DeFi Explainers

May 4, 2021 • #

I’ve gone over off the deep end the last couple weeks trying to wrap my head around DeFi. To date I’ve only dabbled in crypto, being lucky enough to ride some small waves, though nothing life-changing.

DeFi (decentralized finance) is fascinating for its disruption potential (and Ethereum platform on which it’s all built). A basic understanding of the conceptual possibilities shows this stuff is here to stay, even if not in the same form or as loud as meme-ish as it’s been over the past year.

Through Twitter I discovered a channel called Finematics that has a ton of great explainer videos walking through topics like smart contracts, the history of DeFi, NFTs, yield farming, and dozens of others on the esoteric crypto world.

Check out the full channel for the archive.

On Legibility — In Society, Tech, Organizations, and Cities

April 6, 2021 • #

This is a repost from my newsletter, Res Extensa, which you can subscribe to over on Substack. This issue was originally published in November, 2020.

In our last issue, we’d weathered TS Zeta in the hills of Georgia, and the dissonance of being a lifelong Floridian sitting through gale-force winds in a mountain cabin. Last week a different category of storm hit us nationwide in the form of election week (which it seems we’ve mostly recovered from). Now as I write this one, Eta is barreling toward us after several days of expert projections that it’d miss by a wide margin. We’re dealing with last-minute school closures and hopefully dodging major power outages. 2020 continues to deliver the goods.

There’s a lot in store for this week, so let’s get into it:

Seeing Like a State

I’ve been deep in James C. Scott’s Seeing Like a State lately, so I wanted to riff this week on Scott’s notion of “legibility,” the book’s central idea. His thesis in SLAS is that central authorities impose top-down, mandated designs on societies in order to make them easier to understand through simplification and optimization techniques. Examples in the book range from scientific forestry and naming traditions to urban planning and collectivist agriculture.

Boca Raton's legible landscape

Scott calls this ideology “authoritarian high modernism,” wherein governments, driven by a zealous belief in knowledge and scientific expertise, determine they can restructure the social order for particular gain: higher crop yields, more compliant citizenry, more efficient cities, or crime-free neighborhoods (a dangerous proposition when a “crime” is redefined at will by authorities). He’s ruthlessly critical of these ideas, as evidenced by the book’s subtitle, and presents dozens of cases of top-down-design-gone-wrong, the most extreme case being the Soviet Union’s collectivization program that led to widespread famine.

An interesting factor to think about is how and when to apply intentional design in service of legibility and control. It’s not an all good–all bad proposition, to be sure. Even though Scott levels a pretty harsh review of high modernist ideology, even he acknowledges its value in small, targeted doses for specific problems.

Legibility: A Big Little Idea

I linked to a piece a while back by Venkatesh Rao, the source where I first learned of Scott’s work.

The post is largely an introduction to the book’s themes, but adds a few interesting notes on the psychology behind legibility. Given all the history we have that demonstrates the failure rate of high modernist thinking, why do we keep doing it?

I suspect that what tempts us into this failure is that legibility quells the anxieties evoked by apparent chaos. There is more than mere stupidity at work.

In Mind Wide Open, Steven Johnson’s entertaining story of his experiences subjecting himself to all sorts of medical scanning technologies, he describes his experience with getting an fMRI scan. Johnson tells the researcher that perhaps they should start by examining his brain’s baseline reaction to meaningless stimuli. He naively suggests a white-noise pattern as the right starter image. The researcher patiently informs him that subjects’ brains tend to go crazy when a white noise (high Shannon entropy) pattern is presented. The brain goes nuts trying to find order in the chaos. Instead, the researcher says, they usually start with something like a black-and-white checkerboard pattern.

If my conjecture is correct, then the High Modernist failure-through-legibility-seeking formula is a large scale effect of the rationalization of the fear of (apparent) chaos.

