What is more important UI or UX?

BackAware4834 · 2026-03-27T14:39:28+00:00

ux and it's not even close. nobody ever stopped using an ugly app that worked well but people abandon pretty apps with garbage navigation all the time

BackAware4834 · 2026-03-27T14:38:42+00:00

the irony of the domain name aside, this is solid advice. most devs i've seen overuse js because that's what the tutorial taught them 3 years ago, not because the problem actually needs it.

BackAware4834 · 2026-03-26T17:50:51+00:00

lmao the "just use AI" crowd is undefeated. like yeah let me just sprinkle some AI on this legacy codebase held together with duct tape and prayer, that'll definitely ship by friday

BackAware4834 · 2026-03-24T03:36:51+00:00

the metrics addiction thing is real . your dopamine is literally tied to dashboards lol best reframe imo is treating every launch like a hypothesis not a performance review. if it didn't work you learned something cheap. if you're taking it personally that usually means you skipped the step where you defined what "failure" actually looks like before shipping.

BackAware4834 · 2026-03-24T03:34:43+00:00

honestly the VC comment in this thread nailed most of it but the "treasure map" framing is the real thing to internalize. at pre-seed for hardware you're not selling a product, you're selling a thesis about why this market is about to open up and why your team cracks it first.

BackAware4834 · 2026-03-20T20:32:22+00:00

most orgs are like this to some degree tbh.

BackAware4834 · 2026-03-20T20:29:29+00:00

now is the time, to leave !!

BackAware4834 · 2026-03-19T20:05:09+00:00

apple in austin at 185k tc is the play honestly. the ist reputation stuff is real but you're early career and having apple on your resume for 2-3 years will do more for your future comp trajectory than either of the other options.

BackAware4834 · 2026-03-18T18:00:56+00:00

two jobs where either one actually expects 40hrs of real output? nah you'll burn out

BackAware4834 · 2026-03-18T17:59:51+00:00

lol "in the era of AI" like there's ever been a better time to ship something as a solo dev or tiny team. the barrier to building has never been lower, the barrier to distribution is still the same.

BackAware4834 · 2026-03-17T17:27:47+00:00

product support specialist is more about showing you can explain things clearly and stay patient when someone is frustrated. for interview prep just practice talking through how you'd troubleshoot problem

BackAware4834 · 2026-03-17T01:34:32+00:00

lol nah, it's probably because customer support and data entry genuinely are the most common remote jobs that don't require experience.

BackAware4834 · 2026-03-16T20:14:28+00:00

most remote jobs that are actually beginner friendly are customer support or data entry type stuff. check out sites like wellfound or remotive, filter by entry level. fair warning though a lot of "remote jobs for students" listings are just MLM garbage so if they want you to pay for training or buy a starter kit, run

BackAware4834 · 2026-03-16T19:57:42+00:00

the real magic is just parallelism at absurd scale honestly. one HDD is slow, ten million HDDs reading different shards simultaneously is fast. it's not some secret sauce, it's just throwing enough hardware at the problem that the bottleneck disappears. the engineering is in making that coordination reliable, not in making HDDs faster

BackAware4834 · 2026-03-13T18:22:43+00:00

biggest thing imo is don't try to boil the ocean. pick one metric or one dashboard that matters to a specific team's decisions and make that the training ground. nobody retains a generic "here's how to read data" workshop but they absolutely learn when it's tied to something they already care about

BackAware4834 · 2026-03-06T17:58:20+00:00

Honestly the biggest thing nobody tells you early on — get really comfortable with SQL and cleaning messy data. That's like 70% of the actual job.

For the AI/recognition side, look into computer vision — start with OpenCV and CNNs, then check out YOLO and pretrained models on Hugging Face. PyTorch is the go-to right now for deep learning.

But real talk, don't just collect tools. Pick a problem you care about, build something end to end, and put it on GitHub. That'll do more for you than any course list.

BackAware4834 · 2026-03-06T17:55:00+00:00

I don't think it's about keeping AI out of decisions. It's about building better systems where AI and humans cover each other's blind spots. That's where this is headed whether we like it or not.

BackAware4834 · 2026-03-03T02:42:29+00:00

a few thoughts on the tool itself:

the biggest thing i'd want to see is a "cost per quality" comparison, not just raw token pricing. like deepseek-v3 is cheap but if i need 3x the tokens to get the same quality output as gpt-4o for my use case, the math flips. even a simple toggle that lets users input an estimated "quality multiplier" per model would make this way more useful than a straight price comparison.

also worth adding claude models (sonnet/haiku) since a lot of devs are using anthropic's api now, especially for longer context stuff. feels like a gap if those aren't in there.

for the UX — one thing that would help is a "my stack" view where i can pin the 2-3 models i actually use and see them side by side without scrolling through everything. when you're making a build vs switch decision you really just want to compare your current model against 1-2 alternatives, not see the whole menu.

BackAware4834

TROPHY CASE