitcoin price took off in Q4 2020/Q1 2021, a boom in mining investments followed. Throughout 2021, equity capital flocked to bitcoin miners, pumping mining stonks in the process. These rising asset and equity values enabled miners to access increasing amounts of debt. Highlighting this point, several large equity raises of 2021 were accompanied by large debt facilities. As this period also saw the rise of ASIC “futures orders,” it even became possible to secure debt financing on machines that had not yet been delivered. The “old” generation of “institutional miners'' used this as an opportunity to catapult themselves to hyperscale. Simultaneously a variety of new entrants jumped onto the scene with multi-billion-dollar SPACs on zero deployed hash rate.

One can’t help but admire the supporting macro factors that contributed to the perfect storm of this capital binge for North American miners. The COVID stimulus left many markets flush with capital. Energy prices remained low as the commodity bear cycle played out its final act. Bored Patagonia-clad PE bros with a recently piqued interest in “crypto” sought to take advantage of the public/private market arbitrage of hash rate valuations, in hopes their returns might bankroll yachts and bottle service at E11even. All while China banned bitcoin mining, suppressing hash rate during bitcoin’s scenic route from $60k down to $30k and then back up to $69k

But like all binges, the bitcoin mining hype cycle of 2021 was followed by a brutal hangover. The bear market of 2022 has seen many darlings of the last few years turn into distressed assets. Several large-scale public miners have been forced to restructure their balance sheets or file for bankruptcy.

And while debt may have been a new tool for bitcoin miners, credit markets have been around for thousands of years, and the key principles of debt are largely unchanged. In this next section, we will explore these principles, before evaluating the current array of bitcoin mining debt products.

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Principles of Debt

If you consider yourself fluent in the concepts and parlance corporate fuh-nance, feel free to skip this section.

Wikipedia defines “debt” as “an obligation that requires one party, the debtor, to pay money or other agreed-upon value to another party, the creditor.” Such obligations can take many forms, but there are a few key principles that underlie any piece of debt.

Capital stack overview

To understand debt, first one must understand the idea of the “capital stack.”

For our purposes, all forms of financing can be grouped into two buckets: debt, and equity. Debt holders are considered “contractually senior” to equity holders. This means that debt holders have first claim to the assets and are therefore paid out first in the event of a bankruptcy or liquidation. As a result, debt is considered “less risky” than equity, and therefore has a lower expected return. The debt and equity portions of the capital stack can be segmented further; in order of seniority: senior debt, junior or mezzanine debt, preferred equity, and equity. There could also be multiple types of debt or equity that are the same level of seniority, or pari pasu, with each other.

The main reason you would try to fund an enterprise with debt instead of equity is to enhance returns. If you want to buy a $10 project, you can either use $10 of your own money, or you can borrow $5, and—so long as you service the debt—can keep all profits (after debt service) for yourself (on a lower denominator of invested capital). We will explore the impact of leverage on bitcoin mining returns in more detail in a later section.

Lenders structure debt facilities with the goal of getting paid back full principal and interest regardless of other exogenous factors. To do so, lenders seek to give themselves as much protection as possible; “protection” meaning tools that allow them to minimize the risk of not getting their money back. These tools are frequently referred to as “credit enhancements” and come in several forms.

Creditworthiness

The lender will first evaluate the overall creditworthiness of the borrower. Creditworthiness is a measure of the borrower’s ability to pay back the lender. Less “creditworthy” borrowers will typically have additional credit enhancements to increase the lender’s comfort in getting repaid.

Collateral

The simplest form of “credit enhancement” is collateral. Lenders often require borrowers to pledge assets to “collateralize” the loan. This means that if the borrower were to fail to repay (or “service”) the debt, the lender could claim and liquidate the collateral. For example, if you buy a house using debt financing from a bank (take out a mortgage), you pledge your home to the bank. If you fail to make good on your debt payments, the bank can reclaim your house (foreclose).

Debt that is backed by a specific asset (a car, house, or bitcoin mining ASIC) is typically referred to as “asset-backed,” though like all finance jargon, the boundaries of the definition can be murky. In general, if debt is being used to finance the purchase of an asset, lenders will require that asset to be part of the collateral, but lenders might also request additional collateral. Additionally, just because a loan is “asset-backed” doesn’t mean the creditworthiness of the borrower is no longer relevant; asset-backed lenders focus on the overall creditworthiness of the borrower plus the valuation of the underlying assets.

