gave argon 4 a try and it:
- failed to understand the original problem & started solving something else
- hallucinated a lot of methods even after providing a plan
- burnt through a lot of tokens comparatively
- and confidently made up some performance improvement numbers 😭
this one errand has been on my todo list for so long that i just moved it to Q1 2027, jab dekha jayega 😭
next step: expose this over to instinct and let it randomly toggle the height throughout the day 😭
Reverse engineered my standing desk firmware to control it directly from my mac.
github.com/vinayjn/desk
ayush retweeted
presenting beacon :
network gives out at every big show. one trip to loo or bar and your friend group is split for the night
beacon lets you make a squad for your next event, text and send voice notes, see everyone on the venue's own map, walk straight to a friend, and alert the whole squad with where to meet
check it out - reticket.in/beacon
ayush retweeted
The thing I learned this year is that when engineers say they like working on “hard problems”, they actually don't. What they like is puzzle solving, and having a repertoire of patterns that they can pattern match onto traditionally hard problems, usually involving databases or something with scale, etc. And they know that the industry used to pay you a lot for how deep and broad this repertoire was. Unfortunately, in 2026, well, you have a cheat code machine that has infinite breadth and depth for pattern matching. So the question is, do you actually like hard problems? Because there are now hard problems that are a complection of engineering, product, society, culture, politics, and they are fairly intractable, probably unsolvable! Because if you do want to work on those actually hard problems, there is so much money that people will pay you for it. But you’ll have to face that truth about yourself first.








