More from Alex Meub
The park near my house has lots of chestnuts and my kids have been collecting them like crazy (it’s actually their favorite post-school activity). We accumulated quite a hoard. I thought it would be fun to make a launcher so we had something to do with our new chestnut collection. I wanted to go with a very simple crossbow-style design (like the famous D2 item) using latex tubing and a leather pouch for holding the chestnuts. This is what I came up with. It launches chestnuts about 220 feet, and it’s simple enough to build in an afternoon. The frame is a 42 inch 2x2 and a spare IKEA bed slat for the crossbeam, glued and screwed together. A 3/8 inch eye bolt goes through each end of the crossbeam, and the latex tubing is tied to those and to the pouch from a leather shepherd’s sling. Tying the tubing was the fiddliest part. It has to be stretched while you wrap it with butcher’s twine, so I clamped a couple of scrap blocks to my workbench to hold it. I like this design because the tubing can be wrapped around the eye bolts to easily add more tension and power. The Trigger My favorite part of the design was that I decided to use an archery release like this one for the trigger. It provides a safe and reliable way to hold the tubing back, and it’s made to let go cleanly. I 3D printed a little housing that mounts the release securely to the back of the stock, and the release clips onto a loop of archery D-loop cord on the back of the pouch. Then I added a dowel for a rear grip and an old handle I had previously removed from my shop vac. How Well Does It Work? We tried it at the park and it works surprisingly well. Aimed at about 35 to 40 degrees, it sends our chestnuts (on the small side, about 10 to 15 grams) about 220 feet. Thanks to the archery release, we haven’t had a single misfire. I got curious and did some rough math. To go that far with air drag, the chestnuts are leaving at somewhere around 85 to 100 mph, which works out to about the same energy as a paintball. So safety glasses are important and you never point it at anyone. You can find the 3D print on Printables and a full build guide on Instructables. Make sure to always use it with adult supervision :)
Using modern AI coding tools feels like jumping into the cockpit of a BattleMech. My co-worker used this analogy recently and I love it. It perfectly sums up the feeling of vibe coding for me. I can move faster, jump higher and it feels like a there is a whole new world of possibilities available to me. This is true for me as someone who no longer writes code every day, but many experienced software engineers don’t feel this way and I get it. They’ve been running around on foot and learned to be very effective without it. Jumping into the cockpit of something entirely new is jarring. The BattleMech can feel clunky, burdensome and they basically have to relearn all their instincts around movement and orientation (it can also sometimes shoot itself in the foot!). On top of this, many non-technical folks have also jumped into the BattleMech. They are running off in all these strange directions because they don’t know what to use it for. They are copying things, building things that suck and filling social media feeds with their creations. Many software engineers feel the same way as artists did a few years ago because pretty much anyone can create software now. The good news is that domain knowledge and software development instincts are still essential. The BattleMech can be incredible if you know exactly where you want it to go, but it’s also happy to lead you straight off a cliff.
Progress Quest is generally considered the original idle game. It came out in 2002 as a parody of EverQuest and the emerging MMORPG boom. “Playing” it consists of creating a character, clicking “Sold!”, and then watching progress bars fill forever. There’s no interaction, no real gameplay, just waiting. At first glance, it feels like a gimmick — a joke game built to poke fun at the MMO trend. But what’s surprising is that its creator, Eric Fredricksen, built a whole RPG simulation underneath the progress bars. There are 270+ monsters, procedurally named equipment, multiple storylines, intentionally weighted stats, real loot tables, and a surprisingly complex progression system. On top of that, there’s even an authentication system for competitive multiplayer leaderboards that are somehow still around today. I love Progress Quest because of its absurdity, but also because it’s such a good example of something being far better than it needed to be. The amount of effort and attention to detail in this game makes me smile. Exponential Progression At the heart of Progress Quest is a single formula that controls level progression. The time it takes to complete level N is: (20 + 1.15^N) * 60 seconds. That means early levels take minutes (a few hours to get to level 10), while later ones take years (many years to get to level 100). There is also additional time outside of leveling for the player to go to market, buy/sell things, and head back to the “killing