I’ve always been adamant that Product and Engineering are in a partnership, not a “healthy tension” relationship. So I very much agree with this post:
The problem is in the assumption that Product and Engineering teams inherently have different goals. They don’t. Both teams are responsible for the growth and stability of the company, for revenue and scalability. Neither can succeed without the other. When we assume otherwise, we sell each side short.
How to Scale Yourself Down has some really interesting advice on how to go from leading a team at a bigger company to rolling up your sleeves at a startup. A couple of my favorite quotes:
Avoid process out of practice. Leaders who are successful in a startup are the ones who naturally reinvent their own toolboxes, and question what the process is trying to accomplish before establishing something that might be too heavyweight.
However, process is a double-sided coin. “There’s often an overcorrection when leaders move from big companies to small startups. Folks want to shake off that big company feeling and run hard in the other direction. And while the idea of no process sounds fantastic, issues emerge if you don’t start adding at least a little bit of it early on,” he says.
And:
To me, a well-made decision is one that you can explain how and why it was made. Ingraining this in the culture early on will support transparency as the company grows, promote consistency, and reduce politics. In essence, ‘don’t blame me, blame the framework’.
There’s a concept in UX design that I’ve been thinking about a lot in the context of interpersonal work relationships. It’s called “The 9x Effect” and I wrote about it… checks watch… 10 years ago. In short (and heavily simplified), customers value their existing solution/product 3x more than any new “innovation”, and companies overvalue their innovative new product by 3x of what’s currently in the market. So you end up with a 9x mismatch between what companies build and what people believe they need.
There’s another adage that when someone cuts you off in traffic they’re a jerk, but if you cut someone off you had a good reason. We tend to rationalize our own actions while not giving others the benefit of the doubt.
So I’ve been thinking about this in the context of competence at work. I wonder if we sometimes overvalue our own competencies by 3x, and undervalue others’ skills by 3x[1]. And I wonder how that affects the efficiency and health of organizations. We all have a tendency—especially in large organizations—to disagree with strategy, or at the more extreme end of the spectrum, view leadership as “inept” or “clueless”. And I wonder if it’s because of the 9x effect, and if we can all just divide our own opinions by 3 things would get a lot better.
What might happen if as employees we go “well maybe the way I think it should be done is only ⅓ of the answer”. And what if, in turn, leaders go “maybe the way I think things should be done is only a ⅓ of the answer.” Would we be able to come together in the middle and make better decisions together, and in doing so massively improve a company’s culture, autonomy, and efficiency? Sorry, I don’t mean to be a vague question-talker with this post, but I am genuinely curious about this.
A little more critique of ourselves, a little more grace for others… I think I’d like to try that.
Yes, I’m very familiar with the Dunning-Kruger effect. What I’m talking about here is a bit broader and through a different lens. ↩
I came across a couple of really helpful articles recently about how to start a new job well. 30 Tips for New Startup Employees is a long and super useful read—and not just relevant for startups:
Align yourself with the risks of the company. If you’re an engineer but the company is not acquiring customers fast enough, spend your time in marketing. Have range, and don’t try to be too narrow in your focus in the early days. Gain knowledge in a few different areas of the business so you can reduce the overall risks of the company.
Learn How The System Breaks is more relevant to technical roles, but I think “failure streams” can be expanded to other areas of the business as well:
Failure streams are a short circuit to understanding the system, because failures are where the system is interesting and nuanced. Failures are where the heart of complexity, entropy, and flux in the system are. Everything that doesn’t fail behaves like the architecture diagram. Failures show where the architecture isn’t working as intended. By focusing on failures, engineers can onboard quickly into the most important part of the system – the part with problems.
These are all great tips. The one I would add as most important for me personally is related to the concept of Chesterton’s fence:
In the matter of reforming things, as distinct from deforming them, there is one plain and simple principle; a principle which will probably be called a paradox. There exists in such a case a certain institution or law; let us say, for the sake of simplicity, a fence or gate erected across a road. The more modern type of reformer goes gaily up to it and says, ‘I don’t see the use of this; let us clear it away.’ To which the more intelligent type of reformer will do well to answer: ‘If you don’t see the use of it, I certainly won’t let you clear it away. Go away and think. Then, when you can come back and tell me that you do see the use of it, I may allow you to destroy it.’