Scott also points out in the book how much of the high modernist mission is driven by “from above” aesthetics, not on-the-ground results. He analyzes the work of Le Corbusier and his visionary model for futuristic urban planning, most evident in his designs for Chandigurh in India and the manufactured Brazilian capital of Brasília (designed by his student, Lúcio Costa).


While Brasília projects a degree of majesty from above, life on the street is a hollowed-out, sterile existence. Its design ignored the realities of how humans interact. Life is more complex than the few variables a planner can optimize for. It’s telling that both Chandigurh and Brasília have lively slums on their outskirts, unplanned neighborhoods that filled demands unmet by the architected city centers.

He juxtaposes the work of Le Corbusier with that of Jane Jacobs, grassroots city activist and author of The Death and Life of Great American Cities. Jacobs was a lifelong advocate of “street life,” placing high emphasis on the organic, local, and human-scale factors that truly make spaces livable and enjoyable. She famously countered the ultimate high modernist visions of New York City planner Robert Moses.

This contrast between failure in legible, designed systems and resilience in emergent, organic ones triggers all of my free-market priors. The truth is there is no “best” mental model here. Certain types of problems lend themselves well to top-down control (require it, in fact), and others produce the best results when markets and individuals are permitted to drive their own solutions. Standard timekeeping, transportation networks, space exploration, flood control — these are all challenges that are hard to address for a variety of reasons without centralized coordination.

Imposing legibility demands an appreciation of trade-offs. Yes, dictated addressing schemes and fixed property ownership documentation do enable state control in the form of taxation, conscription, or surveillance. But in exchange for the right degree of imposed structure, we get the benefit of property rights and land tenure.

Big Tech’s Legible Vision

Byrne Hobart touched on this idea in an issue of his newsletter. (The Diff is some of the best tech/business/investing writing out there, I highly recommend subscribing). He makes the point that wherever scale is required, abstraction and legibility are highly valuable. He calls up Scott’s usage of the term mētis, translated from the classical Greek to mean roughly “knowledge that can only come from practical experience.” The value of this local knowledge is Scott’s counter to legibility-seeking schemes: that practical knowledge beats the theoretical every time.

I like this point that Hobart makes, though, on seeking larger scale global maxima: that a pure reliance on the practical can leave you stuck in a local maximum:

But mētis is a hill-climbing algorithm. If it’s based on experience rather than theory, it’s limited by experience. Meanwhile, theory is not limited by direct experience. By the 1930s, many physicists were quite convinced that an atomic bomb was possible, though of course none of them had ever seen one. Because some things can’t be discovered by trial and error, but can be created by writing down some first principles and thinking very hard about their implications (followed by lots of trial and error), the pro-legibility side has an advantage in inventing new things.

He also brings up its implications in the modern tech ecosystem. The Facebooks, Googles, and Amazons are like panoptic overseers that can force legibility even on the most impenetrable, messy datastreams through machine learning algorithms and hyper-scale pattern recognition. The trade-off here may not be conscription (not yet anyway), but there is a tax. There’s an interesting twist, though: the tech firms have pushed these specialized models so far to the edge that they themselves can’t even explain how they work, thereby reconstituting illegibility:

Fortunately for anyone who shares Scott’s skepticism of the legibility project, the end state for tech ends up creating a weird ego of the mētis-driven illegible system we started with. The outer edges of ad targeting, product recommendations, search results, People You May Know, and For You Page are driven by machine learning algorithms that consume unfathomable amounts of data and output a uniquely well-targeted result. The source code and the data exist, in human-readable formats, but the actual process can be completely opaque.

Functional versus Unit Organizations

While legibility interests me in its applicability to society as a whole, I’m even more intrigued by how this phenomenon works on a smaller scale: within companies.

Org charts attempt to balance productivity and legibility, which often pull in different directions. Organizational design is driven by a hybrid need:

  1. To ship products and services to customers in exchange for revenue and equity value, and
  2. To be able to control, monitor, and optimize the corporate machine

Companies spend millions each year doing “reorgs,” often attributing execution failures to #2: the illegibility of the org’s activities. Therefore you rarely see a reorg that results in drastic cutback of management oversight.

