Recently built something where simple domain-specific heuristics crushed a fancy ML approach I assumed would win. This has me thinking about how often we reach for complex tools when simpler ones would work better. Occam's razor moments.
Anyone have similar stories? Curious about cases where knowing your domain beat throwing compute at the problem.
I have a silly little internal website I use for bookmarks, searching internal tools, and some little utilities. I keep getting pressure to put it into our heavy and bespoke enterprise CICD process. I’ve seen people quit over trying to onboard into this thing… more than one. It’s complete overkill for my silly little site.
My “dumb” solution is a little Ansible job that just runs a git pull on the server. It gets the new code and I’m done. The job also has an option to set everything up, so if the server is wiped out for some reason I can be back up and running in a couple minutes by running the job with a different flag.
I wrote a clone of battle zone the old Atari tank game. For the enemy tank “AI” I just used a simple state machine with some basic heuristics.
This gave a great impression of an intelligent adversary with very minimal code and low CPU overhead.
I occasionally see people complaining about long TypeScript compile times where a small code base can take multiple minutes (possibly 10 minutes). I think to myself WTF, because large code bases should take no more than 20 seconds on ancient hardware.
On another note I recently wrote this large single page app that is just a collection of functions organized by page sections as a collection of functions according to a nearly flat typescript interface. It’s stupid simple to follow in the code and loads as fast as an eighth of a second. Of course that didn’t stop HN users from crying like children for avoiding use of their favorite framework.
I remember Scalyr, at least before they were bought by SentinelOne basically did parallel / SIMD grep for each search query and consistently beat data that was continually indexed by the likes of Splunk and ElasticSearch.
I’m mostly a hardware engineer.
I needed to test pumping water through a special tube, but didn’t have access to a pump. I spent days searching how to rig a pump to this thing.
Then I remembered I could just hang a bucket of water up high to generate enough head pressure. Free instant solution!
The common one I fought long ago was folks who always use regular expressions when what they want is a string match, or contains, or other string library function.
Seen people tripped up with dynamodb like stores, especially when they have a misleading sql interface like Azure tables.
You cant be "agile" with them, you need to design your data storage upfront. Like a system design interview :).
Just use postgres (or friends) until you are webscale. Unless you really have a problem amenible to key/value storage.