There’s some good insights in this year’s 2023 State of DevOps Report. It’s well worth skimming through. Things like this aren’t exactly surprising, but it’s nice to have some data around it:
Teams with generative cultures, composed of people who felt included and like they belonged on their team, have 30% higher organizational performance than organizations without a generative culture.
Ed Zitron’s newsletter is kind of a hate-read for me because his vitriol knows no end and it can be a lot… but I think he did pretty well in his response to Marc Andreessen’s latest essay:
This is Andreessen’s dream—a continual race to the bottom where the tech industry is incentivized not to solve problems, but to find ways to make already-solved problems cheaper to solve so that venture capitalists can make money.
That’s a good quote, but please don’t stop there. The whole essay is the best rebuttal I’ve seen so far.
This is a thoughtful, well-argued essay by Benedict Evans about where we’re at with LLMs.
Whenever we get a new tool, we start by forcing it to fit our existing ways of working, and then over time we change the work to fit the new tool. We try to treat ChatGPT as though it was Google or a database instead of asking what it is useful for. How can we change the work to take advantage of this?
This is an older post from Lorin Hochstein but it’s new to me, and really insightful. It’s about how to best use our knowledge about the past behavior of a software system to figure out where we should invest our time to improve the system—and how the common method of error budgets is generally not a good way to do this:
I’m skeptical about relying on predefined metrics, such as reliability, for getting insight into the risks of the system that could lead to big incidents. Instead, I prefer to focus on signals, which are not predefined metrics but rather some kind of information that has caught your attention that suggests that there’s some aspect of your system that you should dig into a little more.
So basically, vibe-based incident analysis is where it’s at.
Since I prefer reading over watching, I appreciate Dave Rupert’s summary of this video about AI/LLM responsibility in his post Uncovering a new class of responsibilities:
Three rules of technology outline their nearly hour long talk:
- When you invent a new technology, you uncover a new class of responsibilities
- If that tech confers power, it starts a race
- If you do not coordinate, the race ends in tragedy
It’s those last steps that are the concerning ones. If we fail to respond to #1, we end up with #3.
Here’s a good post from Gergely Orosz discussing Interesting Learnings from Outages. It covers internal vs. public postmortems, how investing in reliability can have bumps along the way, and how to make the difficult decision to try and fix something on the spot, or to do a lengthy restore. This point stood out to me:
“Move fast with autonomous teams” often builds up infrastructure debt. Reddit is a fast-moving scaleup where teams move fast, and it sounded like they had autonomy in infrastructure decisions. The wide range of infra configurations caused several outages, and the company is now paying down this “infrastructure debt.” This is not to say that autonomous teams moving fast is a bad thing, but it’s a reminder that this approach introduces tradeoffs that could impact reliability and will eventually have to be paid down, often by dedicated teams.
Matt Rickard reminds us that it’s worth considering the long-term effects that putting public APIs behind paywalls might have on search engines:
Large models are trained on public data scraped via API. Content-heavy sites are most likely to be disrupted by models trained on their own data. Naturally, they want to restrict access and either (1) sell the data or (2) train their own models. This restriction prevents (or complicates) Google’s automatic scraping of the data for Search (and probably for training models, too). Google will lose results, site by site—it will be Google Search’s death by a thousand cuts.
Here’s some great advice from Robin Sloan on how to find good educational content on YouTube:
These days, when I’m investigating a subject, I tend to go straight to Low View Count Scholarly YouTube, which is of course the version of YouTube you get when you append the term “lecture” to your search. When you hit a tranche of videos between forty and ninety minutes long, with between 500 and 5000 views, you know you’re in the right place.
This Google experiment is interesting and kind of related:
To make it easier for people to learn about topics they’re interested in, we’re experimenting with AI-generated quizzes on the YouTube mobile app Home feed.
Marty Cagan’s latest is all about the agreements between product teams and executive teams. This point about deadlines stood out for me:
Product teams ask that only the product team that will be responsible for delivering on a promise be the one to make that promise, and they not be asked to make a promise or deliver on a commitment where they don’t know what is involved and what would be required to succeed.