Org Chart

Former Microsoft product exec and now-VC Steven Sinofsky wrote this epic piece a few years back comparing the pros and cons of function- and unit-based organizational structures. Each has merits that fit better or worse within an org depending on the product line(s), corporate culture, geographic spread, go-to-market, and headcount. The number one objective of an optimum org chart is to maximize value delivery to customers through cost reduction, top-line revenue gains, lower overhead, and richer innovation in new products. But legibility can’t be left out as an influence. The insertion of management layer is an attempt to institute tighter control and visibility, a degree of which is necessary to appropriately dial-in costs and overhead investment.

Look at this statistic Sinofsky cites about the Windows team’s composition when he joined:

One statistic: when I came to Windows and the 142 product units, the team overall was over 35% managers (!). But the time we were done “going functional” we had about 20% managers.

Even corporate teams aren’t immune to the pull of legibility. When its influence is stretched too far, you end up with Dilbert cartoons and TPS reports.

Emergent Order in Cities

It was serendipitous to encounter this same theme in Devon Zuegel’s podcast, Order Without Design. The show is a conversation with urbanist Alain Bertaud and his wife Marie-Agnes, an extension of his book on urban planning and how “markets shape cities.”

In episode 3 they discuss mostly sanitation and waste management in cities around the world, but my favorite bit was toward the end in a discussion on how different cities segment property into lots and dictate various uses through zoning regulation. Some cities slice property into large lots, which leads to fewer businesses and higher risk for large, expensive developments. But others, like Manhattan, segment into smaller chunks, resulting in a more diverse cityscape that mixes dining, retail, services, and many other commercial activities.

The shopping mall was an innovation that allowed developers with limited local knowledge to have tenants respond to customer demand in smaller, less risky increments. Malls in Asia notably differ from ours in the west in the breadth of goods and services they typically offer. Here’s Marie-Agnes from the episode:

…Remember the Singapore mall. In Singapore the malls have not only retail, but you find also dental offices, notaries, kindergarten schools, dispensaries, and all sorts of activities. Up to now and in general the concept of a mall in the US is for mainly shopping. You may have food court and some restaurants, but nothing like a real city where you have all sort of business.

Devon points out that this quality might make these malls more resilient to market stress than our retail-focused American versions.

Malls are by no means a modern innovation, of course. Ad-hoc congregations of commercial activity have been around for 5,000 years, evolving from purely organic bazaars of the Near East into the pseudo-planned, air conditioned behemoths we have today. Even in our technocratic culture, planners still realize that the flexibility to market demand is crucial to sustainability. Trying to pre-design and mandate a particular distribution of stores and services is a fool’s errand.

In Byrne’s newsletter, he says “once you look for legibility, you start to see it everywhere.” This has certainly been true for me as I’ve been reading Scott’s work. The deepest insights are the ones that cut widely across many different dimensions.

There’s no silver bullet in how to apply legibility-inducing schemes to any of these areas. But until you’re aware of the negative consequences, there’s no way to balance the scales between legible/designed and illegible/organic outcomes.

The Low-Code IKEA Effect

March 22, 2021 • #

I linked a few days ago to Packy McCormick’s piece Excel Never Dies, which went deep on Microsoft Excel, the springboard for a thousand internet businesses over the last 30 years. “Low-code” techniques in software have become ubiquitous at this point, and Excel was the proto-low-code environment — one of the first that stepped toward empowering regular people to create their own software. In the mid-80s, if you wanted to make your own software tools, you were in C, BASIC, or Pascal. Excel and its siblings (Lotus 1-2-3, VisiCalc) gave users a visual workspace, an abstraction layer lending power without the need to learn languages.