fields”. There are still thousands of players active across the remaining multiplayer realms, and pretty much everyone above level 95 has had the game running for over a decade. That doesn’t even count single-player characters. Races and Classes The race and class systems are hilariously absurd, but they don’t affect gameplay at all. The player races are: Half Orc, Half Man, Half Halfling, Double Hobbit, Hob-Hobbit, Low Elf, Dung Elf, Talking Pony, Gyrognome, Lesser Dwarf, Crested Dwarf, Eel Man, Panda Man, Trans-Kobold, Enchanted Motorcycle, Will o’ the Wisp, Battle-Finch, Double Wookiee, Skraeling, Demicanadian, and Land Squid. And the classes are: Ur-Paladin, Voodoo Princess, Robot Monk, Mu-Fu Monk, Mage Illusioner, Shiv-Knight, Inner Mason, Fighter/Organist, Puma Burgular, Runeloremaster, Hunter Strangler, Battle-Felon, Tickle-Mimic, Slow Poisoner, Bastard Lunatic, Jungle Clown, Birdrider, and Vermineer. Hilarious Monster Types There are over 270 hand-crafted monsters, and every one of them has a thematic loot drop. The Giant series imagines what giants would be if they were made of basically anything: Humidity Giant (drops “drops”) Beef Giant (drops “steak”) Rice Giant (drops “grain”) Porcelain Giant (drops “fixture”) Mini Giant (drops “pompadour”) The Golem series follows the same logic: Beer Golem (drops “foam”) Oxygen Golem (drops “platelet”) Cardboard Golem (drops “recycling”) The Scout hierarchy is great: Cub Scout (drops “neckerchief”) Girl Scout (drops “cookie”) Boy Scout (drops “merit badge”) Eagle Scout (drops “merit badge”) The Elemental series is an entirely new take on Elementals: Bacon Elemental (drops “bit”) Cheese Elemental (drops “curd”) Hair Elemental (drops “follicle”) Porn Elemental (drops “lube”) When the game picks a monster to fight, it level-matches against your character and then applies modifier prefixes based on the gap. That adds more flavor to the monster names. Procedural Equipment When you get new gear, the game doesn’t just pull from a list. It runs a little algorithm: Pick a base item matched to your level from a list like Stick → Shiv → Longsword → Halberd Calculate the quality gap between the item’s base level and your level “Spend” that gap across up to two modifier adjectives, each with a point value Whatever is left becomes a numeric +N prefix So a level 40 character might find a +13 Custom Holy Mithril Mail — a level 19 Mithril Mail base, with Custom (+3) and Holy (+5), leaving +13 unspent. The modifier tables are split into good and bad. If the gap is negative — meaning the item is actually better than you — the game pulls from the bad list instead: Rusty, Dull, Bent, Plastic, Nerf (-7), Rubber (-6). There’s also a whole list of spells with names like “Holy Batpole,” “Grognor’s Big Day Off”, and “Roger’s Grand Illusion” that will make their way into your spellbook and increase in level with roman numerals. The Main Game Loop Surprisingly, the game has a real game loop. It works like this: Kill monster task — The game generates a monster with a duration based on your level. When the timer finishes: Loot is added to your inventory, either a specific drop or generic loot XP is gained, which can trigger a level-up Quest and plot bars advance Check encumbrance — After a kill, if encumberance is at or above your limit, you go to market instead of fighting: The game will say “heading to market to sell loot” Then the game sells items one at a time, removing the top item in inventory and adding gold Items with “of” in the name sell for much more This continues until only gold remains Buy or head out — After selling, or if you weren’t encumbered in the first place: If the player’s gold is high enough to buy better gear, the game says “Negotiating purchase of better equipment” and the game upgrades a random equipment slot Otherwise the game will say “Heading to the killing fields” Next kill — After heading out, the game generates another monster and the cycle repeats Stat Progression When you gain a stat point, the game uses a weighted system biased toward your highest stat. Half the time, the gain is completely random. The other half uses quadratic weighting, where each stat’s chance is proportional to its value squared. That creates a snowball effect where your best stat keeps getting better, which feels authentic to how RPG builds tend to work. The only real strategy to playing Progress Quest is trying to roll high STR at character creation. Having higher STR gives you higher max encumberance which affects how often you need to go to market. The thing is, the market trips are such a small fraction of actual game time that this only about a 5% difference in how fast your character will level up. In Conclusion This is probably more than anyone wanted to know about Progress Quest. It’s an absurd, charming little game, and I hope it somehow keeps living forever. If you want to play the “multiplayer” Windows version, you can download it here. I also wanted to play on my Mac, so I vibe-coded an Swift version that runs on modern Mac hardware. See you on the killing fields!