The value of collateral relative to the amount of debt is very important. This ratio has a variety of names, but the most common is Loan-to-Value or “LTV” for short (other variations include “collateralization ratio” and “advance rate”). LTV is calculated as the size of the outstanding principal (the “L”) divided by the value of the collateral (the “V”). This provides a simple way for lenders to calculate their protection in the event they had to foreclose on the loan. For example, if a lender had to foreclose on an 80% LTV loan and liquidate the collateral, the asset price could fall by 20% before the lender took a hit. In other words, the higher the LTV, the riskier the loan. This example also demonstrates the importance of collateral liquidity and volatility; the more liquid and less volatile the collateral, the less risky the loan.

Some loans do not require collateral to be pledged to the lender; these are called “unsecured” loans as the debt is not “secured” by any collateral. Lenders will still consider the borrower’s assets and credit worthiness when sizing and pricing unsecured loans, the lender just has no specific legal claim (or “perfected lien”) against any assets. These loans are typically only available to people and organizations with strong credit credentials, as a loan secured by specific collateral has a lower risk of loss than an unsecured loan. Such loans are rarely available to bitcoin miners.

Covenants

As means of further protection, lenders often also stipulate specific rules around what a borrower can and can’t do; such rules are called “covenants.” Covenants might stipulate the exact use of an asset, certain rules around other activities of the borrower, or might require certain actions from the borrower should things happen that are entirely outside of their control (e.g., margin calls or uptime requirements).

Cost of capital

The above will all help determine the cost of debt (the interest rate). This cost of debt stems from the time value of money. The lender needs to be compensated for giving their capital to the borrower. The amount they need to be compensated is based on the probability of repayment. The riskier the debt is perceived to be, the more expensive that debt will be. In the words of Art Lyon, "There's no bad risk, just a bad price.” Notably, the price of risk varies dramatically with market conditions.

Likewise, a lender’s cost of capital is also important in determining the interest rate a borrower pays. A lender can only offer loans at a cost of capital that is higher than the cost they pay. In fact, a lender’s whole business model is lending out money at a higher interest rate than their own cost of capital; the difference between their interest income and interest expense is their profit, or in debt-speak their “net interest margin” (“NIM” for short). For this reason, in emerging debt capital markets, the cost of capital is typically high as the first lenders likely have higher cost of capital themselves. As the market matures, larger lenders with lower cost of capital often push out these pioneer species by undercutting their rates.

Back-end financing

To this end, the existence of a secondary market for loans in an asset class can influence the cost of debt for those loans. If a lender can sell loans to other investors, then they can lock in a return and free up capital to generate more loans, which can drive down the cost of debt for borrowers. This is the principle behind securitization markets, and is a large reason why certain forms of debt like car loans and mortgages are so cheap. The larger the secondary market for these loans, the easier it is for lenders to originate and distribute, earning net interest margin in the process.

Debt Products for Bitcoin Miners

The above principles underlie all debt, but most industries have a limited array of readily available debt products, typically tried and true structures that have stood the test of time. We will now walk through the existing universe of debt products available to bitcoin miners.

Asset-backed debt

As a reminder, asset-backed debt refers to loans backed by a specific asset. There are three main categories to consider: bitcoin-backed, ASIC-backed, and infrastructure-backed.

Bitcoin-backed debt is one of the oldest structures available to bitcoin miners. The logic is simple: a miner can deposit bitcoin as collateral to the lender and receive a fiat-denominated loan in exchange. Bitcoin has many properties that make it particularly attractive collateral; it’s a digital bearer asset that trades 24/7 on a variety of highly liquid venues. As a result, it typically offers the lowest cost of capital for bitcoin miners. However, bitcoin’s price volatility means LTVs can fluctuate dramatically; for this reason, lenders often have margin call provisions (if bitcoin falls below a certain price, the borrower needs to contribute additional collateral or repay part of the loan). The interest rates for these loans vary depending on the lender and market conditions, ranging from 4 – 12%. The loans have varying terms, but they typically don’t amortize, meaning there may not be any mandatory principal payments until the maturity date.

ASIC-backed debt emerged as the structure du jour during the last bull market. These loans typically had 18-month terms for an all-in cost of capital ranging from 13 – 28%. This is notably more expensive debt than bitcoin-backed loans, but it gave new miners without large bitcoin treasuries access to a new pocket of capital. In some transactions, miners could even finance machines before they were delivered (e.g., if a miner entered into a futures order, they could secure debt financing before the machines were deployed). However, once the financed machines are plugged in, the loans start amortizing (meaning principal is paid down gradually over the term). Similar to bitcoin-backed debt the value of the collateral (ASICs) can be quite volatile, resulting in similar LTV fluctuations. Unlike bitcoin-backed debt, however, it’s hard to employ a margin call on ASICs. This has caused some lenders to offer low LTVs (sub 50% in some cases), but even still, the market turmoil of H2 2022 has resulted in many such loans becoming undercollateralized (LTVs > 100%). In terms of covenants, these loans might stipulate certain uptime requirements, prohibit the use of firmware and immersion, or other operational rules to ensure the value of the collateral is preserved.