Today in the low-code ecosystem you have hundreds of products for all sorts of use cases leaning on similar building principles — Bubble and Webflow for websites, Integromat and Zapier for integrations, Notion and Coda for team collaboration, even Figma for designs. The strategy goes hand-in-hand with product-led growth: start with simple use cases, be inviting to new users, and gradually empower them to build their own products.

Low-code IKEA effect

Excel followed this model since the 80s: give people some building blocks, a canvas, and some guardrails and let them go build. Start out with simple formulas, create multiple sheets, cross-link data, and eventually learn enough to build your own complete custom programs.

What is it about low-code that makes it such an effective strategy? Sure there’s the flexibility it affords to unforeseen use cases, and the adaptability to apply a tool to a thousand different jobs. But I think there’s psychology at play here that makes it particularly compelling for many types of software.

There’s a cognitive phenomenon called the “IKEA effect”, which says:

Consumers are likely to place a disproportionately high value on products they partially created

IKEA is famous for its modular furniture, which customers take it home and partially assemble themselves. In a 2011 paper, Michael Norton, Daniel Mochon, and Dan Ariely wrote identified this effect, studying how consumers valued products that they personally took part in creating, from IKEA furniture, to origami figures, to Lego sets. Other studies of effort justification go way back to the 1950s, so it’s a principle that’s been understood, even if only implicitly, by product creators for decades.

Low-code tools express this effect, too, showing that customers are very willing to participate in the creation process if they get something in return. In the case of IKEA it’s more portable, affordable furniture products. In low-code software it’s a solution tailored to their personal need. Paradoxically, putting additional effort into a product through self-service, assembly, or customization generates a greater perception of value than consumer being handed an assembled, completed product.

SaaS companies should embrace this idea. Letting the customer take over for the “last mile” can be wins all around for everyone. Mutual benefits accrue to both creator and consumer:

  • Customers have a sense of ownership when they play a role in building their own solution.
  • The result can be personalized. In business environments, companies want an added touch of differentiation, to set themselves apart from competitors. They don’t want commodities that any other player can simply buy and install.
  • Production costs are reduced. The creator builds the toolbox (or parts list, instructions, and tool kit) and lets the consumer take it from there. Don’t have to spend time understanding the nuances of hundreds of different use cases. Provide building blocks and let recombination generate thousands of unique solutions.
  • Increased retention! Studies showed that consumers consistently rated products they helped assemble higher in value than already-assembled pieces. This valuation bias manifests in retention dynamics for your product: if customers are committed enough and build their own solution, they’ll more likely imbue it with greater value.

The challenge for creators is to balance that “just-right” level of customer participation. Too much abstraction in your product, requiring too much building of primitives, and the customer is unlikely to have the patience to work through it. Likewise, when you buy an IKEA table, you don’t want to be sanding, painting, or drilling, but snapping, locking, and bolting are fine. Success is a key criteria to get the positive upside. From the Wikipedia page:

To be sure, “labor leads to love only when labor results in successful completion of tasks; when participants built and then destroyed their creations, or failed to complete them, the IKEA effect dissipated.” The researchers also concluded “that labor increases valuation for both ‘do-it-yourselfers’ and novices.”

Participation in the process creates a feedback loop: the tool adapts to the unique circumstances of the consumer, functions as a built-in reward, and the consumer learns more about their workflow in the process.

Low-code as a software strategy allows for a personalization on-ramp. Its IKEA effect gives customers the power to participate in building their own solution, tailoring it to their specific tastes along the way.

Weekend Reading: American-Dream-as-a-Service, Content Marketing, the Fifth Column Reading List, and More

March 20, 2021 • #

👨‍🎓 The American-Dream-as-a-Service

Antonio Garcia-Martinez interviews Austen Allred, founder of Lambda School. Lambda charges no tuition and builds its program on the ISA (income sharing agreement), in which you only pay when you get a salaried position in your field of study.

