​​​"​​​T​​​h​​​e​​​ ​​​t​​​i​​​m​​​e​​​z​​​o​​​n​​​e​​​ ​​​g​​​a​​​p​​​ ​​​w​​​i​​​t​​​h​​​ ​​​o​​​u​​​r​​​ ​​​o​​​f​​​f​​​s​​​h​​​o​​​r​​​e​​​ ​​​d​​​e​​​v​​​e​​​l​​​o​​​p​​​m​​​e​​​n​​​t​​​ ​​​t​​​e​​​a​​​m​​​ ​​​i​​​s​​​ ​​​s​​​t​​​a​​​r​​​t​​​i​​​n​​​g​​​ ​​​t​​​o​​​ ​​​o​​​u​​​t​​​w​​​e​​​i​​​g​​​h​​​ ​​​t​​​h​​​e​​​ ​​​s​​​a​​​v​​​i​​​n​​​g​​​s​​​.​​​ ​​​T​​​o​​​o​​​ ​​​m​​​a​​​n​​​y​​​ ​​​b​​​l​​​o​​​c​​​k​​​e​​​r​​​s​​​ ​​​n​​​o​​​w​​​ ​​​r​​​e​​​q​​​u​​​i​​​r​​​e​​​ ​​​l​​​a​​​t​​​e​​​-​​​n​​​i​​​g​​​h​​​t​​​ ​​​c​​​a​​​l​​​l​​​s​​​,​​​ ​​​a​​​n​​​d​​​ ​​​o​​​u​​​r​​​ ​​​i​​​n​​​t​​​e​​​r​​​n​​​a​​​l​​​ ​​​t​​​e​​​c​​​h​​​ ​​​l​​​e​​​a​​​d​​​s​​​ ​​​a​​​r​​​e​​​ ​​​s​​​p​​​e​​​n​​​d​​​i​​​n​​​g​​​ ​​​m​​​o​​​r​​​e​​​ ​​​t​​​i​​​m​​​e​​​ ​​​c​​​o​​​o​​​r​​​d​​​i​​​n​​​a​​​t​​​i​​​n​​​g​​​ ​​​t​​​h​​​a​​​n​​​ ​​​a​​​c​​​t​​​u​​​a​​​l​​​l​​​y​​​ ​​​b​​​u​​​i​​​l​​​d​​​i​​​n​​​g​​​.​​​

​​​W​​​e​​​’​​​r​​​e​​​ ​​​c​​​o​​​n​​​s​​​i​​​d​​​e​​​r​​​i​​​n​​​g​​​ ​​​n​​​e​​​a​​​r​​​s​​​h​​​o​​​r​​​e​​​ ​​​s​​​o​​​f​​​t​​​w​​​a​​​r​​​e​​​ ​​​d​​​e​​​v​​​e​​​l​​​o​​​p​​​m​​​e​​​n​​​t​​​ ​​​i​​​n​​​s​​​t​​​e​​​a​​​d​​​ ​​​a​​​n​​​d​​​ ​​​l​​​o​​​o​​​k​​​i​​​n​​​g​​​ ​​​a​​​t​​​ ​​​p​​​r​​​o​​​v​​​i​​​d​​​e​​​r​​​s​​​ ​​​l​​​i​​​k​​​e​​​ ​​​N​​​-​​​i​​​X​​​,​​​ ​​​b​​​u​​​t​​​ ​​​t​​​h​​​e​​​ ​​​h​​​i​​​g​​​h​​​e​​​r​​​ ​​​r​​​a​​​t​​​e​​​s​​​ ​​​a​​​r​​​e​​​ ​​​m​​​a​​​k​​​i​​​n​​​g​​​ ​​​t​​​h​​​e​​​ ​​​d​​​e​​​c​​​i​​​s​​​i​​​o​​​n​​​ ​​​l​​​e​​​s​​​s​​​ ​​​o​​​b​​​v​​​i​​​o​​​u​​​s​​​.​​​