A good piece by Bhaskar Chakravorti, also discussing AI’s impact on DEI in the workplace:
For example, while the broad shift toward remote work could help promote diversity with more flexible hiring, I see the increasing use of AI as likely to have the opposite effect. Black and Hispanic workers are overrepresented in the 30 occupations with the highest exposure to automation and underrepresented in the 30 occupations with the lowest exposure. While AI might help workers get more done in less time, and this increased productivity could increase wages of those employed, it could lead to a severe loss of wages for those whose jobs are displaced. A 2021 paper found that wage inequality tended to increase the most in countries in which companies already relied a lot on robots and that were quick to adopt the latest robotic technologies.
Also worth noting this discrepancy, which we seem to hear about a lot these days:
A 2022 study showed improved efficiencies for remote work as companies and employees grew more comfortable with work-from-home arrangements, but according to a separate 2023 study, managers and employees disagree about the impact: The former believe that remote working reduces productivity, while employees believe the opposite.
I enjoyed Rand Fishkin’s extensive and transparent thoughts on how their business is doing. A couple of things especially stood out. First, this point about marketing attribution:
In businesses like ours, most top-of-funnel marketing happens months or years before conversions do. When someone buys SparkToro, we have no way to attribute it to the three videos they watched on LinkedIn or the word-of-mouth recommendation from an ex-colleague at their previous agency, or the podcast they heard Amanda on last month. This would drive a lot of CMOs and CFOs bananas, but if you can lean into the process of trusting your “vanity metrics” (views, likes, comments, shares, emails, I-heard-about-you-ons), you can build a marketing flywheel that’s almost entirely devoid of competition.
I had to read that last sentence a few times to make sure it’s not a typo. This may be the first time I’ve ever seen someone speak positively about vanity metrics. Definitely food for thought…
And then there’s this important point about market segmentation:
Great products aren’t enough, either. To be “great” is, in my opinion, not nearly as valuable as being irrelevant to 99% of people, but exactly perfect for the 1% who deeply care about the problem you solve. Extra bonus points: target your product at a group that’s well-connected to others in their field, and gets value from sharing new things. Nothing’s better than word of mouth marketing. Nothing.
This is a really interesting exploration of how “the SEO arms race has left Google and the web drowning in garbage text, with customers and businesses flailing to find each other.” Some small businesses deal with by having two websites: one for humans and one for robots.
This is a really good history and retrospective of Google Reader. Dang, I feel for this team. It was so much more than an RSS Reader, and they didn’t even like that name. It was the first true social media feed: curated content you care about.
In other words, Fusion was meant to be a social network. One based on content, on curation, on discussion. In retrospect, what Shellen and Wetherell proposed sounds more like Twitter or Instagram than an RSS reader. “We were trying to avoid saying ‘feed reader,’” Shellen says, “or reading at all. Because I think we built a social product.”
Really interesting exploration by Adam Mastroianni, and a history of how messed up our definition of “smart” has become:
My grandma does not know how to use the “input” button on her TV’s remote control, but she does know how to raise a family full of good people who love each other, how to carry on through a tragedy, and how to make the perfect pumpkin pie. We sometimes condescendingly refer to this kind of wisdom as “folksy” or “homespun,” as if answering multiple-choice questions is real intelligence, and living a good, full life is just some down-home, gee-whiz, cutesy thing that little old ladies do.
I’ve always been interested in “sense of place”—finding the reasons why a town or a place exists, and why people are drawn to certain places. Anne Helen Petersen writes beautifully about this concept in an essay about her hometown:
Optimization and remodel culture robs spaces of that heart. I’m sure MOD Pizza, the latest upstart in the pizza world, makes a lot more money. It’s slicker, faster, easier. But it’s not a place, it’s a product—a profit center. You can always tell, can’t you, when a restaurant’s primary purpose is to make a bunch of people who’d probably never eat there a whole bunch of money.