The cool thing about the incentive alignment is that we’re not going to train you to be a sociologist, because it just doesn’t work. A common critique of the ISA model is: oh, now people aren’t going to study poetry anymore. And my response to that is: yeah, we’re not a university, we’re a trade school. The university has 18 million things that it does for you, and we cut cut off a tiny sliver of that, which is: we’re going to help you get a better job, we’re going to help you improve your state in life. That’s all we do.

There are actually more high-paying jobs available than there are people to fill those roles. And that’s true all over the place. I think about it as an optimization problem. You’ve got all this latent human potential, and it’s just kind of bouncing around. Sometimes it goes to school, and it picks stuff at random to study, and you know what you know because of who you’re surrounded by.

📝 Content-Driven Growth

Lenny Rachitsky gets into different types of content marketing by startup, plotted on two dimensions: user-generated to editorial, and vitality-driven to SEO-driven. Useful structure here for thinking about where you want to be and what types of content and tactics fit.

🌍 Earth at a Cute Angle

Some great examples of oblique satellite imagery. Love the shots of the Tour’s mountain passes — Col du Galibier and Tourmalet.

📖 Fifth Column Podcast Reading List

Someone in the Fifth Column podcast community put together an archive of all the books mentioned on the show over the years. This’ll greatly extend the reading list, nice mix of classics and modern stuff.

💻 Microsoft Power Fx

Microsoft has open-sourced its simplistic formula language based on Excel.

Hammock-Driven Creativity

March 2, 2021 • #

Here’s Rich Hickey (creator of Clojure) on the benefits of stepping away from the computer, in his talk on “hammock-driven development”:

He differentiates what the “waking” mind and “background” mind are good at, which I’d interchangeably refer to as the “at the desk” mind and the “away from the computer” mind:

  • Waking mind:
    • Good at critical thinking; analysis, tactics
    • Prone to finding local maxima
    • Can feed work to the background mind
  • Background mind:
    • Good at making connections
    • Synthesis; strategy; abstractions and analogies
    • You can only feed it, not direct it

For anyone in a critical thinking-based market, I’m sure this rings accurate. Think about how we refer to eureka moments popping into our heads — ”shower thoughts”. This idea that we can “only feed it, not direct it” does feel true. For me the most interesting ideas don’t result from me saying “okay, it’s time to think about things” and writing down the result.

Hammock-driven creativity

When I’m working on something, it’s challenging to get “unstuck” while sitting at my desk. Some days I can get in the zone, but most of the time the zone eludes me. It’s not even the active distractions of Slacks, meetings, and email (though those are never-ending), but temptation from the no-kidding thousands of individual little shiny threads to follow.

But then when I’m out for a walk, a run, or driving somewhere, thoughts and ideas abound. And of course I’m never in a good position to take notes or jump right into writing or doing anything about them at the time. My post from last year on Downtime Thinking looked at my experience with this phenomenon. I’ve experimented with techniques for bringing these modes closer together. Too many interesting ideas are lost in the transition between waking and background brain modes.

Hammock-driven creativity helps the mind jar loose from its normal working context. Environment is a strong contributor to controlling your behavior. For myself, my “normal” work environment — sitting at my desk, keyboard and mouse in hand, multiple monitors available — is associated in my brain with dozens of activities other than creative or critical thinking. I’ve experimented lately with “morning pages” as a mechanism working on the writing habit. Start a timer and do nothing but write free-form for 25 minutes. I’m having mixed success with it much of the time, but occasional sessions lead to solid ideas, and I’ll blow past my time commitment promise.

If I can combine the intentionality of morning pages with a minor change of scenery, the forces could combine into a productive combo.

In a recent interview, Jerry Seinfeld described his writing sessions, a brilliantly simple practice:

I still have a writing session every day. It’s another thing that organizes your mind. The coffee goes here. The pad goes here. The notes go here. My writing technique is just: You can’t do anything else. You don’t have to write, but you can’t do anything else. The writing is such an ordeal.

