Eight Sleep Thoughts

I've recently acquired an Eight Sleep, and have been enjoying it.

But broadly speaking, it also creates a culture of intensity around sleeping and bedtime which seems ill-advised.

A few things in particular have been bothering me: an imposition of various values on the user (namely not spending time in bed without sleeping), the lack of couple-oriented features and analytics, and the requirement of having a phone near bed to control the device at all times.

More generally - by definition, the people working on products are more focused on them than users are. Users use a wide range of products in conjunction with one another. 

I love reading before bed. And sometimes, I like lounging in bed in the morning. I'm not a robot pro-athlete / weirdo tech bro trying to optimize my every minute; I'm a hard-working white-collar worker who sometimes likes to relax in bed.

I want to get great sleep. I want to sleep well, and I want to develop good routines. But imposing sleep-centric values on me is generally frustrating, and candidly makes me less likely to feel good about the product and less likely to refer it to other friends.

Strava Adventures

Currently, Strava's feed is composed of activities. Increasingly, however, athletes participate in multi-activity adventures - think bikepacking trips, hiking journeys and ski touring adventures.

Adventures pollute the activity feed by over-posting, and reduce the amount of social behavior by partitioning comments and discussion across semantically related activities.

Strava should introduce a new concept (an adventure) which groups together contiguous activities for the purpose of increasing the prominence and engagement on the feed while also helping users remember particularly meaningful adventures by selecting key photos to highlight the experience.

Excel-based Azure Functions

The world runs on excel, and increasingly, Excel documents are store in O365 / Sharepoint / OneDrive - in the cloud.

Microsoft should support turning any Excel document into the source code for an Azure Function so that you could have lambda functions for every single macro in Excel, easily available for developers to hit.

This would continue to drive people into Excel while also supporting the transition of businesses towards interconnected API-based companies.

The pathology of Google's carbon-based flight metric

“A strange game. The only winning move is not to play.”

Google recently added a number of fairly odd features to their flight booking system that claims to help travelers learn how much carbon a given flight will release into the atmosphere (link).

But the numbers are misleading.

It's not exactly clear how they are computed, but even if they were correct on average, the irony of the feature is that a set of uncoordinated but climate-conscious consumers could end up increasing the aggregate amount of carbon for a given set of flights if they used these numbers as part of their decision-making process.

In fact - it's almost certainly true that price is a better predictor of the actual carbon emissions of a given route than the made-up Google metric. The cost of a flight is composed of a bunch of fixed costs which the airlines then try to make up on the margin by selling every seat on the plane. A full plane, broadly speaking, is the most carbon-friendly plane: and it's also the cheapest plane for everyone onboard.

Carbon emissions are obviously always lower for a direct flight assuming a full plane, but more direct flights between the set of airports would result in planes which are, on average, less full. There's some bin packing math to do here, but the basic premise is that while the naive calculation for me may imply that the direct flight from London to Austin only costs 731 kg of carbon dioxide, occupying one seat on both of the London to NYC and NYC to Austin flight may end up with fuller flights, thus reducing the per-capita cost of travel: both in carbon and dollar terms.

If consumers were to use this tool, therefore, the result could actually be to push airlines away from more efficient hub-spoke routes towards direct flights with lower utilization.

Of course, it's hard for me to actually believes that anyone actually think this matters: once you've chosen to fly to London, you've basically made the call that you're going to use a tremendous amount of carbon dioxide no matter what route you pick. And implying that the choice of flying direct is 20% better for the environment is just lazy - if you can book the flight, the planes are already taking off with or without you.

Climate change is not a problem that will be fixed by individual action: if we want to fix this problem, we need to pursue unpopular policies to increase the cost of carbon. As a consumer, trying to do multi-variate optimization for every choice is an exhausting way to make decisions; it's why having the almighty dollar, rather than a cryptocoin for every commodity, is the way we evolved out of a primitive economy into one based on the free exchange of goods and services.

Which leads me to the question: why did anyone at Google green-light this project?

The most cynical answer: it lets rich people (like Google employees) who can afford direct flights feel good about their ability to pay more money for convenience by giving them a hedonic boost when they book "carbon-friendly" direct flights (which again, they were going to do anyway, because they are actually paying for convenience). 

When users are speculators: Can web3 apps generate sustainable usage?

Two of my previous posts were about the relationship between labor and capital in innovation-rich parts of the economy. Roberto recently asked: "I'm curious if you have any thoughts how the incentive structures change with web3 / crypto?"

I'm not a crypto bull, though I'm interested in the space, and I honestly think that crypto-economics has a related, but distinct modality of disruption.

In Observer or Participant I argued that investors, by betting on success, can reduce its likelihood. With crypto, I suspect that the same perversion can occur, at least in network-driven applications.

Consider a model in which users of a decentralized application, who have been granted tokens which increase in value as the application becomes more valuable. For the marginal user, is it better to a) participate in an existing application, or b) become a pioneer in a new clone of that application.

Without the user-owned tokens, the answer is clear - the value of the network will roughly track the number of users, with quadratic value a la Metcalfe's Law as an upper bound. The marginal user will receive more value from Application A than from Application B.

But in a crypto-economic world, the user's value equation is different: users receive value both from their usage of the application and from their token. I'm sure there's some math that we can do, but assuming a non-inflationary token (e.g. the first N users get the first N tokens), it's not clear that the same incentives hold. In some sense, you've turned your users into employees, and just like the investors in the previous post, these employees may find it more valuable to cash in and leave rather than staying - selling Token A at the peak and then joining Application B seems like it would be value-maximizing in many cases. And certainly for the marginal user, it seems rational to take a bet on Application B.

