Embracing the deadline: How engineers benefit from delivery dates

This is a good summary of the “healthy pressure” we strive towards on our team as well:

While working without the pressure of explicit deadlines can feel liberating, it also increases the chance of distraction. Deadlines help us stay focused, aligned and driven – and can be used to keep project scope in check.

Finding the right balance with product onboarding

There are some great product tips in Scott Belsky’s How to Shape Remarkable Products in the Messy Middle of Building Startups, but this part about onboarding particularly stood out for me:

You can’t expect new customers to endure explanation. You can’t even expect customers to patiently watch as you show them how to use your product. Your best chance at engaging them is to do it for them — at least at first. Only after your customers feel successful will they engage deeply enough to tap the full potential of your offering.

One of the hardest things to figure out with onboarding is the right balance of selecting defaults (“doing it for them”) and having users learn by doing things themselves.

For example, within Postmark’s onboarding a continuing debate is whether or not we should auto-create a user’s first “server” for them, or help them understand the concept better by making them do it themselves. Finding the appropriate amount of friction to introduce is an ongoing and important challenge for any product’s onboarding.

The business case for support-driven growth

Support is a revenue driver, and a personal touch at scale is a great way to grow a business.

— Nick Francis, The Business Case for Support-Driven Growth

What Spotify wants: that you should forget that you’re listening

Liz Pelly’s Streambait Pop is a fascinating look at the “Spotify sound” and other changes in pop music brought about by streaming:

The Spotify sound has a few different variations, but essentially it’s a formula. “It has this soft, emo-y, cutesy thing to it,” Matt says. “These days it’s often really minimal and based around just a few simple elements in verses. Often a snap in the verses. And then the choruses sometimes employ vocal samples. It’s usually kind of emo in lyrical nature.” Then there’s also a more electronic, DJ-oriented variation, which is “based around a drop … It’s usually a chilled-out verse with a kind of coo-y vocal. And then it builds up and there’s a drop built around a melody that’s played with a vocal sample.”

The really interesting part to me is how it’s a sound that’s essentially designed to make you forget about it, so that you just keep streaming endlessly:

The chill-hits Spotify sound is a product of playlist logic requiring that one song flows seamlessly into the next, a formula that guarantees a greater number of passive streams. It’s music without much risk—it won’t make you change your mind. At times, these whispery, smaller sounds even recall aspects of ASMR, with its performed intimacy and soothing voices. When everyone wants your attention, it makes sense to find reprieve in stuff that requires very little of it, or that might massage your brain a bit.

After I read this article I went through my Spotify playlists and counted how many of them had the word “chill” in it. Let’s just say I’m too embarrassed to tell you…

But moving on, I think this “inoffensiveness” in music is one of the reasons I’ve started to listen to so many more genres over the past few years. I now like music that feels like it just doesn’t quite sit right. Any artist or band that combines a little discomfort with a lot of skill has my attention. Just one recent example that comes to mind is Double Negative by Low. I still don’t really know what it is. But I know it’s something really special.

Product teams exist to serve customers

Empowered Product Teams is another gem of a post from Marty Cagan. This part stood out to me:

In most companies, technology teams exist “to serve the business.” That is very often the literal phrase you will hear. But even if they aren’t explicit about it, the different parts of the business end up driving what is actually built by the technology teams.

However, in contrast, in strong product organizations, teams exist for a very different purpose. They exist “to serve the customers, in ways that meet the needs of the business.”

The distinction is subtle, but important. If you only serve “the business”, you’re going to make decisions without asking whether something is user-hostile or not (see, for example, scroll-jacking, or Twitter’s tendency to “forget” that you prefer a timeline that shows latest tweets). Bringing customer needs into any conversation about business needs is the way to build something that’s profitable and sustainable.

The social values of artificial intelligence

A lot of words are being written about AI and machine learning these days, so it’s sometimes hard to know what to pay attention to. M.C. Elish and danah boyd’s Don’t Believe Every AI You See is one of those essays that I would consider essential reading on the topic. On the ethics of artificial intelligence:

When we consider the ethical dimensions of AI deployments, in nearly every instance the imagined capacity of a technology does not match up with current reality. As a result, public conversations about ethics and AI often focus on hypothetical extremes, like whether or not an AI system might kill someone, rather than current ethical dilemmas that need to be faced here and now. The real questions of AI ethics sit in the mundane rather than the spectacular. They emerge at the intersections between a technology and the social context of everyday life, including how small decisions in the design and implementation of AI can create ripple effects with unintended consequences.

And on the supposed “neutrality” of machines:

[There is] a prevailing rhetoric around AI and machine learning, which presents artificial intelligence as the apex of efficiency, insight, and disinterested analysis. And yet, AI is not, and will not be, perfect. To think of it as such obscures the fact that AI technologies are the products of particular decisions made by people within complex organizations. AI technologies are never neutral and always encode specific social values.