I love that: “You can’t do anything else. You don’t have to write, but you can’t do anything else.”

Setting the table for the writing session triggers the Pavlovian mode: “this is writing time.” Then you’ve got the intention, that you can’t do anything else. And I love how he gives himself the leeway to not even write! But in exchange for the freedom for work-avoidance, your only other option is staring at the wall.

Jobs Clubhouse Does

February 23, 2021 • #

If you’re on the internet and haven’t been living under a rock for the last few months, you’ve heard about the startup Clubhouse and its explosive growth. It launched around the time COVID lockdowns started last year, and has been booming in popularity even with (maybe in-part due to?) an invitation gate and waitlist to get access.

The core product idea centers around “drop-in” audio conversations. Anyone can spin up a room accessible to the public, others can drop in and out, and, importantly, there’s a sort of peer-to-peer model on contributing that differentiates it from podcasting, its closest analog.


I got an invite recently and have been checking out sessions from the first 50 or so folks I follow, really just listening so far. Their user and growth numbers aren’t public, but from a glance at my follow recommendations I see lots of people I follow on Twitter already on Clubhouse.

They recently closed a B round led by Andreessen Horowitz, who also backed the company in its earlier months last year. Any time an investor does successive rounds this quickly is an indicator of magic substance under the hood, signals that show tremendous upside possibility. In the case of Clubhouse, user growth is obviously a big deal — viral explosion this quickly is always a good early sign — but I’m sure there are other metrics they’re seeing that point to something deeper going on with product-market fit. Perhaps DAUs are climbing proportional to new user growth, average session duration is super long, or retention is extremely high (users returning every day).

On the surface a skeptical user might ask: what’s so different here from podcasts? It’s amazing what explosive growth they’ve had given the similarities to podcasting (audio conversations), and considering its negatives when compared with podcasts. In all of the Clubhouse rooms I’ve been in, most users have telephone-level audio quality, there’s somewhat chaotic overtalk, and “interestingness” is hard to predict. With podcasts you can scroll through the feed and immediately tell whether you’ll find something interesting; when I see an interesting guest name, I know what I’m getting myself into. You can reliably predict that you’ll enjoy the hour or so of listening.

Whenever a new product starts to take off like this, it’s hitting on some aspect of latent user demand, unfulfilled. What if we think about Clubhouse from a Jobs to Be Done perspective? Thinking about it from the demand side, what role does it play in addressing jobs customers have?

Clubhouse’s Differentiators

Clubhouse describes itself as “Drop-in audio chat”, which is a stunningly simple product idea. Like most tech innovations of the internet era, the foundational insight is so simple that it sounds like a joke, a toy. Twitter, Facebook, GitHub, Uber — the list goes on and on — none required invention of core new technology to prosper. Each of them combined existing technical foundations in new and interesting ways to create something new. Describing the insights of these services at inception often prompted responses like: “that’s it?”, “anyone could build that”, or “that’s just a feature X product will add any day now”. In so many cases, though, when the startup hits on product-market fit and executes well, products can create their own markets. In the words of Chris Dixon, “the next big thing will start out looking like a toy”.

Clubhouse rides on a few key features. Think of these like Twitter’s combo of realtime messaging + 140 characters, or Uber’s connection of two sides of a market (drivers and riders) through smartphones and a user’s current location. For Clubhouse, it takes audio chat and combines:

  • Drop-in — You browse a list of active conversations, one tap and you drop into the room. Anyone can spin up a room ad-hoc.
  • Live — Everything happening in Clubhouse is live. In fact, recording isn’t allowed at all, so there’s a “you had to be there” FOMO factor that Clubhouse can leverage to drive attention.
  • Spontaneous — Rooms are unpredictable, both when they’ll sprout up and what goes on within conversations. Since anyone can raise their hand and be pulled “on stage”, conversation is unscripted and emergent.
  • Omni-directional — Podcasts are one-way: from producer to listener, or some shows have “listener mail” feedback loops. Clubhouse rooms by definition have a peer-to-peer quality. They truly are conversations, at least as long as the room doesn’t have 8,000 people in it.