Infrastructure-backed loans for bitcoin miners also appeared in the last 24 months, allowing miners to gain financing on the supporting infrastructure at a mining site. The loans range from utilities financing substations to mining savvy lenders providing leverage against containerized data centers. Infrastructure-backed lending (or “project financing”) is quite common in other industries (including and especially energy), however these traditional lenders typically are not comfortable lending to bitcoin miners. Legacy industries are often able to borrow against infrastructure at higher LTVs, lower interest rates, and over longer terms (up to five years). But given the volatility of bitcoin mining, miners likely only have access to such loans at materially worse terms than traditional industries like energy. The primary lenders currently serving bitcoin miners with infrastructure-backed debt are either the small subset of legacy institutions who have gotten comfortable with bitcoin mining risk (e.g., certain utilities and energy infra lenders) or smaller lenders who are comfortable taking a bitcoin miner’s power or data center infrastructure as collateral. Infrastructure-backed debt is similar to ASIC-backed debt in that the collateral is a physical asset that can be liquidated (in theory at least), but there is much wider variance in the terms. These loans have yet to become a meaningful portion of the market, but they do exist.

Corporate Debt

Instead of borrowing against a specific asset, miners also might choose to borrow money at the corporate level. A common example of this would be a “Senior Secured Term Loan,” which typically involves an “all asset lien,” meaning that the lender would take substantially all the borrower’s assets as collateral. These loans can also have more complex features, such as rules around accessing some proceeds only after certain operational achievements. There are a few benefits from the lender’s perspective: first, the structure is simpler as there is little risk of multiple pieces of debt that may be in conflict with each other; second, the lender has a claim to all cash flows from the business not just specific assets; and third, if the borrower does default, the lender can just take ownership of the existing operations without being forced to sell collateral on a potentially illiquid market. From a borrower’s perspective, these loans are a simple way to get debt financing, but they offer less flexibility. These loans are typically only available to large miners and may have unique covenants and rules around unlocking proceeds. It’s worth calling out that such loans have not been the primary forms of debt financing for bitcoin miners, but they may become more common in the future.

There are other types of corporate debt as well (e.g., convertible debt and other bespoke structure), but they are not common enough to warrant evaluation in this essay.

Summary Comparison

It is worth flagging that this table is obviously prone to fluctuations in the market (bitcoin price, mining economics, broader macro factors, etc.) as well as borrower-specific considerations. This overview of different structures should be viewed as a high-level map, outlining the current landscape of debt for bitcoin miners (and perhaps provide context for some of the recent news in bitcoin mining).

Next, in Part II, we will look at some high-level considerations for lenders and borrowers alike, play with some math to see the effects of leverage on bitcoin mining operations in a variety of market conditions, and lastly reflect on how the market could evolve in the near to medium term.

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This article was written for the Braiins blog by Drew Armstrong. Drew is the Chairman, President, and COO of Cathedra Bitcoin, a company that believes sound money and abundant energy are the keys to human flourishing. Prior to joining Cathedra, he was a founding member of Galaxy Digital’s bitcoin mining team and helped build out Galaxy's mining equipment finance product. Drew began his career at Barclays' investment bank, where he focused on the origination of esoteric securitized products, such as data center securitizations and collateralized fund obligations. His views here do not reflect those of any of his past, present, or future employers. Follow Drew on Twitter.

Writing is thinking. And at Cathedra, we write to improve our thinking. 

This blog will catalog our writing, old and new. We are first and foremost operators, focused on building a beautiful business at the intersection of money (Bitcoin) and energy. But as we refine our thinking, we will invariably write. And we will share our writing here.

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Our aim was simple: to outline humanity’s relationship with energy from first principles and describe the role bitcoin mining can play in building a better future — one defined by sound digital money and cheap, abundant energy. This is the future we are working to build at Cathedra Bitcoin. And we invite you to join us.

Much ink has been spilt on the topic of Bitcoin’s energy consumption. Many have condemned Bitcoin’s growing use of energy, and in response, many others have sought to justify it. The war wages on, atop the battlegrounds of Twitter timelines, Medium pages and major news outlets. But much of this discourse fails to fully address the concept of energy itself.

Energy is quite literally the foundation of existence. In the words of Robert Lindsay, “no other concept has so unified our understanding of experience.” But energy is also a very subtle concept, so our intuitions on the topic often lead us astray.

