I really like this No Wrong Doors approach, and I think we can learn a lot from it in modern knowledge organizations:

Some governmental agencies have started to adopt No Wrong Door policies, which aim to provide help–often health or mental health services–to individuals even if they show up to the wrong agency to request help. The core insight is that the employees at those agencies are far better equipped to navigate their own bureaucracies than an individual who knows nothing about the bureaucracy’s internal function. […]

Something I’ve been thinking about recently is how engineering organizations can adopt a variant of the No Wrong Doors policy to directly connect folks with problems with the right team and information. Then the first contact point becomes a support system for navigating the bureaucracy successfully.

The Slackification of the workplace has, among other things, resulted in too many different places someone might be able to go for help. It’s frustrating to be sent from team to team, with no one really taking the time to understand and assist with the problem. What if we took a “No Wrong Channel” approach instead? I know it takes a bit of extra time, but I think it’s a worthy goal to become “a support system for navigating the bureaucracy successfully” when someone wanders into our team channel with a question that is not necessarily in our direct sphere of influence.

I’ve been very interested in the rise of the 4-day workweek (4DWW) ever since we adopted it in a previous company and saw the benefits and value it brought to our business. In Do we need to be honest about Fridays? Bruce Daisley makes an interesting observation about how the 4DWW might eventually sneak up on most businesses:

I’ve met several organizations who use Friday as a meeting-free day (to allow team members to chow down on emails and admin). Others tell me that their Fridays are a much slower pace, where meetings peter out mid-morning. […] So, let’s be real, is this how the reality of a four day week will take hold for most of us? That Friday will be kind of a catch-up day for those who need it but that many of us will work at half speed, casually ‘keeping an eye on things’.

Yes, I’m a relentless fanboy of whatever Paul Ford writes, but this is a truly wonderful post about what makes AI so addictive and impossible to look away from. He frames AI as a technology that truly has no shame because “it possesses an absolute willingness to spout foolishness, balanced only by its carefree attitude toward plagiarism.” And so:

By aggregating the world’s knowledge, chomping it into bits with GPUs, and emitting it as multi-gigabyte software that somehow knows what to say next, we’ve made the funniest parody of humanity ever. These models have all of our qualities, bad and good. Helpful, smart, know-it-alls with tendencies to prejudice, spewing statistics and bragging like salesmen at the bar. They mirror the arrogant, repetitive ramblings of our betters, the horrific confidence that keeps driving us over the same cliffs. That arrogance will be sculpted down and smoothed over, but it will have been the most accurate representation of who we truly are to exist so far, a real mirror of our folly, and I will miss it when it goes.

I finally read this very long essay about Rewilding the Internet that’s been making the rounds. It’s about 30 mins of your time and in my opinion it’s time well spent.

It’s about what internet-builders can learn from the field of ecology, where the word “rewilding” has a very specific meaning. It’s essentially about systems thinking, which I know a lot of us care about deeply.

Rewilding the internet is not a nostalgia project for middle-aged nerds who miss IRC and Usenet. For many people across the generations today, platforms like Facebook or TikTok are the internet. They’ve long dwelled in walled gardens they think are the world. Concentrated digital power produces the same symptoms that command and control produces in biological ecosystems; acute distress punctuated by sudden collapses once tipping points are reached. Rewilding is a way to collectively see the counterintuitive truth; today’s internet isn’t too wild, even if it feels like that. It’s simply not wild enough.

In the end, I can’t help but think that though I love these ideas, it’s just… too late. I hope I’m wrong though.

In Crazy Charlie’s Window Michael Lopp says something that has stuck with me for a couple of weeks now (emphasis mine):

The reason, decades later, I frequently think of this unpaid weekend adventure sifting through a year of garbage, hardware, and knick-knacks is because it is when I discovered the compounding non-obvious value from doing exceptional work.

