Newsletters, Bundles, and Indie Publishing

August 14, 2020 • #

In his latest issue of The Diff, Byrne Hobart looks the economic models behind the boom in independent publishing and unbundling of analysis and journalism happening on platforms like Substack:

Bundles tend to grow until they reach a highly profitable mature state—at which point any change in the underlying audience, or the availability of competing products, seriously weakens their economics. The bigger a bundle gets, the more likely it is that a subset of users are all paying for basically one piece of the bundle, which could be sold separately at a better price. And as soon as a bundle is partially unbundled, there are two options: stop offering the part of the bundle that now has a competing single-purpose product, at which point the bundle switches from optimally-priced to overpriced, or keep offering it and accept lower margins. Bundles grow gracefully and shrink painfully.


There’s been talk in the tech world about a newsletter bubble, that readers have too many, can’t read them, and won’t be able to afford to pay for them. Some worry that we’re simply moving from the bundled world of old media to a fragmented space with hundreds of indies to have to subscribe to. Not unlike going from a $70/mo subscription to a Comcast cable bundle to a sum of 7 different $10-15/mo streaming services. They’re going over-the-top only to result in me paying the same thing for entertainment as before1. For written content, we once had to subscribe to the entire Washington Post or Wall Street Journal for writers we enjoy, bringing along “the rest” against our will. Now we can follow our preferred writers directly on their own properties.

In the case of journalism and written analysis, looking at it through only the cost lens is too simplistic. I’m a paid subscriber to 4 or 5 different independent writers’ newsletters, paying a sum greater than I did in total previously for all news subscriptions. But I’m getting a product that wasn’t even on offer in the old world model. Not to mention the freedom and range of motion it affords the writer to explore topics on the edges of their interest. Whatever they’re interested in they can explore, no need to stay in a particular lane to conform to the institutional menu.

I think a natural development we’ll see is new institutions forming around these publications, starting out with an independent writer or two and gradually expanding into larger operations. The Dispatch is at the top of the leaderboard on Substack, and they’re in the early days of building a company around it — destined to expand beyond the few core folks writing there today.

I like and generally support the idea of unbundling, with writers branching out to specialize in niches. This is what the internet has always been great for. Even with the novelty of newsletters as they’re discussed in media, the model is strikingly similar to what we had in the 2000-2006 era of blogs, with independent writers building up their own followings and revenue. What we didn’t have back then were healthy (and stable) income streams — it was mostly ad-driven, which is volatile, irritating to readers, and full of temptation to dabble in other less-than-savory means of making money. I don’t think the financial piece was the biggest problem; the tech was also still new and a high barrier to entry for many professional writers. Tools like Substack give consistency in revenue through subscription, no need to muck with advertisers, and simple publishing tools for dealing with subscriber management, authoring, and email delivery.

The more the space expands, though, the more discoverability will be key. Interesting writers getting a byline at the LA Times get sudden exposure if they can break through to getting a piece published. What does that breakthrough process look like in the indie publishing world? Algorithmic feeds of posts based on interests? Suggestions of complementary publications based on your current subscription list? Would it happen at the post level or publication level? Will someone build an aggregator service to bubble up the best stuff? It would be cool if all a writer needed to do was to write something interesting and have it be “picked up” in the right feed2.

I’m curious to see what kinds of bundles could be created from a decentralized network of long-form indie publications. If Byrne Hobart writes his own property on economics and business, as do Ben Thompson and Matt Levine in their own ways, could they form a “co-op”-like offering into which they each cross-post a selection of their work? If I didn’t want to pay $10/mo for each of them, maybe I could pay $15/mo and get a mixture of writings from each writer of their choosing. Medium’s Publication product works in a similar way technically, but I don’t know how it works from a monetization perspective. A sort of reconstitution of the bundle, but packaged in different recipes for different tastes.

Even if it feels like there’s a glut of newsletters out there to pick from and too much to read, I’d categorize it as a fantastic problem to have and improve upon. Diversity and experimentation are overdue since the heyday of blogs waned after Twitter and Facebook took over everyone’s attention. Big institutional media companies have only gotten less varied over the years, and few of them have figured out how to stay in business. It’s great to see so many independent writers and intellectuals able to drive a good living off of their ideas, creating “monopolies of one”:

Bundling reacts to differentiated desires by creating a less differentiated publication that’s fairly valuable to everyone. But as the cost of the reader’s time rises, focus pays off. And the subscription newsletter model makes it easier than it’s ever been to profitably focus on exactly one topic, and build a one-person monopoly.