The goal of this essay is not to defend Bitcoin’s social benefit. We take for granted that a sound money free from bureaucratic debasement has value independent of the speculation, money laundering and nefarious activities it is so often accused of enabling.

The goal of this essay is to outline our view of the future of energy, bitcoin mining and how these two currents will converge. We conclude that this convergence will catalyze an energy revolution that has the potential to usher in a period of unprecedented prosperity. But first, we will lay the groundwork with some energy fundamentals.

Energy: The Foundations

“Energy is the only universal currency.” - Vaclav Smil, “Energy And Civilization”

Earlier, we stated that energy is the foundation of existence. This is not hyperbole; at the beginning of time — what some have called “The Big Bang” — our entire universe was a dense ball of energy.

In the billions of years since, the significance of energy has not diminished. Even today, all matter contains energy; this insight lies at the heart of Einstein’s famous equation, E=MC². But energy takes many other forms as well: the movement of your hand (kinetic energy), the calories in the food you eat (chemical energy), the light from the sun (electromagnetic energy), the heat from the kettle (thermal energy)… the list goes on, but the underlying concept is the same. Energy is the capacity to do work, regardless of the type of work involved (“power,” on the other hand, is the rate of energy flow).

But not all energy is created equal.

The first two laws of thermodynamics tell us that while energy is conserved, it flows towards equilibrium. A hot body (high energy) connected to a cold one (low energy) will eventually give off its heat until the two are the same temperature (equilibrium). And in this approach toward equilibrium, order is lost. As waste heat is created, entropy increases.

Entropy tells us how the energy of a system is distributed among its parts. Over meaningful time horizons, the entropy of any system will increase. To reduce entropy within some part of the system, entropy must be increased elsewhere. States of order and complexity are lower entropy than states of disorder. The creation and preservation of structure requires a decrease in entropy locally, resulting in an increase in entropy elsewhere.

Though entropy is often viewed negatively, life itself depends on it. Life compresses energy into low-entropy states and pays for it by emitting energy with much higher entropy elsewhere. You ingest resources from the environment (air, food, water) to preserve your internal order and create structure (amino acids, tissue, etc.), and in doing so, you increase entropy in your immediate surroundings.

When considering energy, there are other factors beyond entropy that are relevant as well — density and efficiency in particular. Some forms of energy are more dense than others. Likewise, extracting energy from some low-entropy sources is more efficient than others (this holds true in physics as well as economics).

This inequality between various forms of energy is all the more pronounced in practice. Heat is considered waste in many industrial processes (entropy in its most literal sense). Other ambient, low-density forms of energy may be abundant on earth, but are quite hard to utilize. Today, it would seem foolish to burn grass for energy on an industrial scale. Meanwhile, humans scour the planet for rare minerals to build expensive batteries in hopes that they might offer us a few hours of densely packed energy when we need it most.

It is not just “energy” we care about, but energetic order. We want our energy in a distilled form. We want energy that is easy to command and transport wherever we need it. And we want energy that can be used for anything.

“It is energetic order that’s scarce, and the order in energy that’s expensive.” – Peter Huber and Mark Mills, “Bottomless Well”

The story of our “energy consumption” is really the story of humanity’s Sisyphean effort to create and preserve order, harnessing ever-greater amounts of energy to support life by reducing entropy locally and shedding more entropy elsewhere.

In this light, the terms “energy production” or “generation” are misleading. The energy is conserved, but its order is not; the energy is distilled so that it can be more functional, more concentrated, and more easily controlled. A watt that can be delivered on demand through a tiny wire is far more valuable than a watt of ambient heat. Power plants do not “create” energy; they merely convert it into a useful form. Thus, our “energy footprint” is determined by our ability to facilitate these conversions, limited only by the laws of physics, current technology and economic realities. And a massive portion of this footprint is used to distill energy into its most fungible form: electricity.

The Age of the Electron

Electricity is the most distilled form of energy. It is highly dense; electricity allows for a single transmission line to carry enough energy to power a small country. It is also highly versatile; electricity can power cars, household appliances, many industrial processes, and perhaps most notably, the entire apparatus of information technology that’s allowing you to read these words.

In terms of energetic order, electricity is king. For this reason, technology continues to select for electricity as its primary source of energy. As this trend continues, our economy is becoming increasingly dependent on this form of energy (various climate change policies are only accelerating this electrification).

Developed nations take ubiquitous electricity for granted. Meanwhile, intermittent power can be one of the biggest burdens for developing nations to overcome in their quest for economic growth.