None of these is a new invention. Livestreaming has been around for years, radio has done much of this over the air for a century, and people have been hosting panel discussions since the time of Socrates and Plato. What Clubhouse does is mix these together in a mobile app, giving you access to live conversations whenever you have your phone plus connectivity. So, any time.

Through the Lens of Jobs

Jobs to Be Done focuses on what specific needs exist in a customer’s life. The theory talks about “struggling moments”: gaps in demand that product creators should be in search of, looking for how to fit the tools we produce into true customer-side demand. It describes a world where customers “hire” a product to perform a job. Wherever you see products rocketing off like Clubhouse, there’s a clear fit with the market: users are hiring Clubhouse for a job that wasn’t fulfilled before.

Some might make the argument that it’s addressing the same job as podcasts, but I don’t think that’s right exactly. For me it has hardly diminished my podcast listening at all. I think the market for audio is just getting bigger — not a zero-sum taking of attention from podcasts, but an increase in the overall size of the pie. Distributed work and the reduction of in-person interaction and events has amplified this, too (which we’ll get to in a moment, a critical piece of the product’s explosive growth).

Let’s go through a few jobs to be done statements that define the role that Clubhouse plays in its users’ lives. These loosely follow a format for framing jobs to be done, statements that are solution-agnostic, result in progress, and are stable across time (see Brian Rhea’s helpful article on this topic).

I’m doing something else and want to be entertained, informed, etc.

Podcasts certainly fit the bill here much of the time. Clubhouse adds something new and interesting in how lightweight the decision is to jump into a room and listen. With podcasts there’s a spectrum: on one end you have informative shows like deep dives on history or academic subjects (think Hardcore History or EconTalk) that demand attention and that entice you to completionism, and on the other, entertainment-centric ones for sports or movies, where you can lightly tune in and scrub through segments.

The spontaneity of Clubhouse rooms lends well to dropping in and listening in on a chat in progress. Because so many rooms tend to be agendaless, unplanned discussions, you can drop in anytime and leave without feeling like you missed something. Traditional podcasts tend to have an agenda or conversational arc that fits better with completionist listening. Think about when you sit down with Netflix and browse for 10 minutes unable to decide what to watch. The same effect can happen with podcasts, decision fatigue on what to pick. Clubhouse is like putting on a baseball game in the background: just pick a room and listen in with your on-and-off attention.

Ben Thompson called it the “first Airpods social network”. Pop in your headphones and see what your friends or followers are talking about.

I have an idea to express, but don’t want to spend time on writing or learning new tools

Clubhouse does for podcasting what Twitter did for blogs: massively drops the barrier to entry to participation. Setting up a blog has always required some upstart cost. Podcasting is even worse. Even with the latest and greatest tools, publishing something new has overhead. Twitter lowered this bar, only requiring users to tap out short thoughts to broadcast them to the world. Podcasting is getting better, but is still hardware-heavy to do well.

There’s a cottage industry sprouting up on Clubhouse of “post-game” locker room-style conversations following events, political, sports, television, even other Clubhouse shows. This plays well with the live aspect. Immediately following (or hell, even during) sporting events or TV shows, people can hop in a room and gab their analysis in real time.

Clubhouse’s similarities to Twitter for audio are striking. Now broadcasting a conversation doesn’t require expensive equipment, audio editing, CDNs, feed management. Just tap to create a room and notify your followers to join in.

I want to hear from notable people I follow more often

This one has been true for me a few times. With the app’s notifications feature, you can get alerts when people you follow start up a room, then join in on conversations involving your network whenever they pop up. I’ve hopped in when I saw notable folks I follow sitting in rooms, without really looking at the topic. For those interesting people you follow that you make sure to listen to, Clubhouse expands those opportunities. Follow them on Clubhouse and drop in on rooms they go into. Not only can you hear more often from folks you like, you also get a more unscripted and raw version of their thoughts and ideas with on-the-fly Clubhouse sessions.