It’s a great story, well worth reading. Matthew Ström makes this point in a slightly different way in The polish paradox (again, emphasis mine):

The polish paradox is that the highest degrees of craft and quality are in the spaces we can’t see, the places we don’t necessarily look. Polish can’t be an afterthought. It must an integral part of the process, a commitment to excellence from the beginning. The unseen effort to perfect every hidden aspect elevates products from good to great.

Doing good work and getting the details right result in better outcomes, yes. But it’s about more than that. It’s not just about the job, it’s about us. The sense of accomplishment and purpose that comes from doing great work is an intrinsic reward that is life-giving far beyond the confines of our immediate job duties.

Will Larson really got me thinking with his advice on the best ways to push your organization to improve. It’s essential work, but “organizations can only absorb so much improvement at a given time before they reject the person providing the feedback.” We have to balance the feedback about how to improve with guidance on how operate within the existing environment:

When I focused on how the environment could change to make my team more successful, I was usually technically correct, but usually didn’t help my team very much. Because work environments change slowly, it benefits your team more to give them feedback about how they can succeed in their current environment than to agree with them about how the current environment does a poor job of supporting them. Agreeing feels empathetic, but frames them as a bystander rather than active participant in their work.

I like Mike Hall’s tips for interviewers in his notes about behavioral interviews. The crux of the behavioral interview style is this:

I’d rather know what you’ve done than what you think, and I have adjusted my style a little to help candidates. I try to explain my process up front. “I’m going to ask you about times you did things because I really want to get down to how you work and what your experience is.”

It is, however, very important to realize that adjacent or related experiences are completely valid and should be encouraged:

If you want to build a diverse, vibrant team, or if you’re not one of those disasters of a manager who doesn’t understand that you need people at several levels of experience on a well-rounded team, then you need to think of a behavioral style not as a way to narrowly insist on stories that describe the exact thing you need done. Instead, you need to think in terms of the competencies the thing requires, and think of examples to ask for that reflect those competencies, not an exact task.

This is a good tip for candidates as well—don’t talk in generalities. Be specific about the ways in which you have solved a particular challenge in the past, what worked well, and what you have learned/would do differently next time.

This isn’t entirely surprising but it’s a sad state of affairs, and it’s worth highlighting not just how, but also where LLMs are being trained:

Hundreds of thousands of hours of work goes into providing enough feedback to turn an LLM into a useful chatbot, and that means the large AI companies outsource the work to parts of the global south, where anglophonic knowledge workers are cheap to hire.

I know it’s too dismissive to call chatbots “fancy autocomplete” like many do, but we have to remember that this isn’t magic. The words the bots use come from somewhere. And in the case of “delve”…

I said “delve” was overused by ChatGPT compared to the internet at large. But there’s one part of the internet where “delve” is a much more common word: the African web. In Nigeria, “delve” is much more frequently used in business English than it is in England or the US. So the workers training their systems provided examples of input and output that used the same language, eventually ending up with an AI system that writes slightly like an African.

Mandy Brown nails it, once again:

One of the principles I come back to over and over is adrienne maree brown’s invitation to move at the speed of trust. That is, whenever attempting any effort with other people, prioritize building trust and respect for each other over and above any other goal. The trust forms the foundation from which the work can grow.

If you’re a fan of the Murderbot series (and if you haven’t read it, get on it!) you will absolutely love this recent keynote speech by author Martha Wells at the annual Jack Williamson Lecture at Eastern New Mexico University. She describes how Murderbot came to be, what it’s really about, and where the story sits within sci-fi and our world in general:

There are a lot of people who viewed All Systems Red as a cute robot story. Which was very weird to me, since I thought I was writing a story about slavery and personhood and bodily autonomy. But humans have always been really good at ignoring things we don’t want to pay attention to. Which is also a theme in the Murderbot series.

I won’t ruin the ending by quoting the final paragraph, I’ll just say that this is my favorite thing I’ve read in a long time, and you should savor every word.