But electricity is a particularly tricky commodity to depend on.

Electricity is a distinctly local phenomenon. If there are no transmission wires, it is trapped at the site of generation. This is fundamentally different from the fossil fuels that powered the last roughly 250 years of global industrial growth, which can be extracted around the world, stored cheaply, and transported wherever there is demand.

But we don’t care. Our demand for electricity is fickle. When we plug our phone charger into an outlet, we demand it be met with fresh electrons.

Unfortunately, however, the supply of electricity is constrained. It takes time to build out new power generation projects and complete the requisite regulatory processes. It also takes money, as electrical generation and transmission infrastructure requires substantial capex. So, potential electricity supply is relatively fixed in the short term.

Yet, despite the fickle supply and demand, the electrical grid must be balanced. Grids are effectively massive circuits, so if supply does not match demand, the consequent variations in voltage and frequency can cause blackouts. Phrased differently, unlike every other commodity, electricity must be consumed as it’s produced (though much investment has been made into industrial scale battery storage, this technology has yet to prove viable for long-term storage). Fortunately, at scale, much of the short-term fluctuations in demand cancel each other out. But the balance is still actively managed by grid operators who dispatch different generation resources, storage mechanisms and curtailment programs to achieve this outcome. One of the more common methods is “load following,” with flexible generation sources like natural gas scaling up and down to meet the variable electricity demand (or, even if demand is constant, to balance the intermittent generation of solar and wind resources).

This is all to say that it is expensive and difficult to reliably purify energy into electricity, and civilization as we know it depends on those precious electrons. But this hasn’t always been the case.

The Case for More Energy

Man’s default state is abject poverty. The natural world is not a hospitable place for humans; our environment is neither stable nor safe for us unless we transform it. The livability of the planet for the average human depends on our ability as a species to develop the environment into resources that protect, nourish and sustain us.

For most of history, we have been limited to using human and animal labor to do so. Indeed, humanity’s crowning achievements and the comforts of the modern world — extended life expectancy, resource abundance and material wealth — are enabled in large part by a discovery made in the last roughly 250 years, one which unlocked another source of labor beyond mere humans and animals: machines.

Machines can amplify existing human productivity (the printing press produced a step-function increase in the volume of information that could be copied to paper per unit of time) or enable new capabilities altogether (MRIs and other medical imaging technologies provide views into internal organs that no amount of human labor alone could).

But machines don’t power themselves. The cheaper and more abundant the fuel for our machines, the more machine labor we have at our disposal to improve our living standards. Consider, for example, the technological progress and quality of life gains made in the centuries following the Industrial Revolution — the period in history during which man discovered that fossil fuels could be used to cost-effectively power machines. Today, based on the average American’s daily energy consumption, a single individual has the equivalent of nearly 600 humans working at their behest (and without violating any human rights). For most of human history, each individual’s productivity was limited to what they could achieve with their own two hands.

Today, we have freed ourselves from that particular constraint. But consequently, we are more dependent on machine labor than ever. This reality was laid bare in the power crisis that befell Texas in February 2021, during which winter storms caused power outages that triggered food and water shortages, critical infrastructure failure and dozens of fatalities. A few days without energy to power our machines can be a stark reminder of just how fragile modern civilization is. But we will need yet more energy in the future.

In a way, energy is the meta-problem. The most difficult challenges we face as a species become soluble only by converting greater amounts of energy into more highly-ordered forms. The cost of transportation becomes trivial. Food preservation through refrigeration can be delivered to every country in the world. The cost of desalination and other water purification processes is vastly reduced, allowing us to solve the water crisis and its downstream health effects. Our global capacity for computation is hindered only by access to silicon, a problem which is itself tractable with more energy. And without these watts, we will struggle to find alternative solutions.

“It is by mastering power itself — the capture and release of energy — that societies master everything else.” - Huber and Mills, “Bottomless Well”

Of course, the unfortunate flipside of this coin is the grim reality that less energy production exacerbates existing problems and creates new ones. It means fewer resources to sustain life: less food, fewer economic opportunities and higher costs of living. On a long enough timescale, it leads to civilizational decline and all the human suffering that attends it — an acute manifestation of disorder. From a humanist perspective, less energy is never the solution.

A common objection to this brand of energy maximalism is that efficiency improvements can and should obviate the need for more energy. Why can’t we just do more with less? The short answer is: because we never do. Jevons paradox holds that gains in efficiency with which a resource is used only lead to increased demand for that resource. More efficient automobiles led to more driving, not less gasoline. In the case of energy, more efficient generation technologies serve to increase energy consumption rather than curb it. Energy begets more energy; much of the energy we consume today is in the service of discovering, extracting and developing more energy resources for tomorrow.

