I’ve added an ActivityPub plugin to my blog. I LOVE the idea of just using my own platform and having it published to followers wherever they are. Let’s see if I can get this to work
How to Sleep: Part 2
Equipment
As a follow up to part 1 I’d like to take some time to talk about some of the devices I use to help me listen to audio books and get to sleep.
When I was single, I mostly listened to audiobooks on my phone speaker or on something like a Homepod Mini in my bedroom. However, once I was married, my wife and I wanted to listen to different books and that meant we needed headphones so we would not disturb the other person.
A surprising benefit of this was that the headphones also kind of act like ear plugs, blocking out street noise of which there is a A LOT in NYC.
Sleepytime Headphones
The best headphones for most people are the Sleeper Wireless headphones from sleeperbuds.com
⭐️⭐️⭐️⭐️⭐️
ALL sleep headphones will take some time to get used to, but these are some of the easiest to use, lightest, most comfortable and at $30 you can’t really go wrong.
I first discovered these on https://www.adv-sound.com/ after visiting their booth at CanJam in NYC. In general they are quality headphones at very reasonable prices. They eventually spun this product line off to https://sleeperbuds.com specifically for these. They were also the very first headphones I found specifically billed as being for sleep.
Since then a number of other headphones specifically for sleep have cropped up, but are less great in sometimes small and sometimes big ways.
Gotchas
Because there ear tips aren’t swappable they may not fit very well in your ears or provide the best seal against outside noise depending on the shape of your ear
The Upgrade Pick
⭐️⭐️⭐️⭐️⭐️
Significantly more expensive than sleeper buds, but cheaper than Kokoon, these earbuds are basically perfect.
Lots of fit options to swap to find both he most comfortable fit, but also the best noise isolation for your ear shape.
Battery lasts easily all night. Case and headphones appear to be able to charge at the same time. They are true wireless meaning no cables pulling on you as you turn at night. Low profile for side sleeping.
https://www.sleepphones.com/
⭐️⭐️⭐️
These originally were pretty good in terms of comfort and sound quality but after a design change made the headphones themselves out of a harder plastic, they became too uncomfortable. They also tended to slide around on my head as I tossed and turned at night.
They also don’t do a great job of blocking out street noise, so I had to pair them with some standard ear plugs for life in NYC
Kokoon Nightbuds
⭐️⭐️
Crazy Expensive at $250. I had originally backed these on Kickstarter. They were comfortable, the sound was good. Some of the buttons for adjusting volume broke after a few months of use and when I reached out to customer support they said it was out of warranty (less than a year?).
The sleep tracking never really worked for me, it would always shut off too soon and I’d have to restart my book as I was drifting off to sleep.
This was all before they were purchased by Philips so I don’t know how the product quality or customer support quality have changed since the acquisition.
Honorable Mention
Advanced Sound Group ADV. Sleeper TWS
⭐️⭐️⭐️⭐️
I wanted to love these. They are very nearly perfect except for some critical flaws.
These are the best fitting, best sounding sleeper ear buds. They are true wireless which means no cord pulling on you when you turn over. They last 5 hours which is plenty of time to fall asleep. They also feature active noise cancelation making them even better at blocking out unwanted street sounds than any other headphones I’ve tried.
When these first came out I bought a couple pair as they were only $80 (most sleep earbuds are well over $100+ and often closer to $200+). The first night they startled me awake by very loudly announcing “LOW BATTERY!”
I emailed customer support asking if there was anything they could do on the Firmware, they had a meeting and made the change, offered to re-flash my headphones for free if I just sent them in. Amazing. Every pair I ordered after that did not have the annoyingly loud low battery alert and instead would just die silently when they ran out of battery. Perfect
But all was not well, and I guess that’s why they’ve abandoned this product. The big issue is charging. The case and headphones don’t charge as one would expect, or at least if you’ve ever used AirPods you’ve come to expect that you can charge both the case AND the ear buds at the same time but that’s not the case here and it breaks my heart.
Instead it seems like you have to charge the case, and then charge the earbuds. Meaning you can’t just take them off in the morning, pop them in the case, pop the case on the charger (they offer wireless charging) and be on with your day confident that you’ll have fully charged headphones that night. Instead you’re surprised at bedtime when you take the case off the charger that your ear buds have no power at all 🙁
The best workflow I managed to come up with was:
- Take ear buds out of charging case
- Put charging case on charger
- In the morning remove charging case from charger
- Put earbuds in charging case OFF charger
I found this difficult enough to keep up with that I removed a star and can only give these 4 stars even though they are perfect in almost every other way.
