This site contains 29257 unique* 88x31 buttons that I scraped from the GeoCities archives compiled by the incredible ARCHIVE TEAM before GeoCities' demise in late 2009.

I shouldn’t go through all ~30,000 images to find the ones I made for Tim’s World or That’s Unpossible, right?

…right?

Whenever I talk about a knowledge win via robots on the socials or with humans, someone snarks, “Well, how do you know it’s true? How do you know the robot isn’t hallucinating?” Before I explain my process, I want to point out that I don’t believe humans are snarking because they want to know the actual answer; I think they are scared. They are worried about AI taking over the world or folks losing their job, and while these are valid worries, it’s not the robot’s responsibility to tell the truth; it’s your job to understand what is and isn’t true.

You’re being changed by the things you see and read for your entire life, and hopefully, you’ve developed a filter through which this information passes. Sometimes, it passes through without incident, but other times, it’s stopped, and you wonder, “Is this true?”

Knowing when to question truth is fundamental to being a human. Unfortunately, we’ve spent the last forty years building networks of information that have made it pretty easy to generate and broadcast lies at scale. When you combine the internet with the fact that many humans just want their hopes and fears amplified, you can understand why the real problem isn’t robots doing it better; it’s the humans getting worse.

I’m working on an extended side quest and in the past few hours of pairing with ChatGPT, I’ve found myself constantly second guessing a large portion of the decisions and code that the AI produced.

This article pairs well with this one I read today about a possible social exploit that relies on frequently hallucinated package names.

Simon Willison writes:

Bar Lanyado noticed that LLMs frequently hallucinate the names of packages that don’t exist in their answers to coding questions, which can be exploited as a supply chain attack.

He gathered 2,500 questions across Python, Node.js, Go, .NET and Ruby and ran them through a number of different LLMs, taking notes of any hallucinated packages and if any of those hallucinations were repeated.

One repeat example was “pip install huggingface-cli” (the correct package is “huggingface[cli]”). Bar then published a harmless package under that name in January, and observebd 30,000 downloads of that package in the three months that followed.

I’ll be honest: during my side quest here, I’ve 100% blindly run npm install on packages without double checking official documentation.

These large language models truly are mirrors to our minds, showing all sides of our personalities from our most fit to our most lazy.

I’ve owned my own home for close to five years now, and I’m slowly coming around to the idea of making major changes to it in order to make it feel like it is mine.

During the pandemic, we poured a patio in the front of our house and spent nearly every day sitting on it.

In fact, that patio led to the formation of several enduring relationships with my neighbors.

I find it tough to shake the renter’s mindset, where I can’t do anything to affect the “resale value” of my home because… well, maybe the next owner won’t buy it because of the deep purple walls in the basement.

But the more I lean into tweaking what we have, the more I feel comfortable, productive, and happy. I’m incredibly grateful to have property which I can modify however I see fit to improve the wary of life for my family and myself.

This article also made me reflect on how toxic it can be to covet other people’s homes:

We should always remember that the purpose of a home is for living and that decoration, for many, is a form of self-expression. Media literacy, which has improved with regard to beauty and fashion content, lags when it comes to architecture and interior design. Changing that begins with realizing that most homes don’t actually look like hotel lobbies or real estate listings. They, rather joyfully, look like homes—dust bunnies and all.

Here is how platforms die: First, they are good to their users; then they abuse their users to make things better for their business customers; finally, they abuse those business customers to claw back all the value for themselves. Then, they die.

I call this enshittification, and it is a seemingly inevitable consequence arising from the combination of the ease of changing how a platform allocates value, combined with the nature of a "two-sided market," where a platform sits between buyers and sellers, hold each hostage to the other, raking off an ever-larger share of the value that passes between them.

If you’ve spent much time in the same tech bubbles as me this past year, you’ve probably come across this article already.

At a bare minimum, I’m sure you’ve seen the phrase “enshittification.”

Once you understand the concept, you do start to see the pattern unfold around you constantly. ¹

While there are countless examples of this natural platform decay within our virtual world, what about the physical world?

Is enshittification simply human nature, an inescapable fate for any collaborative endeavor above a certain size?

And if enshittification is not inevitable, what are the forces that lead to it, and how can we combat them when building our own communities?

I’m a sucker for this style of post. This one in particular is jam packed with so many great pieces of advice that I had to read it three times before sharing it.

Here’s the very first item on her list. If it speaks to you, take ten minutes and thoughtfully consider the other 100 items.