All this to say, there is no optimistic version of the future in which humanity does not use significantly more energy than it does today.

To the extent we discover new, cheaper ways to energize machines, human quality of life will improve, as we gain ever more mastery over our physical surroundings. This process need not be limited to the environment on Planet Earth; given access to energy that is sufficiently affordable and abundant, humanity could use machines to transform the environments of other planets to support human life. This is a vision that animates us and one we believe is worthy of vigorous pursuit.

Money and Energy

“Money is energy. Bitcoin is the first crypto monetary energy network, capable of collecting all the world’s liquid energy, storing it over time without power loss, and channeling it across space with negligible impedance.” - Michael Saylor

Money allows one to command resources. If energy is the capacity to do work, then the ability to command resources is itself a form of potential energy. Indeed, money and energy have always been linked.

In his seminal essay, “Shelling Out,” Nick Szabo identifies “unforgeable costliness” as an essential property of various proto-monies throughout history. Throughout the ages, the likelihood of a good being used to facilitate wealth transfers has been in part a function of the difficulty with which one could produce or obtain additional units of said good. That is, to be selected as a money on the free market, a good must be costly to produce in terms of time or energy.

“Wampum” — clam shells — carried value among inland Native Americans in the 17th century largely because one could only collect them near ocean shores, requiring considerable exertion to travel to the coast and back. Rai stones were large, disk-like rocks that were for centuries used as a primitive form of money by the inhabitants of the Yap islands in Micronesia. Weighing as much as four tons, rai stones were not native to the Yap islands; importing additional stones necessitated great expenditure of energy. And of course, the commodity monies of more recent history — gold foremost among them — all entail energy-intensive production processes owing to their lack of abundance in the Earth’s crust.

Luminaries including Henry Ford, Thomas Edison and Buckminster Fuller have at various points championed the idea of a currency literally backed by energy (though we remain skeptical of the wisdom and practicability of such proposals). Even the U.S. dollar — a fiat currency whose marginal cost of production approaches zero — is in some sense “backed” by energy today. For decades, the world’s largest producer of oil has agreed to settle all of its sales in U.S. dollars in exchange for U.S. military protection, an arrangement that has come to be known as the petrodollar system.

In Bitcoin, Satoshi made the relationship between energy and money explicit. Bitcoin’s proof of work is a synthetic recreation of Szabo’s “unforgeable costliness”; new bitcoin are issued to miners, who provably consume energy. To this day, proof of work remains the only way we know how to verify in a digital system that energy has been expended in meatspace.

Recently, Michael Saylor has popularized the notion of money as a technology for transporting energy across time and space. We agree with his assessment of Bitcoin as “the most efficient energy network in the history of the world.” As Saylor put it, “the challenge of humanity is, ‘how do I store and transmit energy across time and space and domain?’”

With its fixed supply and digital nature, Bitcoin does not suffer from the same “transmission losses” that plague the monetary energy networks of old. Storing one’s monetary energy in gold involves significant carrying costs and leakage in the form of transaction costs, should one ever seek to transmit that energy across space. And while the U.S. dollar and other fiat currencies improve on gold’s salability across space, they perform poorly as a vessel for transporting monetary energy across time.

Enter Bitcoin Mining

Bitcoin can be understood as a distributed machine that automates the issuance of scarce monetary units and the settlement of financial transactions. The system achieves these ends by demanding that certain network participants — namely, miners — provably consume electricity, which allows the network to order transactions and assure final settlement in the absence of a trusted third party. Perhaps more profoundly, this proof of work creates a connection between the physical and digital worlds that cannot be falsified. The nonce used to create a valid block is the residue of a physical process which must consume energy.

Like other machines, Bitcoin is a productivity-enhancing technology. In the centuries to come, Satoshi’s invention will save incalculable human time in two ways. First and foremost, Bitcoin offers savers protection against large-scale time theft perpetrated by central bankers and their inflationary monetary regimes. Second, Bitcoin liberates resources that would otherwise be spent in the primitive practice of actively managing the money supply — much in the same way that other technological advancements throughout history have allowed us to discard mundane tasks in favor of more productive pursuits. You will seldom encounter someone scrubbing clothes by hand in a home with a washing machine.

To fully understand its relation to the energy sector, we must first grasp the economics of bitcoin mining. At its most fundamental level, bitcoin mining requires nothing more than specialized hardware, electricity and an internet connection. It can be done anywhere in the world at any time of day. Miners’ revenues are unknown, but their costs are usually fixed. And the primary cost is energy. This incentivizes bitcoin miners to find the cheapest power possible, and they scour the earth to do so. As a result, miners typically use power that would otherwise be wasted — or, as coined by Nic Carter, “nonrival energy.”