The other issue was with connectivity between the two ear buds. I would pretty regularly only get sound out of 1 year. You could sometimes get the other ear to work if you put it back in the charging case for a second and then put it back in your ear, but not always.
How to Sleep
For most of my life I’ve had a problem. I have always had trouble getting to sleep, sometimes leading to being in bed, tired, but still quite awake way later than I’d like. Over the years I’ve worked hard to correct this. I’ve invested a bunch into having a healthy bedtime routine, consistent, less blue light, only use the bedroom for sleep, etc. but I am unwilling to give up on caffeine completely which is probably the culprit.
What to do instead?
Well the biggest problem for me was that my mind would be racing and looping over things again and again. If that sounds like you, then have I got the trick for you. Audio books.
You see, I had realized that falling asleep with the TV would make it so my mind doesn’t race as I pay attention, but the pressure was always there to open my eyes to see what was going on. But Audio books are perfect* at giving you something to engage with, but no need to open your eyes.
But you have to choose the right book. If a book is too compelling, you’re just as likely to stay awake all night listening. This has happened to me a couple of times. On the other hand if a book is too simple or boring then your mind will race anyway as it stops paying attention.
What’s the perfect balance? LitRPGs.
LitRPGs are books where the main character is embodied in a role playing video game (usually). The stories are fun and interesting, but the reading aloud of stat sheets is decidedly not which gives them a good balance.
Here are a few that I think are great, or at least great examples of the genre:
Classic LitRPGs
Magic, but no explicit ties to video games
Deck building
Midly
A week ago I did something I’ve always wanted to do. I launched my first iOS App.
It’s a simple app that solves a niche problem I was having: I wanted to see my friends more in real life.
However, as I’ve gotten older and have more responsibilities I’m finding planning small get togethers to be more cumbersome. My hope is that if it’s easier to do, I’ll do it more often.
This app helps with that by automating a few steps that had me juggling three windows/apps to find a place to meet up.
Step 1
Enter all the locations where people will be coming from. Add as many as you like. They can be contacts in your contact list, businesses, street addresses, a neighborhood, etc.
Step 2
Press the “meet in the middle” button and get place suggestions between everyone.
That’s it
You don’t even need to login. It’s FREE. I don’t track any data. No plans to make it a business. There are a few more features coming as I get time to add them. Check it out. Could be useful to people here if you do a lot of coffees with folks in diffferent places. I wish I’d had this back when I was dating.
As I write this I’ve just added another major feature that is waiting for App Store approval. The ability to save the groups you create and easily recall them in the future. This is a big step towards making this into the recurring dinner planning app of my dreams.
A case for minimizing moving parts in a build
Unrolled Tweet Thread
If we take the chance that a tool (compiler, linker, batch, whatever) remains working for a particular codebase after one year as a given probability p, then the chance that build remains working after x years is pxn, where n is the number of tools used in the build.
That’s “just math”. Even if we assume a 99% chance that a tool still works on the codebase after a year (an extreme rarity these days!), that graph looks like this:
With just one tool, the build has an over 95% chance of working after five year. With ten tools, it has only a 60% chance! And that’s with every tool having a _99%_ chance of remaining working (meaning no breaking changes to the tool that affect the build in question).
If we assume a still probably favorable given today’s environment, but slightly lower p of 90%, the graph now looks like this:
This is, of course, an epic disaster. With just 3 tools used, after 5 years there is _very little chance_ that your codebase will still build correctly. And that’s at 90% and just 3 tools!
If you look at 90%/10 tools, heaven forbid, that bottom line says your build almost certainly doesn’t work after only 2 years… and in fact has barely a 30% chance of working after just 1 year!
Now imagine that we don’t say “tool”. We just say “dependency”. The equation _remains the same_. Modern codebases often have 10s, 100s, or even 1000s of dependencies! What does that do to this graph?
Here is the graph of 10, 100, and 1000 dependencies, assuming a never-happens-on-github percentage chance of a dependency not breaking your build at 99%:
10 dependencies sort-of works. It has a 60% chance of still working after 5 years. 100 dependencies doesn’t work. It’s less than 40% after just 1 year. 1000 dependencies breaks with almost complete certainty after a mere _four months_.
