Rumesh Eranga retweeted
Vibe coders everyday struggle in 15 seconds.
Readers added context they thought people might want to know
The original creator of the video is Nathan Doan, from Nathan Doan Comedy on YouTube, and the present watermark is not affiliated with him. The video is stolen and will result in losses for the original creator.
youtu.be/83cDUAJnyR4
Rumesh Eranga retweeted
I've got an agent in a loop optimizing a renderer with the goal to minimize frame times (and tests to measure). It got times down from 88ms to 2ms and allocations down from ~150K to 500. Sounds good, right? Wrong. This is exactly why agent psychosis is a big fucking problem.
As an experiment, I rewrote the Ghostty core render state in Go, with access to identically laid out data structures as Ghostty and the exact same validation tests. I made a purposely naive renderer (simple, correct, but slow). 88ms per frame with 150,000 allocations (horrendous, lol)!
I then kickstarted a Ralph loop to bring the frame times down. I told it it can't modify input data structures or the public API or tests (they're correct), but it can do anything else it wants. It got to work.
It has worked for about 4 hours. I've spent around $350 on this experiment so far. The results?
88ms => 1.5ms
150K allocs => ~500 allocs
Incredible right? Nope.
My hand-written renderer I ported has frame times (same benchmark) of ~20us (0.020ms) and 0 allocations in the update path.
This is the problem with psychosis and lacking systems understanding. If you don't understand the system, you're going to accept that this is an incredible result. If you understand the system, you'll see better solutions immediately and can do roughly 75x better on throughput.
The people who blindly trust agent output are in the former camp. They're sheeple, overdrinking from a fountain of mediocrity.
Standard disclaimer: I use AI all the time. I like AI. The point I'm making is to not blindly accept results. Think. Analyze. Learn.
Rumesh Eranga retweeted
Fork your dependencies, trim them to only your use case, never update unless it breaks for your users. I’ve been vocal about this for 10+ years. I’ve always said that updating is way riskier than latent bugs (which can be tracked and CVEs monitored).
If you are updating a dependency, it’s on you to analyze every single commit in the full transitive set of dependencies. If you dont see anything compelling, dont update!
I remember at HashiCorp once in awhile an engineer would try to update a dep or replace a DIY lib with an external one and id always ask “show me the commit we need.” Dont update for the sake of it.
Feeling pretty swell about this mentality with all the supply chain attacks happening.
Rumesh Eranga retweeted
AIs writing PR/issue descriptions that are overly long and contain tons of unnecessary detail are like dumb people who keep talking and using big words about bullshit that doesn't matter in an attempt to sound smart. Also, this is going to drive me to crash out.
Rumesh Eranga retweeted
Everyone: AI!
Literally everyone: AI!
Apple: look at this new font that looks like glass for your Home Screen how magnificent and incredible only Apple can deliver this reimagined experience for you.
Rumesh Eranga retweeted
We’ve raised $17.2M to help tax professionals take control of tax season.
We’ve brought together some of the highest-performing talent from the best companies—and we’re looking for more.
Now it’s heads down. Build fast. Fix tax. 🔥
Proud to be part of the team
Replying to @FiledLeroy
We raised $17.2M to give tax pros leverage—not chaos–from @NorthzoneVC @Jess_M_Schultz, @DayOneVC @mashadrokova, JVentures, @Neo @apartovi, RaineVentures @GSRubenstein, and GreensVentures and an amazing crew of angels. 🙏
Rumesh Eranga retweeted
To the firms that believed in us early, our investors, our extraordinary team, thank you
Now we’re opening early access to a select group of firms
Rumesh Eranga retweeted
If you're done surviving tax season and ready to forge a new path, this is your moment
📩 Apply here: filed.com/early-access
Rumesh Eranga retweeted
Filed is an AI tax preparer built to fit the way firms already work. No rip-and-replace. No black box. No late-night chasing PDFs. Just faster prep, cleaner reviews, and compounding accuracy over time
Read more from @DominicMadori in @TechCrunch: techcrunch.com/2025/05/21/fi…
Rumesh Eranga retweeted
We raised $17.2M to give tax pros leverage—not chaos–from @NorthzoneVC @Jess_M_Schultz, @DayOneVC @mashadrokova, JVentures, @Neo @apartovi, RaineVentures @GSRubenstein, and GreensVentures and an amazing crew of angels. 🙏
Rumesh Eranga retweeted
We decided to help tax pros actually enjoy tax season. Not survive it. Not dread it. Enjoy it
A crazy idea? Maybe
Until it worked 👇
Tried to unsubscribe @NotionHQ emails for days and still they are emailing. Super irritating.
A simple plugin @Ashanfer @mjmrz and I made many years ago. (No longer maintaining though)
github.com/99x/serverless-dy…
Rumesh Eranga retweeted
There are over 1,000 engineering blogs. Here are my top 9 favorites:
- Netflix TeachBlog
- Uber Blog
- Cloudflare Blog
- Engineering at Meta
- LinkedIn Engineering
- Discord Blog
- AWS Architecture
- Slack Engineering
- Stripe Blog
Over to you - What are some of your favorite engineering blogs?
--
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Rumesh Eranga retweeted
More context: This was in 2016, and at the time the bundling infra was already 4-5 years old. It is still ahead of its time even today!
The bundling infra works by bundling JS files together "automatically" (via ML) based on an amount of variables that is incomprehensible to humans, including user-specific things like location, language, thousands of concurrently running A/B tests, together with the usage of each individual JS module. Consider for example that you are rolling out a completely new news feed and you want to A/B test it, first with 1% of users but eventually with 50% of users. If you bundle the new code together with the old code all the data like load times will be skewed, or 99% of users might download code they don't use. This system optimized for all of these cases to keep bundle sizes down and eliminate variance in testing. It's amazing!
The way it generated bundles was by running once every 24 hours based on the latest set of production data. Relative paths were used as "ids" to identify a module. If the ids were unknown, it was assumed the file was new and wouldn't be bundled until 24 hours later. Removing one set of files and directing the bundler to another folder with the same layout would make the bundler think all files were new.
In response to this breakage the system was changed to rely on unique module ids (which we already had) instead of relative paths. There were tons of other improvements to this infra since.