Phrased differently, bitcoin mining is a permissionless energy sink. Anyone, anywhere in the world can generate revenue by plugging mining machines into an electricity source. This sink is also highly flexible with respect to both time and space. Bitcoin miners can turn their machines on and off without any obligations to customers and can operate in almost any physical envelope.

For the energy sector, bitcoin mining provides a constant demand for energy and a revenue floor, allowing us to monetize energy that would otherwise go to waste. Energetic order is such a precious resource, it would be a shame to let it go unused.

“Do not waste any energy, make it useful.” - Wilhelm Ostwald, winner of the Nobel Prize for Chemistry in 1909

We already see this taking place in the wild, with bitcoin miners helping to balance the intermittent electricity supply of renewables or capturing natural gas that would otherwise be vented or flared. But even more than just utilizing existing wasted energy resources, bitcoin mining will incentivize new generation far in excess of our current capabilities.

The Future of Energy and Bitcoin Mining

Bitcoin mining directly incentivizes new and more efficient forms of energy generation by offering a “bounty” to anyone, anywhere, at any time, who finds a cheaper way to produce energy at scale. This direct financial incentive for more efficient generation and the newfound viability of previously uneconomical sources of energy will cause a general decline in the price of energy worldwide.

We may well see bitcoin mining operations bootstrap new human settlements into existence. Whereas in the past, generation was only economically viable in locales that were relatively close to the ultimate site of consumption (i.e., population centers), bitcoin mining allows us to develop power generation infrastructure in remote, energy-rich locations and monetize it via the Bitcoin network. After recovering the initial capital cost, the mining profits can be used to fund additional infrastructure build-out to support residential or commercial human settlements that will benefit from the cheap, abundant energy resources.

Economic incentives will impel bitcoin mining to completely saturate the energy sector in the coming decades. The gradual convergence of these two sectors has already begun, and will continue from both directions. Energy producers will monetize surplus power that would otherwise be sold at low or negative rates to the grid (or wasted altogether) by selling it to the Bitcoin network. And bitcoin miners will vertically integrate, owning their own power generation and infrastructure to improve their margins and thereby their competitiveness. It stands to reason, then, that in the future, the most efficient miners will also be energy producers.

At what point will we reach full saturation? Dhruv Bansal of Unchained Capital submits his theoretical “Nakamoto Conjecture” as a plausible answer to this question. Bansal predicts an equilibrium at which the marginal revenue earned from mining bitcoin equals the marginal revenue earned from selling power to the electrical grid. Mining beyond this threshold would be economically irrational for energy producers, since selling power to the grid would be more lucrative. Below this threshold, there remains an economic incentive for producers to continue mining.

Thus, Bitcoin’s energy consumption as a share of global energy production will continue to increase as market participants arbitrage this difference. Bansal refers to this share as the “Nakamoto Ratio” — the fraction of global energy production that is dedicated to securing the monetary base.

The optimal value for this ratio is open for debate, but Bansal hypothesizes that once we reach this saturation point — when marginal revenue from mining equals marginal revenue from selling power to the grid — the Nakamoto Ratio will stabilize, marking the go-forward share of global energy that is used to secure the money supply.

But we are nowhere near this saturation point today. Bitcoin’s energy consumption could grow by a factor of 100 before representing an appreciable fraction of global energy consumption. And revenues from bitcoin mining continue to far exceed those earned by traditional energy producers. Miners using latest-generation equipment today earn over $0.40 per kilowatt hour (kWh), versus an average household cost of electricity in the U.S. of $0.13 per kWh (this figure includes transmission and distribution charges, so the wholesale revenue earned by power producers is likely considerably lower).

What does this mean for humanity? We foresee a new energy revolution.

The Future is Nuclear

We believe bitcoin mining will help rekindle the lost dream of nuclear energy, which today remains humanity’s most promising option for cheap, abundant, clean, safe power. This is because bitcoin mining fundamentally changes the economics of nuclear energy.

Nuclear power plants are expensive to build relative to other forms of electricity generation, suffering from high upfront capital costs and long lead-times. As a result, expected payback periods for nuclear projects are measured in decades, meaning returns are highly sensitive to the cost of capital. In developed economies, uncertainty around future demand growth and heightened competition from other generation sources have injected further risk into the proposition of financing nuclear energy. Meanwhile, a global trend toward market liberalization has shifted the burden of financing new nuclear projects from the public sector to the more returns-sensitive private sector. In sum, new nuclear power plants will not be built unless the expected returns justify the risk — a hurdle made more difficult by considerable regulatory- and policy-related obstacles.