All of this is already something you know intuitively. Projects with lots of dependencies never work out-of-the-box. You are constantly updating, patching, and struggling to get their builds working, because every time something downstream changes, somebody has to fix it.
The “dependency culture” of modern programming has put us into a state where software requires perpetual, constant maintenance. No longer can we take a build and say “this works” and come back to it in a year. Great for job security, horrible for software quality.
As for speculation, I wonder, at least in part, if this answers the questions me and other people like me have, which is how do companies like Twitter employ thousands of developers while seemingly producing almost no additional software or improvements?
Well, if you assume that Twitter’s collective codebase is a 1000+ dependency nightmare, as I assume it probably is, then the math kind of tells us the answer: the vast, vast majority of their time will have to be spent simply keeping their existing code working.
Casey Muratori (@cmuratori)
Musk’s Rules for Engineering Design
1. Make your requirements less dumb
As engineers we are often given a list of requirements from someone else. We just accept them and start trying to design. We trust that other people know what they’re doing in part because our entire educational career we could never question the premise of a problem. The teacher says “Solve this” and you solve it – you don’t get to say “This is a dumb question” (Unless you’re fine failing as I was with Prof. Dempsey in Calc 3)
Musk goes on to say that in order to allow people to question the requirements, there’s another rule that goes along with this one.
1.a All requirements must have a person associated with them, not a department.
You can have a reasoned argument with a person but try arguing with a “department” and you’ll soon find yourself in a Dilbert Cartoon.
2. Delete the part or process
If you are not occasionally (say 10% of them time) adding things back in, then you aren’t deleting enough.
3. Simplify or Optimize
The most common error of a smart engineer is to optimize a thing that should not exist.
Once you have less dumb requirements, and you’ve eliminated as much as you can from the design only then try and optimize what’s left. These first 3 rules are really trying to get at one problem. The problem of really smart engineers trying to optimize the system they’ve been given rather than thinking about things from base principles and then optimizing. We tend to jump to optimization.
4. Accelerate Cycle Time
You’re going too slow, go faster.
5. Automate
Only once all the other steps are complete, only then should we then try and automate a process. Doing it this way unlocks a few really nice properties. Automation takes longer to setup and get working but pays dividends in the future. However, those dividends only come if you’ve automated the right thing.
The Discipline of Software
One of the things I find the most difficult to teach is the discipline to solve exactly the problem that is in front of you, and only that problem. Solve it in the simplest way you can think of. Be confident that in the future if new requirements arise, such as improved performance, you’ll be able to make a “better” implementation to account for the new requirements. Then move on to the next real problem.
I think this is kind of like the joke that if you ask a lawyer if they know the time, they’ll say “Yes”.
Another way to say this might be: Solve real problems, not imaginary ones. It can be difficult to tell the difference. Our brains are equipped with a simulation engine that allows us to imagine things that aren’t really there. Imagine a sparrow with orange stripes. If you don’t suffer from aphantasia then you likely saw exactly what was described. What you might not have noticed is that while you saw the bird, the real world blanked out. The simulation engine takes over our real senses to run its simulation. You can imagine something scary and you will be scared even though it is not real.1 In this same way the problems you think of can feel real. This is an illusion and the way to combat that is to say you’ll only work on problems that have real evidence, a real example, an actual data set, not imagined scenarios.
Ask yourself: “Is this requirement real or is it just a thought?“
“Yes, but you only have to implement it once! So you should take the extra time to do a good job!”
That assumes you’ve correctly predicted the future and the code is used exactly the way you thought it would be. If you have this ability and care at all about money, you should be playing the stock market and not writing code for other people. I have learned the hard way that I do not. I’ve implemented complex solutions that took a long time to write only to discover that some requirement I didn’t think of has broken it completely effectively requiring a redesign to handle the new scenario.
This is how I code. I work this way because I’ve discovered that I’m not particularly good at predicting the future. I can imagine all kinds of problems that are not real, they’re just thoughts. Trying to account for all of these imagined problems leads to very complex solutions. Complex solutions are difficult to reason about, difficult to implement correctly, take more time to implement than simpler or more naive solutions. They are more difficult to debug and fragile to changing requirements (the ones you didn’t imagine).