In other words - while it may be frustrating to users that Facebook's founder and employees have been able to capture so much of the value that Facebook's users have created, the new incentives in a token-based world may actually make it impossible to create networks with as much value as their web2 competitors; rather than winner-take-all, web3 network effects may actually drive a tremendous amount of internecine warfare with splintering communities forking and re-tokenizing each other's networks. Empirical results from the currencies (BTC / ETH etc) seem to imply at least some amount of stability, but we're in the early days, and the impact may not be what we expect - jealousy is a powerful motivator.

Throughput trumps prioritization

One thing I've been reflecting on a lot as I read about various "theories of vaccination" is the key philosophical distinction between people and their proclivity to think temporally - to make decisions in the present which reflect a belief that the future is both predictable and mutable.

This comes up in a lot of theories of innovation: growing the pie vs slicing the pie, centralized management structures focused on "efficiency" versus artist colonies focused on "creativity," Thiel's "determinate optimism" vs "indeterminate pessimism," focuses on journey versus destination, and whether to emphasize economic growth over economic redistribution.

In this case, we see a fundamental tension between throughput and priority, between efficiency and effectiveness, between theory and data, and between the present and the future.

Like with most dialectics, I suspect there is merit on both sides, but by focusing so heavily on how to most efficiently distribute the vaccine we have now, knowing what we know now, to do the most good, we're missing the point - our goal should be to develop a decision-making framework that engages with an uncertain, but predictable, future in order to do the most good over the next 12 months.

More importantly - good prioritization with low throughput is almost always far worse than high throughput with bad prioritization.

• High-throughput systems can avoid decisions - rather than deciding between two high-priority goals, a high throughput systems can do both.
• High-throughput systems can pivot faster as priorities change - forward momentum is almost always easier to redirect than the inertia of a system at rest.
• High-throughput systems produce more information - because the system is doing more, it has the capacity to learn more quickly. It spends less time in an ivory tower, more time tinkering.
• High-throughput systems are more fun for the participants - every member of a high-throughput system matters and can individually impact the goal of doing more and moving faster. Rather than simply waiting for orders from above, when the system is focused on throughput, every participant can help on the margin.

In other words - when you don't know what to do, doing anything is better than doing nothing, and building a culture of "doing" is far more important than building a culture of "waiting." Maybe people get a few extra shots, maybe we accidentally miss a few second doses, maybe we accidentally give the vaccine to someone who didn't "need it." But vaccinating the population as quickly as possible is the goal, and we should be spending as many of our human, scientific, and financial resources to get that done faster, even if that introduces some randomness and inefficiency along the way.

Observer or Participant: Can the invisible hand sow the seeds of its own destruction?

As discussed in the previous post, companies in rapidly developing markets need to run effective idea factories - organizations of extremely talented and motivated humans arranged to bring new ideas to market. While markets often reach a "peacetime" state of equilibrium in which a few key winners dominate, the transitional "wartime" state is often marked by intense competition (e.g. the Browser Wars or Cloud Wars).

This competition happens between competing idea factories as capital gets injected into a company and intellectual property comes out the other side until one of the factories achieves some kind of "moat," at which point the war concludes and the winner has a defensible business which can produce attractive profits for a long time.

Different organizations have different inherent talent - as described by Matthew Ball, Disney and HBO regularly outperform Netflix in the efficiency of their content production. And that talent is distributed between employees and the organization. But regardless of the distribution, no matter how talented the organization may be, unlike a traditional company, IP-driven companies at war still rent huge percentages of their idea factory from their employees and depend on that talent retention to continue fighting.

So what happens as the market gets involved? Investors look into the future and pick a winner - the company which they believe will emerge as one of the dominant "peacetime" players. They do this, often, by looking at momentum and velocity: which organization is moving more quickly, taking more ground, developing more features - which idea factory is more efficient?

Then they discount that victory into the present (with a historically and unsustainably low interest rate) so that capital flows into the winner. This creates a uniquely low cost of capital for the presumed victor, all but ensuring their victory. Perception becomes reality as optimistic prognostications become the assumptions that drive present value calculations. In this model, victory itself is a self-fulfilling prophecy.

But underneath all of this lies a key question about incentives: in a war that depends on human capital, where that same human capital is compensated with stock in the enterprise, what happens when investors pay the factory workers so much for the factory's potential that the market shifts from playing the passive role of an observer into an active role, as a participant.

What happens when individual employees - not founders, or even executives, begin taking home 5-10x more than they expected? Do they continue to fight with the hunger that is necessary to win? Do they keep burning with the passion that is required for true innovation? Or do they, individually and collectively, take their foot off the gas? Does the hyper-capitalization of the idea factory perversely result in a factory that becomes less capable of victory even as it becomes more expensive?

And if so, what does that mean for capitalism - if capital can destroy value, how can we insulate small teams from capital and enable them to commit to long-term change, long-term success? What types of compensation mechanisms can we develop that are more stable, that result in more self-binding, more Ulysses Pacts where liquidity is available, but without the corrosive effect of hyper-liquidity? How could we design a compensation system in which the workers had stakes in their outcomes even in excess of their investors, where by deferring liquidity today, collective organizations could agree to provide liquidity only after victory was assured?

Today, we distribute the spoils of a future war to a present-day army, and too few people have thought through the unintended consequences as newly rich soldiers quietly leave the field in the midst of battle.