- The "kitchen" area is so tiny, if you want water you will queue, there are only 2 places on the whole floor where you can get it and they are tiny rooms where at max 5 ppl could enter, 3 comfortably.
- Queues at the bathroom, there are 2 stalls, for the whole floor, I couldn't find another one (I really hope there is one more, I just failed to find it, I did ask, nobody knew about another one). This got worse and worse as the week progressed. I've noticed a similar issue at my previous employer (5Y old building, part of why I left, health issues that are greatly improved by the access to a toilet)
- They implemented some eco-friendly lights, with movement sensors. This sounds great and I am for helping the environment, the problem is that in practice these lights turn on-off every few minutes, during the day, in summer, in a sunlight filled building. My eyes were so tired every EOD.
- In the same eco-friendly manner they made the AC not run during the night and morning. So, if you respected the work schedule and came to the office in the morning it was hotter than outside. It's summer, we had 30C in the morning, 47C in the afternoon. I needed to wait for 1-2h for the AC to kick in and recover after arriving in the office.
> At the macro level we spend a great deal of time designing, estimating and planning out projects, to ensure that our expensive coding time is spent as efficiently as possible. Product feature ideas are evaluated in terms of how much value they can provide in exchange for that time - a feature needs to earn its development costs many times over to be worthwhile!
Maybe I am spending my life working at the wrong corporations (not FAANG/direct tech related), but that doesn't match at all my experience. The `design` phase was reduced to something more akin to a sketch in order to get faster iterating products. Obviously that now, as you create and debate over more iterations, the time for writing code is increased (as you built more stuff that is discarded). What is that discarded time used for? Well, it's the way new people learn the system/business domain. It's how we build the knowledge to support the product in production. It's how the business learns what are the limits/features, why they are there, what they can offer, what they must ask the regulators etc.
Realistically, if you only count the time required to develop the feature as described, is basically nothing. Most of the time is spent on edge-cases that are not written anywhere. You start coding something and 15m in you discover 5-10 cases not handled in any way. You ask business people, they ask other people. You start checking regulation docs/examples, etc. etc. Maybe there are no docs available, so you just push a version, and test if you assumptions are correct (most likely not...so go again and again). At the end of this process everyone gains a better understanding on how the business works, why, and what you can further improve.
Can AI speedrun this? Sure, but then how will all the people around gain the knowledge required to advance things? We learn through trial and error. Previously this was a shared experience for everyone in the business, now it becomes more and more a solitary experience of just speaking with AI.