John Warner writes about the passing of Cormac McCarthy as well as Elizabeth Gilbert’s decision to indefinitely postpone the publication of her novel following the appearance of over 500 negative reviews of the book on Goodreads (also see How Goodreads Reviews Can Tank a Book Before It’s Published). He makes some interesting observations about “parasocial relationships”:
My first reaction was that we were in the realm of the parasocial, the invention or a relationship with a celebrity who doesn’t know you exist. My most parasocial relationships are with my favorite Peloton instructors who are clearly encouraged to stoke this feeling in platform participants as a way to keep us invested and involved.
Another example is Taylor Swift’s recent relationship with some other recording artist with bad politics and questionable hygiene, something her fans could apparently not countenance, and perhaps drove her to break up with the dude.
Michael Lopp’s latest is an excellent reminder of what good leadership is all about:
Earlier in this piece, I wrote I was disappointed when you asked me to decide. I’m not disappointed in you; I’m disappointed with myself. See, my primary job as your leader is to give you the skills and experience I’ve gained over the years. If I cannot guide you toward making the decision, I’m reminded I’ve not yet achieved my primary goal in our professional relationship.
My job is to teach you not to need me.
Patrick Klepek writes about making games for kids, but there are some great generalizable product lessons throughout. Like this reminder not to drift toward the “average” user:
“We have this phrase internally, we say ‘don’t make a rosé,” said Grand-Scrutton. “And it’s because one of my friends in the industry, one of my mentors, he said this phrase to me, and he said that if you go to a restaurant and you’ve got someone that loves red wine, or someone loves white wine, you don’t give them a rose because no one’s happy. You gave them an awesome red or an awesome white. So we say that internally, when we are riding this line of only half doing something, we say ‘it’s too rosé.’ Rosé is a perfectly fine wine choice, but we felt we were rosé-ing it.”
Mike Fisher writes about a really interesting tool to get teams comfortable with taking risks, called the Failure Workshop:
One strategy to familiarize team members with failure is to conduct a Failure Workshop. Think of it as a tabletop exercise on failure in a safe environment. The workshop’s objective is to “stay in the failure” while fostering a supportive space for peer interaction. This is similar to a pre-mortem but it keeps the participants thinking about possible failure scenarios instead of brainstorming solutions.
I missed this 2017 piece by John Salvatier, and it’s so good. He talks about how easy it is to get intellectually stuck in our ways, and how to break out of that:
The direction for improvement is clear: seek detail you would not normally notice about the world. When you go for a walk, notice the unexpected detail in a flower or what the seams in the road imply about how the road was built. When you talk to someone who is smart but just seems so wrong, figure out what details seem important to them and why. In your work, notice how that meeting actually wouldn’t have accomplished much if Sarah hadn’t pointed out that one thing. As you learn, notice which details actually change how you think. If you wish to not get stuck, seek to perceive what you have not yet perceived.
In today’s example of “technology is not neutral” Audrey Watters talks about how depressing fitness tracking can be:
Fitness technologies shape how we think about fitness; they shape how we think about our movement — why we move, how we move, and so on. We covet the gadgets that promise to give us more and more data and deeper and better insights about ourselves, supposedly to learn more about ourselves. And yet, we are simultaneously un-learning to trust ourselves (or trust professionals — our teachers and coaches), waiting for the “nudge” and the badge to compel us move.
Related, also see Lukas Mathis’s Streak Redemption about what happens when you break a streak in one of these apps:
Conversely, losing a streak can be so demoralizing that it can be difficult to start from scratch, and get going again.
You’re going to have to trust me that this is actually really good:
John Wick may be shallow entertainment, but the story of its success highlights some deep lessons about what the rest of us might be missing in our pursuit of a job well done.
Some great advice here:
If you take nothing else away from this post, it’s this first point: Don’t freak out. Visibly losing control of yourself is one of the most damaging ways that leaders self-sabotage. Seeing the person who’s supposed to be in charge lose control under pressure is confidence-destroying and can take a very long time to recover from.
Also:
You only sound as smart as the dumbest thing that comes out of your mouth. The more you say, the more dumb stuff that you have the chance to say. Consciously try to have a timer going in your head that tells you to wrap it up after you’ve been talking for ~30 seconds, unless there’s a specific reason that you need to speak for longer (e.g. a presentation).