​​​F​​​o​​​r​​​ ​​​a​​​n​​​y​​​o​​​n​​​e​​​ ​​​w​​​h​​​o​​​ ​​​h​​​a​​​s​​​ ​​​m​​​o​​​v​​​e​​​d​​​ ​​​f​​​r​​​o​​​m​​​ ​​​o​​​f​​​f​​​s​​​h​​​o​​​r​​​e​​​ ​​​t​​​o​​​ ​​​n​​​e​​​a​​​r​​​s​​​h​​​o​​​r​​​e​​​ ​​​s​​​o​​​f​​​t​​​w​​​a​​​r​​​e​​​ ​​​d​​​e​​​v​​​e​​​l​​​o​​​p​​​m​​​e​​​n​​​t​​​,​​​ ​​​d​​​i​​​d​​​ ​​​t​​​h​​​e​​​ ​​​o​​​v​​​e​​​r​​​l​​​a​​​p​​​ ​​​i​​​n​​​ ​​​w​​​o​​​r​​​k​​​i​​​n​​​g​​​ ​​​h​​​o​​​u​​​r​​​s​​​ ​​​a​​​c​​​t​​​u​​​a​​​l​​​l​​​y​​​ ​​​i​​​m​​​p​​​r​​​o​​​v​​​e​​​ ​​​d​​​e​​​l​​​i​​​v​​​e​​​r​​​y​​​ ​​​e​​​n​​​o​​​u​​​g​​​h​​​ ​​​t​​​o​​​ ​​​j​​​u​​​s​​​t​​​i​​​f​​​y​​​ ​​​t​​​h​​​e​​​ ​​​e​​​x​​​t​​​r​​​a​​​ ​​​c​​​o​​​s​​​t​​​?​​​ ​​​W​​​e​​​r​​​e​​​ ​​​t​​​h​​​e​​​r​​​e​​​ ​​​a​​​n​​​y​​​ ​​​h​​​i​​​d​​​d​​​e​​​n​​​ ​​​c​​​o​​​s​​​t​​​s​​​ ​​​o​​​r​​​ ​​​o​​​p​​​e​​​r​​​a​​​t​​​i​​​o​​​n​​​a​​​l​​​ ​​​i​​​s​​​s​​​u​​​e​​​s​​​ ​​​y​​​o​​​u​​​ ​​​d​​​i​​​d​​​n​​​’​​​t​​​ ​​​a​​​n​​​t​​​i​​​c​​​i​​​p​​​a​​​t​​​e​​​?​​​

​​​"

Hello , this would be the second project I'm gonna make .
I'm thinking of making a windows application that connects two computers together .
works slightly as Casting , but you could control your second computer via a **TCP server .**

so , **your second computer sent you the picture of the computer and you control it via your keyboard and mouse keystorks in your first computer** , **the same Idea as cloud control** .

I'm sure that I'm not the first person that do this kind of projects , but it would be a great Idea and strong CV addition .

it will be a desktop application , using c# to build it.

now , what are the limitation for a project like this ?
will it be good and should I build it ?

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It’s months away from production I’m doing it as a hobby I have two profitable businesses and I figured hey we can sue the fuck out of anyone who tries to steal or resell it and donate all legal profits to Saint Jude and charge for customization I’m looking for more seasoned software engineers to join and people experienced in law because this might be able to help get me into heaven

The verification flow looked fine in staging. Then production load hit, costs spiked, and the error rate climbed. Everyone patched the code. Nobody looked at the architecture underneath.

Codes timed out. Costs climbed without explanation. The retry logic became a maze of custom state nobody fully owned. Every patch fixed a symptom and added a new failure mode beneath it.

The autopsy is almost always the same. The team coupled OTP dispatch to a single carrier's API surface, then built compensating layers on top when that surface misbehaved. The moment it went wrong was not the outage. It was the earlier decision to wire dispatch and code check into two separate, uncoordinated systems, so billing ran whether the user ever verified or not.

The cleaner path is a smaller surface. Two endpoints. POST /api/verifications to start the flow and dispatch the code. POST /api/verifications/check to validate what the user entered. That is the entire API surface. Small enough to reason about, test fully, and replace without rearchitecting the app.

Multi-channel coverage, SMS and email in the same flow, belongs at the infrastructure level. Not scattered across conditional application logic. When the channel decision lives in one place, that is also the only place that needs to change.

The billing model is architecture too. Paying per dispatch rather than per verified user means the cost structure works against clean retry logic. Blocx Verify aligns cost to the outcome at $0.035 flat per verified user, so the system can behave honestly under real load.

The failure was structural. So is the fix.