1. You are overly obedient. You not only do what people tell you to do, but find it hard to imagine any world other than the one they present to you. Spend more time thinking about what you want, in isolation from the pressures of the world. (Keep this in mind while you read the rest of this very prescriptive document.)

I hate the internet.

...that's a lie. I love it, but I hate the algorithms.

That's also a lie... I love the algorithms.

I watched this video on the plane ride back from Nickelodeon Resort yesterday, and I have to say, it got me.

Hank's assessment of how the algorithms deployed by social networks come up short in actually giving us what we want is spot on.

It's why I love how many friends are spinning up their own newsletters. And this new newsletter was a no brainer instasubscribe.

Ever since my buddy Paul gifted me a premium subscription to Garbage Day, I've been a voracious newsletter subscriber. They do a great job of filling the void that Google Reader left in my life.¹

This website has been my way of curating the internet, sharing things I've found that interest me, but maybe I should start a newsletter myself and do things in both places.

Should I tell my impostor syndrome to shove it and start my own newsletter, y'all?

The algorithms¹ blessed me with this video last week, and I find myself coming back to it when I'm doing deep work.

I also am enjoying his Rammstein version, and I am eagerly looking forward to checking out the Linkin Park and Avenged Sevenfold ones soon.

If I could play the piano, this is absolutely the kind of stuff I would want to play.

One can of course relate to money in pathological ways. For those whose standard of value resides not in a conception of their fully-lived life (a la the builder), but in the impressions or judgments of others (be it God or society or their parents or some other “drill sergeant”), money means whatever it purportedly means to those others—status, in some circles, or wicked materialism in others, or in still others, “privilege” to be forgiven with obligate philanthropy. 

By contrast, a builder’s relationship to money is not mediated by any of these external intermediaries. She understands that money is a medium of value exchange, and what she values is set by the life she wants to build and the world she wants to live in. 

There are also simpler pathologies, such as when fear or insecurity drives founders to pursue short-term monetary gains over the longer-term health and durability of their business. But such financial anxieties can be diagnosed and remedied by re-orienting toward the overarching goal of building one’s best life, which presumably includes a healthy and durable version of one’s business (or whatever one is building) as part of it.

Quite a useful way to reframe money and its importance to a well considered life.

I’m an unabashed fan of Simon Willison’s blog. Some of his posts admittedly go over my head, but I needed to share this post because it gets across the point I have been trying to articulate myself about AI and how I use it.

In the post, Simon talks about wanting to get a polygon object created that represents the boundary of Adirondack Park, the largest park in the United States (which occupies a fifth of the whole state!).

That part in and of itself is nerdy and a fun read, but this section here made my neck hurt from nodding aggressively in agreement:

Isn’t this a bit trivial? Yes it is, and that’s the point. This was a five minute sidequest. Writing about it here took ten times longer than the exercise itself.

I take on LLM-assisted sidequests like this one dozens of times a week. Many of them are substantially larger and more useful. They are having a very material impact on my work: I can get more done and solve much more interesting problems, because I’m not wasting valuable cycles figuring out ogr2ogr invocations or mucking around with polygon libraries.

Not to mention that I find working this way fun! It feels like science fiction every time I do it. Our AI-assisted future is here right now and I’m still finding it weird, fascinating and deeply entertaining.

Frequent readers of this blog know that a big part of the work I’ve been doing since being laid off is in reflecting on what brings me joy and happiness.

Work over the last twelve years of my life represented a small portion of something that used to bring me a ton of joy (building websites and apps). But somewhere along the way, building websites was no longer enjoyable to me.

I used to love learning new frameworks, expanding the arsenal of tools in my toolbox to solve an ever expanding set of problems. But spending my free time developing a new skill with a new tool began to feel like I was working but not getting paid.

And that notion really doesn’t sit well with me. I still love figuring out how computers work. It’s just nice to do so without the added pressure of building something to make someone else happy.

Which brings me to the “side quest” concept Simon describes in this post, which is something I find myself doing nearly every day with ChatGPT.

When I was going through my album artwork on Plex, my first instinct was to go to ChatGPT and have it help me parse through Plex’s internal thumbnail database to build me a view which shows all the artwork on a single webpage.

It took me maybe 10 minutes of iterating with ChatGPT, and now I know more about the internal workings of Plex’s internal media caching database than I ever would have before.

Before ChatGPT, I would’ve had to spend several hours pouring over open source code or out of date documentation. In other words: I would’ve given up after the first Google search.

It feels like another application of Morovec’s paradox. Like Gary Casparov observed with chess bots, it feels like the winning approach here is one where LLMs and humans work in tandem.