Here, too, bitcoin mining offers a path forward. In the future, behind-the-meter bitcoin mining operations will serve as a “captive customer” for new nuclear power projects, providing stable, predictable demand for electricity. This captive demand will shorten payback periods and make underwriting new nuclear projects less risky for potential investors, reducing their cost of capital and leading to more nuclear generation. This in turn will increase both electricity supply and competition among producers, driving down electricity prices to the benefit of consumers.

Nuclear power plants typically function as a baseload source of power, as they are slower to ramp up and down generation than other energy resources. As a flexible load, bitcoin mining operations can increase or decrease power consumption on short notice, providing demand response services. This would allow nuclear energy to absorb a larger share of any grid’s generation portfolio, thereby reducing the need for costly supplementary peaker plants.

Indeed, at sufficient scale, bitcoin mining could “invert” the grid entirely. Today, load-following energy resources vary their supply output in response to changes in demand to balance the grid. However, with bitcoin mining, generation can remain at peak levels, with miners soaking up any excess and temporarily curtailing their power consumption during peak hours.

But perhaps more importantly, bitcoin mining will incentivize new advancements in nuclear reactor technology.

For decades, nuclear fusion has been “30 years” from commercial deployment. Perhaps bitcoin mining will offer the financial incentive to finally unlock another piece of Einstein’s famous equation, serving as a sink for the excess energy while we as a species grow into its power. After all, if we had discovered a technology capable of providing terawatts of power generation 50 years ago, what would we have done with that energy?

Conclusion

Life is order. We fight to survive, to preserve and perpetuate this precious instance of complexity we call humanity. Energy is our primary resource in this undertaking, and entropy is the inevitable byproduct. We transform energy outside of our bodies to sustain order within, and we pay for this by shedding disorder elsewhere. We are soldiers of the second law of thermodynamics, struggling to protect the order of life and create structure within our world, emitting entropy as exhaust as we progress in this pursuit.

Looking back on the course of human history, civilization has advanced as we have mastered these transformations, developing better methods of harnessing more energy. At the dawn of our species, we were condemned to compete in unfriendly nature using only the energy of our own bodies. We then graduated to harnessing agriculture and animal labor to channel more energy and develop the first civilizations. Over time, the trend continued: capturing the natural power of wind for maritime travel and trade; transforming the flow of streams and rivers to refine our food supply; and eventually extracting hydrocarbons to power the machines that ignited the Industrial Revolution. Humanity has ceaselessly pursued more efficient ways to harness and utilize more energy. At a civilizational scale, advances in energy generation have yielded substantial economic growth, freeing us to lift our heads toward the sky and our minds toward the future.

If we hope to advance further as a species, we must continue our quest to harness ever more energy, and to do so ever more efficiently. If we hope to overcome the crises we face today, we will need to develop and implement better energy technologies. And if we hope to someday become an interplanetary civilization, we will require far more energy than we use today.

“It is not too much to expect that our children will enjoy in their homes electrical energy too cheap to meter, will know of great periodic regional famines in the world only as matters of history, will travel effortlessly over the seas and under them and through the air with a minimum of danger and at great speeds, and will experience a lifespan far longer than ours, as disease yields and man comes to understand what causes him to age.” – Lewis Strauss, Chairman of the United States Atomic Energy Commission, 1954

In Bitcoin, we have — for the first time in human history — a technology that directly financially incentivizes the discovery of cheaper ways to harness energy, one which cares not about geographic location, consumer demand or other historical hindrances to energy generation.

Accordingly, we believe the emergence of bitcoin mining will galvanize the greatest revolution in energy production since fossil fuels and the Industrial Revolution. It holds the potential to drive humanity up the Kardashev scale, incentivizing us to master the energy resources of our planet and beyond.

“Money doesn’t just scale in response to society’s energy usage, it causes it.” – Dhruv Bansal, “Bitcoin Astronomy: Part II”

The ensuing advances in energy technology will dramatically improve our ability to cheaply power the machines we use to survive and prosper, extending the reach of our species to worlds beyond our own. They will enrich lives and relieve suffering at an immeasurable scale, a prospect friends of humanity ought to celebrate rather than scorn.

Credit to the individuals whose work has shaped our thinking on the topics of Bitcoin and energy: Alex Epstein, Dhruv Bansal, Mark Mills, Peter Huber, Saifedean Ammous and Vaclav Smil.

Special thanks to Dhruv Bansal in particular, whose help in the editing process and patient teaching was been indispensable.