  1. Granted, the quality and feature set might be better with on-demand and the available content catalog, but there’s still the downside of needing a suite of different apps of variable quality. And also having to realize which show is on what service. 

  2. Perhaps social media feeds fill this hole right now. And for newsletters, things like forwards to friends, etc. 

The State of Distributed Work

August 12, 2020 • #

Like most teams, we’ve now been fully remote and distributed since March 13th, almost 5 months exactly after moving a team of 50+ to fully remote, with no upfront plan on how to best organize ourselves.

About 20 of our team was already remote (scattered across the lower 48) before the COVID lockdown started, but several of them were in the office fairly regularly. But that still leaves 30+ that were forced to figure out a remote work setup overnight. Even the previously remote staff had to get used to changes in communications with the rest of the team adjusting in-flight.

So what’s worked and what hasn’t? What’s the overall impact been?

My general view is that it hasn’t impacted productivity overall in a terribly material way. After a few weeks to find stability with the work-from-home reality, things settled into a regular cadence for the most part. Aside from many of us with kids and other home impacts having to manage solutions for school closures, e-learning Zoom classes, and cabin fevered children, the work cycle leveled off into a predictable flow.

Zoom life

Zoom fatigue is a serious thing. I don’t think we’re having more meetings or conversation on a minute-to-minute basis, but as many have pointed out during this lockdown, there’s something different about voice and video interaction that absorbs more energy, draws greater attention bandwidth, or something. It also seems that with all people remote, there’s a bit of a creeping tendency to inflate invitation lists and make meetings bigger than their in-person versions would be. No hard evidence of this, but it feels like we’ve got a higher average people-per-meeting than pre-quarantine. And for me, the more heads on the Zoom session, the more draining it tends to be.

Being on persistent video doesn’t help, since it pressures you to sit still and be visible in the frame, when in person we’d often be up and about, at the whiteboard, leaning back in chairs, or getting something from the fridge. We haven’t had enough time yet to develop the social norms about what’s acceptable and not while on remote calls. Personally, I’m inclined toward seeing other people and having them see me, since we’re all starved for the ability to interact face to face, but perhaps over time we’ll work out some norms about when it’s expected to be present at the desk and when voice-only would suffice.

Documents, artifacts, and async work

With collaboration, we’ve been far less impacted than I expected. We’ve been able to make do. Most product design groups live and breathe by sketching, drawing, or whiteboarding ideas, and I’ve yet to find any good distributed digital methods for replacing the exploratory process of sketching something out in a group setting. I’ve done a few Zoom calls where I’ll screenshare the iPad with Concepts open. It’s excellent that we’ve got tools like this today to do visual collaboration without too much friction, but it’s still very one-way — iPad sketcher is drawing, but others can’t “take a pen” themselves and add to it like they would at a whiteboard. I’m sure someone will develop a live Google Docs-like multiplayer sketchboard to fill this need (hint: someone please do this!).

Even in pre-COVID times, most of the company has always been pretty solid with asynchronous work. Things are facilitated through Slack as a foundational communication layer, then plenty of collaborative Google Docs and Sheets on top of that for interactive work. We recently set up Confluence, too, where we want to have a better central location for content — like an internal blog and a place that’s better for collaborative work on documents than Docs. The truth here is that there’s no shortage of tooling to help teams with async work; it’s a human behavior and comfort problem to get everyone in the right tempo of working this way.


One of the biggest benefits of co-located teams is the random hallway interaction you get that’s very hard to replicate remotely.

In some ways removing the random hallway chatter is what we often long for — a way to add more time to our day for deep work. But lots of hallway chatter results in not only human social connection, but also real work discussion and idea exchange. There still doesn’t seem to be a good mechanism to replace what gets lost here when you’re distributed. You do recover some productivity with more time for deep work (if you can keep the meeting-creep down), but it’s less clear what longer-term detriments there will be on the ideas never discovered or pursued that result from those random encounters. For a couple months some of us were doing regular “social hour” Zooms to fill this void. They were great for maintaining interpersonal connections, but didn’t solve the problem for new product ideas or work topics.