A few years ago, I built a Wi-Fi-controlled Nerf turret, but I never got around to creating a proper build guide for it. When I finally sat down to write one, I realized just how many things I would do differently. That realization quickly snowballed into a full redesign—and the result is a vastly improved version of the SwarmTurret. This new version is not only more powerful and precise, but it’s also easier build. Here are some of the major upgrades: Simplified Assembly: I reused the shell of an existing plastic blaster, which significantly cuts down on 3D printing and makes putting it together much easier. Improved Stability: A new belt-driven Y-axis adds smoother motion and includes an adjustable tension system. Enhanced Accuracy: The camera has been repositioned for better aiming precision. Direct X-Axis Drive: I replaced the original gear system with direct motor control for more responsive movement. Performance Boost: Upgraded from Raspberry Pi 4 to Pi 5 for faster web app performance. Integrated Power Supply: Now features a built-in power supply with an on/off switch—no more fumbling with cables. Web App Enhancements: The control interface is more intuitive and responsive. I’ve published the complete build guide, along with the updated code and 3D printable parts.
More in programming
My now-traditional “summary” of the conference along with my own commentary and thoughts.
Every year, browser vendors collaborate via the Interop project to synchronize their efforts on new HTML/CSS/JS features. This year, there’s a ton of super exciting features being considered! In this blog post, we’ll explore the CSS of the future, to get a glimpse of what we’ll soon be able to do.
Imprint’s average engineer is merging 4x more PRs than 2 years ago. Yay. Aggregated behind the average is something even more interesting: we have two teams that are merging 10x their PRs over that period. One engineer is merging 25x the PRs per week of our average engineer two years ago, and a number are merging 10x. That’s pretty neat, and the slope of the line suggests our average in a year is going to look much closer to today’s p90 than today’s p50. Even more importantly, we aren’t just shipping more, our quality has improved: incidents are down 42% half-over-half, and critical incidents are down 78% half-over-half. I think we’ve always known the quality/velocity tradeoff wasn’t a particularly useful construct, but that’s undeniable today. As we’ve walked this path, we–like everyone else progressing down it–have run into the problem of pull request review. The p50 pull request review took about 33 minutes to complete 2 years ago, but now takes us about 77 minutes. The slope here correlates tightly with the number of pull requests getting merged. Tightly enough that addressing it became one of my priorities for the week. We solved it! Just kidding, we’ve absolutely not solved it, but I think our current approach is an interesting one, which we call the small-change. The work discussed here was shaped and done by many folks at Imprint including Dan, Joy, Daniel, Lenny, Taylor, Ted, and Annie, among many others. Why review pull requests? There are four reasons we review pull requests: Knowledge sharing between author and reviewer – software engineering is generally learned via apprenticeship, and reviews are a primary mechanism of experienced engineers teaching others what good software looks like. We believe the current volume means that this knowledge sharing will have to move towards operating on clusters of pull requests, rather than individual pull requests Preventing errors – review has always been an expensive time to catch errors, and we believe that effective CICD along with harness verification techniques like poteto’s pstack are more effective mechanisms for preventing errors than review Preventing malicious behavior – my experience is that even careful code review will generally miss competent malicious behavior, although fortunately most malicious behavior is incompetent. We believe both sorts of behavior are best identified using a combination of fixed rules (modifying these specific objects/classes/files requires review), anti-abuse mechanisms that we’ve refined in our LLM-based member support experiences, auditing, and audit log inspection Compliance obligations in our documented controls – these can be changed, but today they require that an independent human reviews changes in a subset of our repositories In the modern development paradigm, we think there is a better solution for each of these problems. But, we also want to make these changes very cautiously. Small steps with small-change We believe we move fast by finding narrow, contained ways to validate new practices, so to iterate our way into an effective solution, we’ve developed the concept of a small-change. Here’s how it works: When a pull request is marked ready, CICD determines whether it is eligible to be a small-change. This is represented as a passing Github check. There is also a label for visibility, but it is the check itself, managed by the build and not human modifiable, that determines eligibility. (The label is used for initial filtering, but the check is still independently verified.) Something is a small-change if it meets all of these criteria: It is less than 1,000 lines of code There are no p1 or p2 findings from our ai-code-review automated review bot The author has “experience” in the service or application, defined as 10+ prior merged pull requests into that service or application’s directories. For changes working across multiple services or applications, the author must have experience in all of them to qualify Impacts fewer than N distinct services or applications. N is 1 on our frontend monorepo, and N is 3 in our backend monorepo, where typical changes will modify both a gRPC service and a