Practically what I’ve found is that sometimes the naive implementation is all you need. It’s sufficient for the problem sizes you’re dealing with, and you saved yourself a ton of time by not implementing something more complicated with better performance. You were able to move on to add more value to the project quickly because you implemented an N^2 algorithm in a hour instead of taking a week to write a much more complex solution. And it was fine. If it isn’t fine, then you’ll know that pretty quickly, and you’ll have actual evidence to justify taking the time to create a more complex implementation. You can point to the real data you’re trying to process and say “this is the reason I need more time”.
I am starting to wonder if this is something that can even be taught. Is this a conclusion one needs to come to on their own? Through their own experiences. After all, that is how I have come to this philosophy.
I have, on several occasions, had more work than I could possibly do under tight deadline. The argument that deadlines are arbitrary falls on deaf ears when you are burning cash and have no product to sell. Working code today is better than perfect code tomorrow. What good is perfectly written code that nobody uses? Nobody uses it either because it wasn’t what they actually needed to solve their problem (you predicted wrong, but spent a long time implementing the wrong thing), or worse your company no longer exists because it blew through all it’s cash before you could make a single sale.
While we could go back and forth about the benefits of a strict adherence to any programming philosophy: Static vs Dynamic, Agile vs Big Design Up Front, Types vs Tests, DDD, CQRS, TDD, etc. One thing I will say is that if you want to get better at this discipline, I think that some amount of Test Driven Development is the best way to practice this.
Notes:
1. The information about the brain’s simulation engine can be found in the book Stumbling on Happiness by Daniel Gilbert of Harvard University
Map of Off Leash Dog Friendly Parks in NYC
All the information above was taken from https://www.nycgovparks.org/facilities/dogareas and encoded to the best of my abilities. I’ve tried to encode the rules for the specific park in the description when you click on the pin but if you know more specific details let me know in the comments and I’ll do my best to keep this map up to date. Enjoy!
How to make Kaleidoscope your default Git Diff and Merge tool
First you need to grab the ksdiff command line tool and install it
https://www.kaleidoscopeapp.com/ksdiff2
Then the following set of commands will set kaleidoscope to be your default diff/merge tool
git config --global diff.tool kaleidoscope
git config --global difftool.kaleidoscope.cmd '/usr/local/bin/ksdiff --diff "$LOCAL" "$REMOTE"'
git config --global merge.tool kaleidoscope
git config --global mergetool.kaleidoscope.trustExitCode true
git config --global mergetool.kaleidoscope.cmd '/usr/local/bin/ksdiff --merge "$LOCAL" "$REMOTE" --base "$BASE" --output "$MERGED"'
Then to run it
$ git difftool FILE1 FILE2
$ git mergetoolMindfulness Twitter
I’ve started a serious mindfulness practice and it’s been really great. I’ve been practicing on and off for years, but my wife has never really given it a go. She, like many, doesn’t really feel anything or understand what it is they’re supposed to feel. What does success look like?
Different analogies work better for different people. The one that has worked particularly well for me has been two parts.
- Your thoughts can come and go, and you can observe them separately from interacting with them, like sitting on a park bench watching people walk past.
- When you inevitably get lost in thought, you can bring yourself back gently to the practice like taming a wild horse. Slowly, pulling in further as the thoughts circle around you.
This didn’t work so well for my wife, but recently we’ve stumbled on a breakthrough. Your brain is like Twitter.
You can imagine your mind like the Twitter timeline. You don’t really have much control over what tweets appear, save for a little bit of signal based on who you follow initially. Your thoughts are the same, you can control your environment and what information you’re exposed to – but which thoughts show up, you have little control over.
Further, like the Twitter timeline you have a choice. You can look at each Tweet and let it scroll past or you can engage with it. When you engage with a Tweet by clicking like, retweet or commenting that signals to the Twitter algorithm (which is optimizing for engagement, not what you’d actually like to see) that it should show you more like that. Again, the analogy holds for thoughts. Thoughts appear in your head and you can look at/observe them without engaging further. Or you can engage and your mind is likely to show you more of the same.
If something is making you angry, and you think you can stay angry without your mind constantly generating reasons why you’re perfectly justified to be angry, you are mistaken. If something your timeline is making you angry… Ok, I think you get it.
I always pick on Twitter on this blog, but the same can be said for any social media with an algorithmic controlled timeline. Facebook, Instagram, etc.
I think ultimately this is exactly why these algorithms are so addictive. Because they mimic the natural thought process so incredibly well. Just like opioids are addictive because they mimic endorphins. They’re not the same, but tell that to your brain.