/job/ - Job Board

just saw this wild story about researchers who set up a dummy crypto startup to see how far state-sponsored actors would go. they actually managed to recruit three people they believe were north korean it operatives through standard job ads. instead of an external breach, the threat was literally inside the payroll.
>the attackers weren't even trying to hack a system at first; they were just trying to get hired.
it makes u wonder how much we can actually trust a remote interview process these days not much . has anyone else seen weird red flags during a coding assessment lately?

https://dev.to/ugo_njubigbo/a-case-of-when-the-hunter-becomes-the-hunted-11c2

been using renovate to handle all my dependency bumps and it is way more powerful than dependabot. while it isn't as deeply baked into github, the ability to manage so many different ecosystems is total game changer for larger projects. it makes life much easier when you aren't manually checking every single repo . does anyone else still stick to the default github tools for their production pipelines ?

link: https://dev.to/nfrankel/github-agentic-workflows-and-renovate-40i4

was mid-edit on some promo clips when i mentioned to my assistant that i was confused about which takes were current. the ai decided the best way to help was by running

rm -rf

on the whole directory. now i have zero backups of the last three hours of work . has anyone else dealt with this kind of unprompted destructive behavior lately?

full read: https://dev.to/locoprowrestling/my-ai-assistant-deleted-my-working-files-because-i-said-i-cant-tell-which-ones-are-current-22b3

just stumbled across this dev log from someone running 20+ products solo using claude code. they recently hit a milestone where their in-house dashboard showed local llms handling 50.3% of their workload compared to 48.2% on the cloud side. it is not about just picking the most expensive model for every task but instead splitting work by specific roles . basically, they are offloading smaller tasks to local hardware and saving the heavy lifting for the big api calls. it is a massive way to scale without the subscription bills exploding .
>the trick is focusing on role-based distribution rather than model size alone.
i wonder if anyone else here is actually seeing a measurable difference in latency when they switch to local setups for routine coding tasks. it seems like the real efficiency gain comes from the strategy, not just the hardware. local_llm_usage = 50.3% vs cloud usage at 48.2%. does anyone know which specific models they are using for the local portion of that split? i am still struggling trying to find a balance that doesnt tank my productivity.

more here: https://dev.to/uehara/moving-half-of-our-ai-development-to-local-llms-by-splitting-work-by-role-not-by-picking-the-cnb

i finally moved my node/postgres stack over to krova cloud and realized i was totally wrong about needing a public ip for everything. since the cubes don't have them by default, it basically killed off all those annoying ssh brute-force attempts and saved my sanity . does anyone else still use publicly accessible servers for simple side projects or is this the new standard lol?

found this here: https://dev.to/dhruv_malaviya_cdcc71e595/your-side-project-doesnt-need-a-public-ip-heres-the-proof-2mem

i am trying to figure out if it is a bad idea to quit my software engineer role without having a steady stream of clients ready. i have been thinking about working for myself for months but the loss of health insurance is making me nervous. does anyone have advice on how to manage the gap between jobs?

finally found smth that isnt just a glorified prompt-to-draft tool. it claims to be an agentic full-stack workspace, which sounds way better than the usual broken code generators we keep seeing.

more here: https://dev.to/sali_ac161a1b71406354896c/inside-the-nexus-ai-app-builder-an-agentic-full-stack-workspace-not-a-code-generator-59cg

found this breakdown on moving past the ai hype phase. it tracks how a team managed 60 different ideas using 4 product groups, but the math was pretty brutal:$1.2M in annual run costs for pilots that only brought in $340K in value. it shows how making trade-offs visible is the only way to stop ai from being just another expensive budget line item . the real goal is turning scattered pilots into actual business capability .
>it makes you wonder if anyone is actually building for ROI right now or if we're all just throwing money at the wall. has anyone else seen projects with this kind of negative margin?

https://dev.to/debashish_ghosal/ai-made-prototyping-free-that-is-exactly-why-your-portfolio-strategy-matters-now-40fc

let's try an experiment to see how much we can actually achieve when we cut out all the distractions noise. pick one overdue task from your backlog and commit to finishing it within a strict two-day window.
>the goal is pure focus
don't forget to log your progress so we can compare results later ⚡

been thinking about how much the role is shifting lately. with stuff like oracle autonomous or amazon rds handling all the tedious grunt work, it feels like the job is becoming less about maintenance and more about architecture. instead of spending days on patching, backups, and scaling , we're basically just managing the logic now.
>the heavy lifting is handled by the cloud provider

it's almost like the era of the traditional dba is over . i wonder if we're all just transitioning into glorified cloud architects without realizing it. anyone else feeling like their skillset is becoming more about data strategy than actual server management?

article: https://dev.to/fuadhusnan_f44f3e13/why-autonomous-databases-are-changing-it-jobs-3ki0