As Kevin Kelly also pointed out years ago in his book What Technology Wants, technology is never neutral. It possesses the collective values of its creators. And that’s where things so often go wrong. A great resource on this topic is Sara Wachter-Boettcher’s book Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech.

The problem with Instagram alternatives

I’ve been a long-time subscriber and fan of Craig Mod’s newsletter. In the latest edition he has some really interesting thoughts on Instagram, and social media in general:

Instagram will only get more complex, less knowable, more algorithmic, more engagement-hungry in 2019.

I want to have a place very far apart from that, where I can post photos on my own terms. Not have an algorithm decide which of my posts is best. And I don’t want to be rewarded for being anodyne, which is what these general algorithms seem to optimize for: things that are easily digestible, firmly on the scale of “fine, just fine.” It becomes a self-fulfilling prophecy, as the more boring stuff we shove into our eyeballs, the more boring our taste becomes.

I’ve long since deleted my Facebook account, but in what has become a fairly familiar form of hypocrisy in myself and many of my friends, I’ve stubbornly held on to Instagram. I’ve toyed with Sunlit in conjunction with Micro.blog as an option, but as with most of the Instagram “alternatives” out there, the network effect simply isn’t there.

The other important distinction is that I see a major difference between photographers and Photographers (capital P). Craig is a Photographer, so it makes sense for him to be way more thoughtful and concerned about where he shares his photos. I mostly post pictures of whatever vinyl I’m listening to, so it’s not exactly high art.

Which brings me to an even bigger question… what is the purpose of sharing photos for small-p photographers? For me, I want to connect with people I know, make them part of my life, maybe influence their music taste a little bit. And I want to see similarly mundane things about their lives. And that is why starting a photography newsletter like Craig — or moving to Sunlit — isn’t really an option for me. Because I need to use the thing where my people are at.

I just wish the thing I have to use was less yucky. I’d absolutely pay a monthly fee to remove the yucky parts.

A 2019 manifesto: analog over digital

I’ve been thinking about Cal Newport’s post called Join Analog Social Media all day, especially as we get to the end of another year:

The dynamic at play here is that digital activities that are mildly positive in isolation, combine to crowd out other real world activities that are potentially much more satisfying. This is what allows you to love Twitter in the moment when you discover a hilarious tweet, but at the end of the day fear that the app is degrading your soul.

Understanding this dynamic is critical because it tells you that you cannot improve your life by focusing exclusively on digital tools. Triaging your apps, or cutting back phone time, will not by itself make you happier. You must also aggressively fill in the space this pruning creates with the type of massively satisfying, real world activities that these tools have been increasingly pushing out of your life.

Simply cutting back on social media time is only going to leave a weird emptiness behind if we don’t fill that gap with some real connection time with the people in our lives.

I’m not sure about New Year’s Resolutions, but if I have any, it would be to look at everything through the lens of a new manifesto: analog over digital. Just as with the Agile Manifesto, the word “over” is of utmost importance here. It doesn’t mean I’m done with digital. It just means that I want to look at the things I do, and critically evaluate whether or not an analog approach could be more meaningful. For example, should I stop tracking my runs on Strava, and just enjoy them instead? Should I have a go at hand journaling instead of putting everything in Day One? The answer may very well be “no”, but I’d like to ask the question more in 2019.

Happy New Year, everyone.

Filling our empty moments with sound and noise

In Filling the Silence with Digital Noise, Kate Moran and Kim Flaherty share some research-based findings on how people use digital background noise to make sure it’s never quiet around them:

While many participants reported feeling the need to have some sort of audio in the background during their silent moments, others reported a more intense version of this phenomenon: the need to fill all the empty moments in their lives with some activity to avoid boredom or downtime. This behavior fills the ‘silence’ in a figurative way — people use their devices to keep their minds constantly occupied.

I read this article with interest, because I also do this—albeit for a different reason. I have a condition called tinnitus, which is a consistent ringing in the ears. There is no cure for it—the only way to deal with it is to learn to manage and be ok with it. For those of us who suffer from tinnitus, silence is torture. Because there is no silence. Your only choices are (1) the sounds/noises you put on around you, or (2) a loud ringing in your head that comes from nowhere and everywhere and never goes away.

Guess which option we usually go for…

Data-driven vs. data-informed decision-making

The Netflix Data War is a very interesting post about the internal discussions that happen between Netflix’s content team and their data team. In short, data isn’t everything:

[…] in almost any decision-making situation involving data, there is some non-zero percentage of the process that involves “gut”. The reason is because not all information about a process can be incorporated into a data analysis, and it’s important for data analysts to realize that.

That’s an important point to reflect on. It doesn’t matter how complete a data model is. There are some variables that simply cannot be included, because it’s impossible to know what should be included in any particular model.

Apart from that, it’s also just a fascinating look at the internal workings of Netflix.

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