Simon ends his post with this:

One of the greatest misconceptions concerning LLMs is the idea that they are easy to use. They really aren’t: getting great results out of them requires a great deal of experience and hard-fought intuition, combined with deep domain knowledge of the problem you are applying them to. I use these things every day. They help me take on much more interesting and ambitious problems than I could otherwise. I would miss them terribly if they were no longer available to me.

I could not agree more.

I find it hard to explain to people how to use LLMs without more than an hour of sitting down and going through a bunch of examples of how they work.

These tools are insanely cool and insanely powerful when you bring your own knowledge to them.

They simply parrot back what it believes to be the most statistically correct response to whatever prompt was provided.

I haven’t been able to come up with a good analogy for that sentiment yet, because the closest I can come up with is “it’s like a really good personal assistant”, which feels like the same analogy the tech industry always uses to market any new tool.

You wouldn’t just send a personal assistant off to go do your job for you. A great assistant is there to compile data, to make suggestions, to be a sounding board, but at the end of the day, you are the one accountable for the final output.

If you copy and paste ChatGPT’s responses into a court brief and it contains made up cases, that’s on you.

If you deploy code that contains glaring vulnerabilities, that’s on you.

Maybe I shouldn’t be lamenting that I lost my joy of learning new things about computers, because I sure have been filled with joy learning how to best use LLMs these past couple years.

I don't know if I'm one of the only weirdos that still uses Plex and listens to MP3s, but dammit, a carefully curated music collection of which I feel some ownership feels critically important to me.

I have started going back in and using the rating systems to rate entire albums.¹ Because this seems like a natural follow up question, I basically only give albums one of three ratings²:

• ★★★★☆ (4 stars): This is an important album to me, but I don't wanna hear it every day.
• ★★★★★ (5 stars): This album is everything right now.
• ★★★★⯨ (4.5 stars): Somewhere in between the two. It is either a 5 becoming a 4, or a 4 on its way to fivedom³.

Doing this gives me the ability to create a smart playlist containing all of the albums with at least a 4.5 star rating.

This morning while getting ready, I uncharacteristically grabbed my iPad and used Plexamp to listen to that playlist on shuffle.

The first thing I noticed on the much larger screen was how awful the album artwork looked for many of my albums.

They looked quite pixelated and blurry. Some of them looked like scans where you could clearly see stickers and thin, diagonal white lines on the sides.

I decided this must be something I rectify tonight.

I've updated the artwork for maybe 50 albums so far, and I'm stunned at how much of a difference it makes to have nice looking album art.

I've had some of these albums for decades now. When I added artwork back in the mid 2000s, the best I could hope for in many cases was a 256x256px JPG that I could find on a message board.

At the same time, the past few weeks gave me several opportunities to pay attention to these albums in a way I never have before.⁴

For most of my life, I generally used music to distract me from my thoughts. I would occasionally listen to the lyrics and look up the meaning of a song, but those details were often secondary to the overall feeling of a track.

Something in the past couple of years changed that in me, though, and now I have been enjoying music on so many more levels. What was an artist going through when they made a song? What was the creative process like? What do these words mean to the artist?

The best system I found was to use the Plex web app on my laptop to select new album art, and then use the Plexamp iOS app to move from song to song, finding songs which had low res album art.

I noticed after a few changes that when I saved the album art on my laptop, it instantly reflected on my phone.

So of course, I started hovering over the "save" button on my laptop, then glanced down at my phone while clicking.

And what you'd see was a cool cross fade where the image got sharper. Cleaner. Fresher. Way more detailed. Way less pixelated.

It allowed me to be a bit of an ophthalmologist, covering one eye, flipping between two different lens strengths and asking whether I preferred option 1 or option 2.

Polishing up my music collection, cleaning up this blog... these were things I used to do for fun.

They were mindless activities. A chance to express myself without feeling any judgement.⁵ To feel accomplished and organized, a little slice of order within a chaotic life filled with incessant disorder.

I have been so busy for the past twelve years that I forgot what fun really looked like.

I thought fun was learning how to build a company. To understand what it takes to build successful and impactful software.

And in many ways, those things were fun. It is really cool to make computers do complex stuff, to build tech that makes people's lives better. It brings me so much joy.

But that's not the only thing that's fun in the world. And I might have done a bit better at relegating those pursuits to my professional life, and then figured out a way to pursue other joyful things outside of that.

It's weird coming back to my media library after essentially neglecting it for most of my adult life. It feels like opening a time capsule, but then jumping down into it and living amongst the decade old cruft.

But it feels good to clean it out and use it again. To treat it like my house instead of a history exhibit.