I want to have an intellectual conversation with someone else, but I’m stuck at home!

Or maybe not even an intellectual one, just any social interaction with others!

This is where the timing of Clubhouse’s launch in April of last year was so essential to its growth. COVID quarantines put all of us indoors, unable to get out for social gatherings with friends or colleagues. Happy hours and dinners over Zoom aren’t things any of us thought we’d ever be doing, but when the lockdowns hit, we took to them to fill the need for social engagement. Clubhouse fills this void of providing loose, open-ended zones for conversation just like being at a party. Podcasts, books, and TV are all one-way. Humans need connection, not just consumption.

COVID hurt many businesses, but it sure was a growth hack for Clubhouse.

Future Jobs to Be Done?

Products can serve a job to be done in a zero- or positive-sum way. They can address existing jobs better than the current alternatives, or they can expand the job market to create demand for new unfulfilled ones. I think Clubhouse does a bit of both. From first-hand experience, I’ve popped into some rooms in cases when I otherwise would’ve put on a podcast or audiobook, and several times when I was listening to nothing else and saw a notification of something interesting. Above are just a few of the customer jobs that Clubhouse is filling so far. If you start thinking about adjacent areas they could experiment with, it opens up even more greenfield opportunity. Offering downloads (create a custom podcast feed to listen to later?), monetization for organizers and participants (tipping?), subscription-only rooms (competition with Patreon?). There’s a long list of areas for the product to explore.

Where Does Clubhouse Go Next?

There’s a question in tech that’s brought up any time a hot new entrant comes on the scene. It goes something like:

Can a new product grow its network or user base faster than the existing players can copy the product?

This has to be at the forefront of the Clubhouse founders’ minds as their product is taking off. Twitter’s already launched Spaces, a clone of Clubhouse that shows up in the Fleets feed. That kind of prominent presentation to Twitter’s existing base adds quite the competitive threat, though Twitter isn’t known for it’s lightning-quick product innovation over the last decade. But maybe they’ve learned their lesson in all their past missed opportunities. What could play out is another round of what happened to Snap with Stories, a concept that’s been copied by just about every product now.

Clubhouse is doing a respectable job managing the technical scalability of the platform as it grows. The growth tactics they’re using with pulling in contacts, while controversial, appear to be helping to replicate the webs of user connections. The friction in building new social interest graphs is one of the primary things that’s stifled other social products over the last 10 years. By the time new players achieve some traction, they’re either gobbled up by Twitter or Facebook, or copied by them (aside from a few, like TikTok). Can Clubhouse reach TikTok scale before Twitter can copy it?

There are still unanswered questions on how Clubhouse’s growth plays out over time:

  • How far can it reach into the general public audience outside of its core tech-centric “online” crowd?
  • Like any new network-driven product, when it’s shiny and new, we see a gold rush for followers. What behaviors will live chat incentivize?
  • How will room hosts behave competing for attention? What will be the “clickbait” of live audio chat?
  • What mechanisms can they create for generating social capital on the network? How does one build an initial following and expand reach?

Right now, the easiest way to build a following on Clubhouse is just like every other social network’s default: bring your already-existing network to the platform. It’s a bit early to see how Clubhouse might address this differently, but most of the big time users were folks with large followings on Twitter, YouTube, or elsewhere. It’d be cool to see something like TikTok-esque algorithm-driven recommendations to raise distribution for ideas or topics even outside of the follower graphs of the members of the rooms.

Clubhouse (and this category of live multi-way audio chat) is still in the newborn stages. As it matures and makes its way to wider audiences outside of mostly tech circles, it’ll be interesting to see what other “jobs” are out there unfilled by existing products that it can perform.

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