Or to put it in terms of systems thinking:
Before you disturb the system in any way, watch how it behaves. If it’s a piece of music or a whitewater rapid or a fluctuation in a commodity price, study its beat. If it’s a social system, watch it work. Learn its history. Ask people who’ve been around a long time to tell you what has happened. If possible, find or make a time graph of actual data from the system. Peoples’ memories are not always reliable when it comes to timing.
When you join a new organization you’re probably going to see a lot of random “fences across roads.” Instead of saying “let’s tear this thing down,” first ask “why is this fence here?” There is always a reason, and it’s very likely that there is value in the reasoning. First understand, then make change.
I didn’t realize that there’s a strategy backlash going on in some corners of the internet, but Packy McCormick has a good defense of the importance of having a good strategy:
Execution without strategy is wasteful and tragic. Just as “Companies that have the best products, most talented people, and fastest growth are precisely the ones for which moats are most important,” companies that are the best at execution are precisely the ones for which strategy is most important. They’re the only ones that have a shot. The better you are at execution, the faster you can run in any direction. A good strategy helps you run fast in the right direction.
He also provides a good summary definition of what strategy is, based on the (must-read!) book Good Strategy Bad Strategy: The Difference and Why It Matters:
A strategy is a high-level plan to achieve one or more goals under conditions of uncertainty, designed through recognizing the challenge (diagnosis), setting a direction to overcome it (guiding policy), and detailing steps to implement the policy (coherent actions).
The biggest problem I’ve seen in organizations that struggle with good strategy is that everyone wants a strategy but it’s very hard to figure out how to get started with its creation. It is such a lofty, nebulous concept, and everyone has a different idea of how to go about it. So it’s really important to define what it is and what it’s for, and get broad agreement on that, before starting to create a strategy. To put it another way, make sure you define the black hole words.
For more on this, check out my (very long) case study on Collaborative Product Strategy Development.
I’m on a bit of a break right now (LinkedIn update here if you’re interested), and while I’m figuring out how to spend my time wisely I’ve been reading a lot of sci-fi. The latest book I finished—and really enjoyed—is Ascension by Nicholas Binge:
An enormous snow-covered mountain has appeared in the Pacific Ocean. No one knows when exactly it showed up, precisely how big it might be, or how to explain its existence. When Harold Tunmore is contacted by a shadowy organization to help investigate, he has no idea what he is getting into as he and his team set out for the mountain.
My best attempt at describing this would be it’s like Event Horizon on a mountain, with some really interesting existential philosophy thrown in. Some quotes I liked and highlighted:
There’s no such thing as starting fresh: new beginnings all contain the old ones bundled up inside of them. Starting fresh means not having a history anymore; it means not having an identity.
And…
“Do you know why Sisyphus keeps climbing,” Thomas asked, looking up at me, “even though he knows he’ll always end up back at the start?” John’s last words—echoing back at me across space and time. “Why?” He smiled and stood up. “Because that’s what life is. A constant climb. Eternal growth. The continual battle against entropy. It doesn’t matter what the destination is, or what’s at the top; all that matters is that you keep climbing. That’s what it means to be alive, Harold. That’s what it means to be human.” He turned away from me, walking off into the night.
If you’re in the mood for some smart spacey sci-fi horror, give this one a go!
I fully agree with Chris Coyier’s main point in Other People’s Busted Software is an Opportunity:
If you make software that does work reliably, you’ve got a leg up. Even if your customers don’t tell you “I like your software because it always works”, they’ll feel it and make choices around knowing it.
It feels like so many teams prioritize “innovation” over quality, so we end up getting stuck with products that have an overwhelming number of features but they all barely work—or the whole thing is slow and cumbersome. At some point we seem to have forgotten that product quality is not optional, and that it should be built in from the start.
Not only that, but in a “project” mindset teams just continue to move on to the next feature without taking the time to learn and improve what they shipped, as Marty Cagan points out in From Projects to Products:
Most efforts lose all hope of providing real value, and just try to get something shipped. Then as soon as they do finally ship, it’s not like they can iterate to improve the product. Instead, the people usually scatter off to their next assignments; nobody owning the outcome, and any important learnings from the effort likely lost.
This seems almost silly to point out, but a feature is not going to help your business if (1) it doesn’t add value and/or (2) it doesn’t work well. And yet somehow lots of teams put validation and quality on the backburner while they rush to get more features out. So Chris is right in his post: focusing on product quality is a huge differentiator in today’s software market.
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.