It still remains to be seen how many companies return to full in-person work models after all of this settles down. I’m sure many will go back to something almost resembling the pre-shelter model, but I’d bet that there’s plenty of residual work-from-home that’ll happen even in the most face-to-face-leaning organizations. Over time we’ll surely all adapt to some sort of regular pattern, hopefully landing on something more effective than we had before. I know that hybrid models have shown poor results in the past, but I think there’s a way to get to a place like that that works for everyone, now that we’re all subject to the same costs and benefits of working remotely.

Go-to-Market Fit

August 10, 2020 • #

I recently watched this Mark Roberge session where he had an interesting way of describing the challenge that follows product-market fit. Tons of startup literature is out there talking about p-m fit. And likewise there’s plenty out there about scaling, leadership, and company-building. One of the most fascinating stages is in between, what he calls “go-to-market fit.” This is where you’ve found some traction and solved a problem, but haven’t figured out how to do it efficiently. Here’s how you think about the key goals in each phase:

  • Product-market fit: customer retention
    • If you can attract users but they don’t stick around, you aren’t yet solving a painful problem (assuming you haven’t let pricing and other things get in the way)
  • Go-to-market fit: scalable unit economics
    • You know you’re there when you can repeatably deliver something valuable scalably and profitably

In each of these cases the real measurement lags your execution, so you need to find a proxy metric that predicts the goal number.

You can find metrics that are predictive signals of retention, but they’ll shift from product to product pretty widely. Things like active sessions, session lengths, sign in frequency, time-in-app, and the like can track with likelihood to stick around, but you’d have to experiment with ways to measure this if you’re in pre-product-market fit territory.

To predict go-to-market fit, you should know what a set of scalable and profitable metrics look like for your business. If you set down your target unit economics, like the LTV:CAC ratio (Mark uses the industry-common 3:1 as an example), you can work backwards to daily behaviors you can orient your team on to see how sustainable your pricing, packaging, and positioning are. It might take some experimentation given the acceptable goals would vary by company, but what you want to do is pick things you can measure quickly, like driving all the way down to leads per day, so you can adapt and change your tactics to zero in on what works. Waiting around for longer “actuals” to come back from accounting on your revenue means you can’t change quickly enough to sustain unprofitable models long enough to figure it out.

We often think a lot about product-market fit stage being the fast and loose experimental phase of a startup, but what Mark makes clear here is experimentation doesn’t stop — it merely shifts from product and customer success to sales and marketing. Though the tighter all these areas work together to experiment, the better the results.

Weekend Reading: Commercial Imagery, Proof Mechanisms, and Cinematic Universes

August 8, 2020 • #

🌏 The Commercial Satellite Imagery Business Model is Broken

My friend Joe Morrison’s latest is an extended rant on the commercial satellite imagery market, and a plea to that industry to rethink how they might improve their go-to-market approaches for selling to commercial businesses.

I can vouch for his account of what it’s like to work with a commercial provider first-hand. Their business models make it challenging to go direct-to-customer, even at fairly high price tags. Until they can lower the barrier to entry into the two- or three-figure territory for acquiring any imagery, I don’t see the market widening very much farther beyond the use cases commonly addressed today. It’s not just pricing, though; they need self-service, automated delivery mechanisms to get the scale economics working.

It’s still too niche of a business, to me, to be truly realized at SMB/mass market level. Perhaps the continued convergence of gaming tech, mapping, and imagery data will create new use cases and customers to ramp demand high enough to motivate some of what Joe is asking for.

📑 Proof of X

Julian Lehr’s latest essay addresses proof mechanisms in internet services. How proof points relate to signaling. When new social networks emerge they have to introduce new proof mechanisms to differentiate themselves from existing incumbents. These can either be novel proof-of-creative-work hurdles or completely new proof-of-x mechanisms.

Also check out his previous related article on Signaling as a Service.

🎥 Cinematic Universes Aren’t New; They’re the Oldest Stories on Earth

The entertainment industry’s fascination with fantasy, science fiction, and superhero properties is giving people what they’ve wanted for thousands of years: epic, interconnected stories like those of Greek, Norse, and eastern mythologies:

At the core of our current fascination with the MCU or the Star Wars Galaxy is a fascinating fact: they resemble the epic stories that dominated human culture for thousands of years. They tell stories that feature countless characters, each one serving a role as part of an vast story, authored by scores of unknown writers and slowly shaped by audiences, each of whom could explain - if not detail - the particulars of these universes.

