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Link roundup for June 27, 2023

Ask Questions, Repeat The Hard Parts, and Listen →

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.

The Creators of Disney’s New Platformer Explain the Hard Lessons of Making Games for Kids →

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.”

Failure →

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. 

Reality has a surprising amount of detail →

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.

Fitness Technology and the Templated Body →

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.

The Slow Productivity of John Wick →

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.

A Practical Guide to Executive Presence →

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).

You don’t have a culture problem, you have a management problem

Great points on company culture from the Raw Signal group in You don’t have a culture problem, you have a management problem:

Culture handbooks don’t produce culture, people do. The culture you experience in your organization is a rolling average of the last thousand interactions you’ve had. Every piece of feedback, every conflict, every trade-off is culture. Every hiring, promotion, and firing, too. Those interactions come from everywhere, but a disproportionate number will come from your close peers, and your own boss. Culture may be everyone’s job, but some people have a lot of sway on your local average.

They go on to explain what managers can—and should!—do to take ownership of the culture in their organizations.

MrBeast and product management (sorry)

This is a fascinating profile of MrBeast and his YouTube empire (NYT Gift Article). It’s extensively researched and presented with a steady hand. The reason I link to it here is I think he would be a pretty good product manager, albeit a litte bit on the obsessive side:

Donaldson stands out for his dedication to understanding how YouTube works. For most of his teenage years, “I woke up, I studied YouTube, I studied videos, I studied filmmaking, I went to bed and that was my life,” Donaldson once told Bloomberg. “I hardly had any friends because I was so obsessed with YouTube,” he said on “The Joe Rogan Experience” last year.

After high school, he hooked up with a gang of similarly obsessed “lunatics” and planned out a program of study. He and his friends “did nothing but just hyperstudy what makes a good video, what makes a good thumbnail, what’s good pacing, how to go viral,” he told Rogan. “We’d do things like take a thousand thumbnails and see if there’s correlation to the brightness of the thumbnail to how many views it got. Videos that got over 10 million views, how often do they cut the camera angles? Things like that.”

That reminds me of the famous 41 shades of blue testing at Google. Also, one thing I never realized about the whole thing is that MrBeast’s pitch is basically “Hey, you do charity just by watching me because I use the money I get for charity, so the more you watch me the more charitable you are.” That is a bit disturbing but also pretty clever.

Managing feature requests from stakeholders

It might be controversial, but I tend to agree with Kax Uson point about managing feature requests from stakeholders:

I have learned that it’s perfectly alright for stakeholders to have solution requests. And to expect them to bring problems to us is unrealistic.

The post gives some good advice on how to translate solution requests into problems/opportunities that teams can solve:

Speak the language they speak. Talk about the benefits and impact of their requests. If you do build the feature they’re asking for, what value would it provide for the customers/users and the company? Speak in outcomes.

Metrics to check when evaluating a company as a job seeker

There’s some really good advice for job seekers in Carilu Dietrich’s post 10 Most Important Metrics For Evaluating a Company:

Net Dollar Retention (NDR) is one of the best ways to see if a tech company is healthy and growing. It measures the expansion or contraction of a company’s existing customer revenue over a given period. NDR takes into account the revenue lost from churn and increased revenue from upselling, cross-selling, and renewals from existing cusomers.

I would also add Gross Revenue Retention to that list. It describes how much revenue a company keeps from its existing customers over a specific period, not including any new revenue from new customers. So, if a company started the year with $100 from its existing customers and ended the year with $90, even if they lost some customers but upsold others, the gross revenue retention would be 90%. It helps guage how good a company is at keeping its current customers happy and continuing to spend money, without taking into account any new business they’ve gained.

How generative AI might change the product profession in the future

I promise this isn’t going to become an AI blog, but Marty Cagan’s latest on Preparing For The Future has some solid points on how generative AI might change our profession. Here he talks about the impact on QA:

The new generation of AI-based test automation tools has the promise to revolutionize our approach to ensuring the product is behaving properly. On the other hand, our current approach to quality is largely based on deterministic products.  This means that given a set of inputs we can predict what the appropriate output should be, and we can count on that being true indefinitely.  

Yet for many new products built on generative AI, our products are no longer deterministic, but rather probabilistic.  We can no longer count on the same inputs generating the same outputs.  For many contexts, this is not a problem.  But for other contexts, especially when safety is involved, this will require different approaches to ensure appropriate behavior.

Also, yes please:

For those product managers of empowered product teams, the time spent creating artifacts such as written narratives, roadmaps, PRD’s, and acceptance criteria, as just a few examples, should be significantly assisted by the new generation of tools, some of which are already starting to appear. Even at the very rudimentary level, if the new generation of tools can significantly reduce the time a product manager (or engineer) spends dealing with tools like Jira, that will be a substantial win.

Evaluating AI product opportunities by plotting them on a “Survival Curve”

Aniket Deosthali (Head of Product for Conversational Commerce at Walmart) provides a great framework for evaluating AI product opportunities in How to Build AI Products People Want:

The most efficient way to evaluate AI opportunities and unlock the advantages of AI is by using the Consideration x Context framework. Let’s start with some baseline definitions.

Y-Axis = Consideration: The amount of effort required to make a decision.

The more thought you put into a decision, the higher consideration it is. For example, choosing a dish detergent is “low consideration” for most shoppers, compared to buying a car which is “high consideration.” Consideration can be represented as a function of the number of compelling alternatives and the stakes – users’ tolerance for errors, for example.

X-Axis = Context: The volume of abstract concepts AI needs to know. 

Context refers to how many abstract concepts a model needs to know in order to provide a useful response. Does it only need to understand a small batch of data points (like a product catalog), or does it need to understand the entire internet (like ChatGPT)?

He goes on to explain how to plot different solutions on a “Survival Curve.” If you work on AI products this is one of the rare actually helpful articles for PMs in the area of AI and LLMs.

Experimentation in the real world: Southwest Airlines

The post 7 innovations that Southwest is testing to improve its crucial turn times is a great real-world example of experimentation in product (make sure your ad blockers are charged for this one, it’s published on The Points Guy…).

Zach Griff goes over several ideas Southwest Airlines are trying to improve the time between when a flight arrives and leaves again. For instance, for when you’re queuing on the jet bridge:

The first is the installation of Bluetooth speakers in the jet bridge, which play (royalty-free) disco, electronic dance music, hip-hop and kids music during boarding and deplaning. Listening to music at a high beats-per-minute rate is scientifically proven to get people moving faster and more efficiently, according to McCartan, which is exactly what Southwest wants during one of the most critical phases of the turn.

There are lots of learnings for PMs sprinkled throughout the post.

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