common HTTP gateway Shared libraries and utilities files are not eligible for small-change Each repository has a .small_change file which allows per-path customization while we continue to tune the behaviors. For example, a service dealing with money movement can be excluded Our Slack automation tags every reference to a pull request with reacji labeling the state of that pull request, for example if it has failing tests, if it has been approved but tests are still running, or if it is ready to merge. We added a small-change reacji that indicates which of those pull requests meet the small-change criteria In our internal skills repository, we created two skills that have been distributed across harnesses: review-small-change which takes a list of repositories and reviews all open, non-draft, small-changes, including providing approval if they meet the review’s criteria (all checks pass including small-change check, and not touching on sensitive topics such as payments and security) review-pr-cluster which reviews batches of pull requests to identify common themes that came up, and suggest opportunities for discussion and adding verifications We set the social expectation that any error caused by a small-change is a failure in our system, and has to be solved at the system level: improvements to ai-code-review, to our verification mechanisms, to our CICD, to our harness, etc. This took about two days of infrequent attention to implement and rollout, although I imagine we will be tuning the knobs here for a long time. Maybe forever. fleet: centrally orchestrated harness I’ll briefly mention our other approach to reducing code review volume, which anchors on our centrally-orchestrated harness, fleet. (Which is similar to Stripe’s Minions although not following the one-shot approach in particular). We rely on fleet to implement and verify software in a highly controlled harness running in the cloud, with independent evaluation mechanisms to identify the correct number of independent reviewers for any given change. That number can be as low as one (e.g. fleet writes, one human reviews) for changes evaluated as safe. Results / next steps / reception I’ll be honest, it’s too early to give a useful result here. From early results, about 10% of changes qualify as a small-change. Those are now eligible for very fast approval, and generally get it unless they trip a flag, generally due to touching a security or money adjacent topic. While 10% is a small percentage, the core concept here is working, and ultimately will succeed or fail based on our ability to expand that percentage over the next few months in tandem with expanding our verification mechanisms to be increasingly comprehensive. This is ultimately going to fail or succeed depending on our ability to improve our verifications, which does require more difficult sorts of techniques to accomplish in low scale-complexity, high domain-complexity software than in the high scale-complexity, low domain-complexity products where many techniques like incremental rollouts are exceptionally effective. (Don’t get me wrong, they still work, they just provide less coverage when most users have different configuration and behavior.) Folks have not been uniformly excited about this, it’s a substantial change from how we’ve learned to be good engineers, and it’s uncomfortable to reevaluate whether a long-held best practice has become merely dogma. The most energizing part of the current cycle is that we get to reevaluate these practices we grew up on every week; the most painful part of the current cycle is that we’re likely to fall behind if we ever stop reevaluating them.
The park near my house has lots of chestnuts and my kids have been collecting them like crazy (it’s actually their favorite post-school activity). We accumulated quite a hoard. I thought it would be fun to make a launcher so we had something to do with our new chestnut collection. I wanted to go with a very simple crossbow-style design (like the famous D2 item) using latex tubing and a leather pouch for holding the chestnuts. This is what I came up with. It launches chestnuts about 220 feet, and it’s simple enough to build in an afternoon. The frame is a 42 inch 2x2 and a spare IKEA bed slat for the crossbeam, glued and screwed together. A 3/8 inch eye bolt goes through each end of the crossbeam, and the latex tubing is tied to those and to the pouch from a leather shepherd’s sling. Tying the tubing was the fiddliest part. It has to be stretched while you wrap it with butcher’s twine, so I clamped a couple of scrap blocks to my workbench to hold it. I like this design because the tubing can be wrapped around the eye bolts to easily add more tension and power. The Trigger My favorite part of the design was that I decided to use an archery release like this one for the trigger. It provides a safe and reliable way to hold the tubing back, and it’s made to let go cleanly. I 3D printed a little housing that mounts the release securely to the back of the stock, and the release clips onto a loop of archery D-loop cord on the back of the pouch. Then I added a dowel for a rear grip and an old handle I had previously removed from my shop vac. How Well Does It Work? We tried it at the park and it works surprisingly well. Aimed at about 35 to 40 degrees, it sends our chestnuts (on the small side, about 10 to 15 grams) about 220 feet. Thanks to the archery release, we haven’t had a single misfire. I got curious and did some rough math. To go that far with air drag, the chestnuts are leaving at somewhere around 85 to 100 mph, which works out to about the same energy as a paintball. So safety glasses are important and you never point it at anyone. You can find the 3D print on Printables and a full build guide on Instructables. Make sure to always use it with adult supervision :)