I’m currently making my way through Stephen Fry’s Mythos, his retelling of Greek mythology. The parallels between ancient myth and modern fictional universes like Marvel and Star Wars are striking, especially when you get to read them in a contemporary style from an author like Fry.

Readwise, Books, and Spaced Repetition

August 7, 2020 • #

In his piece “Why Books Don’t Work,” Andy Matuschak made a strong case that books are a poor medium for knowledge transfer. Even with the most advanced book experiences today (like digital ebook downloads to a Kindle), if you took away the digital e-ink screen, a reader from the 16th century would still recognize books as no different than what they had. We’ve added digital on-demand access, dictionary lookups, and the ability to have a library in your pocket1, but the fundamental model for conveying the knowledge is still what Gutenberg would recognize, based on the “transmissionism” mode of teaching.

Spaced repetition

Matuschak quotes this great passage from Carl Sagan in Cosmos:

What an astonishing thing a book is. It’s a flat object made from a tree with flexible parts on which are imprinted lots of funny dark squiggles. But one glance at it and you’re inside the mind of another person, maybe somebody dead for thousands of years. Across the millennia, an author is speaking clearly and silently inside your head, directly to you. Writing is perhaps the greatest of human inventions, binding together people who never knew each other, citizens of distant epochs. Books break the shackles of time. A book is proof that humans are capable of working magic.

Knowledge is transmitted, as if by magic, across the decades and centuries. This makes it all-the-more unfortunate how bad our brains are at retaining all that information. We have a mechanism for cheap, reliable knowledge transfer, yet are still bad at hanging onto that knowledge.

One can also be reading books for enjoyment. The act of reading itself can be fun, even if the signal strength of retention is less than perfect. Fiction is like this, of course, where the primary goal is entertainment, not education. Not that there’s no wisdom embedded in fiction — in fact, I would make a case that fiction offers deep insights worthy of remembering2. But I even see nonfiction works on my shelf that I remember enjoying years ago that I’ve mostly forgotten about, certainly in any conscious way that’s useful to me.

The defining purpose of nonfiction, though, is to educate, to convey ideas in a way that disseminates them to a wide audience and allows wisdom to compound over years by connecting dots in readers’ minds. Writers spend hundreds of hours distilling their ideas into works of a few hundred pages that we blaze through in a couple of weeks, retaining little.

Spaced repetition

Purely linear transmission is not the best model for understanding, but it’s the best that we have available to us today, cheaply and readily accessible. People like Andy Matuschak and his collaborator Michael Nielsen are busy behind the scenes working on this problem of how to build tools for thought that can harness the novel advantages of today’s technology. They experimented with this idea in their project, using the complex subject of quantum computing combined with a “mnemonic medium” that integrated spaced repetition testing. The results they’ve shown from this experiment are promising evidence for the technique to increase retention. It’s a simple approach — interspersing simple questions within the text — but the problem is one of medium. Our existing reading and teaching tools don’t have affordances for this today.

Until we make headway in those new areas, what can we do to get more out of reading? How can we extract and retain the right ideas from what we read without having to reinvent the nature of books themselves?

Enter Readwise

One of the most useful tools I’ve discovered in the past year is Readwise, a service that’s working to solve this problem and enhance reading retention through a simple workflow:

  • Readwise syncs your highlighted passages from Kindle, web articles, and even tweets
  • See a sampling of those highlights in your inbox each day for review, through email or their mobile app (what they call your “Daily Readwise”)
  • Highlights are selected randomly from your archive, and can be resurfaced with whatever regularity you prefer

It’s such a simple idea that, like all great innovations, makes the most of the pre-existing infrastructure around it. The goal is to help readers retain what they read. I love it because of how simple it is. Readers like me aren’t looking for something scientific or complex; even an incremental improvement in reading comprehension and recall is enough to enhance the overall nonfiction reading experience.

Because I read so much and highlight copiously, my Readwise has over a hundred books, each with dozens (if not hundreds) of highlighted passages. At last check I have around 5,000 highlights in the archive. As they come through in each day’s review, I regularly get to see things I highlighted years ago from books I sometimes barely remember reading. There have been numerous times where a passage has spurred me to go and re-download the book on my Kindle and skim back through. This trigger is exactly what I want out of a service like this: a reason to be more diligent in reading practice, highlighting, and regular review. Just in the past year or so of using it, I’ve been able to dredge quite a bit of fleeting knowledge back up into memory. Without a service like Readwise (even with highlighting), it’s highly unlikely I’d ever remember much more than a two-sentence synopsis of most books in my library.