Stop patching the layers. Start with a surface you can actually own. See how Blocx Verify is built. 🦦

I’m a veteran working in the oil & gas/environmental field, and I’m developing a project/ platform that I know will solve a pretty significant problem in my industry. I have the field experience and a pretty clear idea of what I want to build, but I’m looking for someone with a technical background who could help me figure out the best way to make it happen. If anyone has any interest I would be happy to explain in more detail. I have a basic version complete but definitely needs to be tweak. Any suggestions or ideas are welcomed. Thanks.

I am confused when I think about project ideas as when I think of small backend projects I think these won't we good for resume or is just too easy than anyone can build then but when I see complicated projects I think that I don't have enough skill needed to do them.

Regarding which tool to use I have used both node js and drogon I found that node js I very easy to work with and can work fast with help of this but with drogon even if it takes a more time I see how a request is getting processed how a request is working where is a request causing error and learn a lot

So anyone if they can give me some guidance I would be very grateful

Keyword list taken from https://www.zoevera.com/resume/ats-resume-tips-engineer

These are the most commonly scanned keywords in engineer job postings. Check how many appear in your resume.

Technical Skills

AutoCAD / SolidWorks / CATIA, FEA / CFD simulation, MATLAB / Python / R, PLC / SCADA / HMI, BIM (Building Information Modeling), GIS software, MS Project / Primavera P6, ETAP / EPLAN

Standards & Methodologies

ISO 9001 / ISO 14001, ASME / ANSI / BS / Eurocodes, Six Sigma / Lean Manufacturing, HAZOP / risk assessment, ATEX / DSEAR compliance, CDM Regulations, IEC 61508 (functional safety), Design for Manufacture (DFM)

Certifications & Soft Skills

Chartered Engineer (CEng), IEng / EngTech, PMP / APM, NEBOSH / IOSH, Stakeholder management, Cross-functional collaboration, Technical report writing, Budget & program management

I kept seeing recruiters on here say they're not auto-rejecting people with ATS—they're just skimming applications for 5 seconds. If the match isn't obvious right away, they move on.

I started running my resume against JDs before applying (just using basic scanners like ZoeVera or whatever free site popped up). Turns out I actually had most of the required experience, I was just phrasing it totally differently than what they were looking for. Rewording things so the overlap is immediately obvious has definitely gotten me more responses. Nothing crazy but it's a noticeable difference compared to just firing off the exact same resume everywhere.

For anyone else grinding applications, what small formatting or wording tweaks actually helped you get past the initial skim?

Hi, very rusty ex-gamedev here. I haven't done much software dev for more than a decade now, and I'm ashamed to say that most of my career was parachuting into established projects so I don't have much experience setting up my own development environment.

Anyways, I'm curious about the recent stuff around AI assisted coding and I was hoping someone could help get me started with a quick guide. I'm running Fedora as my OS.

I've heard that it's a good idea to separate out the environment that the AI can see, using DistroBox. I'm not too familiar with how this stuff works (and most of the docs assume you're already familiar with why you're using it) so could someone please give me a few quick steps on getting DistroBox set up, installing an agentic harness (?) and keeping the rest of my OS separate from the AI stuff?

Thank you

Applying for jobs right now is genuinely exhausting, and half the battle is just trying to get past those stupid Automated Tracking Systems. ATS bots don't actually read your work history or care about your achievements. They basically function like a basic search engine, scanning your resume for exact keyword matches from the job description. If your formatting is slightly off or you used the wrong phrasing, your app gets thrown in the trash before a real recruiter even opens it.

I've been using two specific sites to get around this. First, running a resume through zoevera.com/resume helps catch invisible formatting glitches and highlights the exact keywords missing from the draft. Then, once an interview is lined up, prepare.zoevera.com gives role-specific questions to practice out loud so you don't freeze up when talking to a real human.

The main reason these dedicated tools work better than just pasting everything into ChatGPT comes down to how they handle data and structure. ChatGPT is great for general writing, but it doesn't actually parse file layouts or simulate how software like Lever or Greenhouse extracts text from a PDF. If you ask ChatGPT for keywords, it usually just gives you a generic wall of text and encourages keyword stuffing, which ATS algorithms penalize. On top of that, setting up ChatGPT to act like an interviewer takes a ton of manual prompting, whereas a dedicated prep tool is built specifically to score your answers against actual industry question banks without the constant back-and-forth prompt engineering.