Do you really need that amount of RAM when SSD and NVMe storage is so fast and high-bandwidth nowadays? Just add some swap space and be done with it. Wear and tear on the underlying Flash media is not the problem it once was, given how big SSD's are these days - and you can use SMART statistics to keep track of any emerging issue from that POV.

I need it when working with huge source trees. Windows sucks at that and extra memory that allows for more caching helps. Mac sucks less in that respect. Still git status on Intel MacBook Pro 2020 takes 2-3 seconds while on Thinkpad X280 from 2017 with Linux it took less than a second.

Maybe it's just that many people find 16GB is enough for their use cases :) (I actually cannot think of any use cases for an ultra-portable when you would actually need more than that)

Ultra portable is a definition of form, not function. I want to run the same Qubes on my laptop as I run on my desktop.

This applies to normies too. I mean, it's nice to have (web/g/hot)mail, slack, skype, messenger, element, discord open in the background while surfing the web and I doubt that 16GB will be enough for long.

What if I want to run photoshop and illustrator at the same time? Heaven forbid, they rewrite those power tools to run on electron.

I can run all of those workloads in 16gb of ram without issue without a swap partition or pagefile enabled on my windows partition, the only thing that might struggle is multiple vms, but that isn’t a typical workload, which is why more than 16gb is so rarely seen.

Normies use their phones for that.

Ultra-portable is a feature, not an end goal. Netbooks’ end goal were to be portable and they failed miserably. Most people work on thinkpads, I don’t know about you, but I actually cannot think of a time where my browser, IDE plus a few cached programs don’t exceed 16GB.

There exist other, larger ThinkPads that accommodate user upgradable RAM slots for those that need it. No product can be all things for all people. For example you can get the P1 with 64GB of memory.

As someone who splits his work between a 64GB workstation and a 16GB ultraportable, there are a ton of use cases where 16GB is a perfectly acceptable amount of memory. That said, 32GB of soldered memory is feasible in a ultra-portable these days so it would be nice for Lenovo to get with the times.

Netbooks' endgoal was to be ubercheap, the portability was an afterthought. Even aside from this ThinkPad model, there are plenty of high-end ultrabooks on the market that are not much less portable than the old netbooks.

True about RAM's failure rates being really, really low. But when it fails in such devices, the very expensive option available to you for repair is replacing the whole motherboard! And no easy upgradability means if Windows or Ubuntu tomorrow increases its minimum requirement for RAM to more than 8 GB, you are stuck with sub-par performing device.

I still have a Thinkpad X220 with such a CPU, all maxed out lying around. FullHD upgrade kit is waiting to be installed :-D

I hardly need more than 8GB for typical developer workloads, and the only thing capable of filling up the 1GB on the GPU are games and 3D visualizations, why bother with more on a laptop?

Only for doing Docker/Kubernetes at the coffee shop, from my point of view.

I work on a desktop application. Developing on a laptop is often a requirement especially when dealing with touchpad/touchscreen input and animations. Realistically one cannot do that over a remote desktop. It just adds too much latency. Plus most remote display clients suck at forwarding complex touch gestures. And when the sources include a copy of Chromium, one better get 32GB. For example memory usage during linking may hit at least 12GB.

Similarly developing mobile apps is more convenient on a laptop as one can interact with an emulator with proper touch input. But then ide and emulators take memory.

On the other hand developing a web-related code on a laptop locally can be even harmful, as opposite to using ssh or remote extension in vscode. Things are too fast locally and one may become aware of performance problems only after fixing those requires a big refactoring.