Readwise follows a spaced repetition model for increasing recall. True spaced repetition systems use specific algorithms to extend the time between recall tests (like the Leitner system). For example, you might first get quizzed on an item a day after first being shown it, and if your answer is correct, then you’ll be asked again in 5 days, 10 days, et cetera. The correct/incorrect answer provides a feedback loop to the algorithm to best estimate the spacing for resurfacing it again.

Tuning your reviews

Since not all the books in your archive are of equal importance to you, you can tweak the frequency that highlights are resurfaced on a per-book basis. I only have a couple in my library that I’ve turned down. Usually the quantity of highlights in a book is a good proxy for how interested I am in retaining info from it, so books with very few highlights are already less likely to appear in the daily batch. You can also dial in the preferences for new versus old books. You can have it favor more recent reads to review information while the reading is fresh, or favor pulling up more items from farther back in time.

Tuning your Readwise reviews


The most commonly used integration is probably their Kindle sync service. It’s certainly the most high-volume for me. But in addition Readwise can sync from iBooks, and even has a slick camera-based OCR tool for clipping sections from physical books3. You can also pull in highlights articles through Pocket and Instapaper, and even save tweets or threads to include in your reviews. They’ve also got a super slick integration with Notion, if that’s something you’re interested in.

Active recall

A key feature related to the native concept of spaced repetition is Mastery mode, which allows you to generate flashcard-like questions from specific highlights. On each highlight shown in review, you can add it to your Mastery catalog, either generating a question & answer flashcard or a fill-in-the-blank version of the quote (a technique known as cloze deletion). I only do this for concrete statistics and facts that I find notable enough to want to remember. Depending on the types of works you read most frequently, though, this could be incredibly helpful, especially for content like digital textbooks.

In my now-hundreds of Daily Readwise reviews, there have been countless times that a highlight pulled up from the archives has prompted a thought or idea that I jotted down in my notes. Occasionally they’ve even spurred such deep thinking (usually because I see it in a moment of already thinking about a similar idea) that I haul off and write a blog post from it. This for me is the one of Readwise’s core values. Since writing is a medium for learning, a tool in the belt that helps you synthesize ideas for writing is a powerful one.

Readwise has been in everyday usage around here. I recently had a 110 day streak that I broke a week ago, but still I make it a point to pop it open every day when I get the morning push alert and flip through the clips it assembles.

Future Ideas

One unsolved (and maybe unsolvable) area is a way to address audiobooks. Certainly the technologies exist to do playback, capture, and speech-to-text transcription, but it’s a question of integrating these all together in a system that would work. Audible is the largest player by far, but it generally has poor support for integrations of any type, and also generally innovates at a snail’s pace. I’m not familiar with other audiobook players, but maybe one day there’ll be a way for a new entrant to encroach on Amazon’s monopoly in this space.

For podcasts there’s a new player called Airr that’s doing something interesting with this, using a feature they call “AirrQuotes.” It allows you to clip a segment of audio from a podcast, along with the text transcript to send to another app. I could see a future integration here where you could have podcast clips automatically transcribed and added to your Readwise archive. (Update: Airr integration is now live within the Airr app, like they’re reading my mind)

I’ve added a post-processing step to my reading to collect the noteworthy ideas, forcing myself to write a concise summary and bulleted list of the salient takeaways that resonated. I’ve done this now with my last few books and it’s been a fantastic way to parse through the content a second time — sort of like the first “active recall” review. This extra passthrough to aggregate thoughts into a system helps drive compound interest on the ideas.

It’s rare for new productivity tools to stick with me this long. All of the tools in my daily routines are ones I’ve relied on regularly, and it takes a while for new ones to really click. Readwise clicked for me early and earned its staying power right away. If you’re an avid reader, you’ll love it.

  1. Okay, let’s be honest: this is a phenomenal innovation. 

  2. Science fiction especially isn’t just my favorite fiction genre for entertainment value, I also believe there’s a lot to be learned about invention, creativity, human behavior, psychology, and more from good speculative works. Check out Dan Wang’s comments on this topic

  3. I’ve been using this a lot lately and it’s fantastic. Works great for any books you can’t (or don’t want to) read in e-reader format. 

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