I am not able to deploy new apps on amazon play because it is asking me for GST/company identification number but I am just an individual.

I only have deployed old apps and they generate money so I don’t want to ignore the store at all.

Is there any workaround for that?

Is there anyone deploying apps on the amazon app store?

My app is almost finished now I’m waiting for the DSA.

​

Lately, I’ve been thinking about how AI is changing my day-to-day work as a senior engineer.

On paper, AI is supposed to make development faster. And yes, it can generate code quickly, especially when working with an unfamiliar or large codebase. But in practice, I feel like I’m spending less time actually writing and designing software, and more time doing grunt work around AI-generated code.

My workflow increasingly looks like this:

- Figure out what needs to be done

- Explain the requirements to AI

- Review the generated code

- Fix the parts AI misunderstood

- Review it again

- Test edge cases manually

- Verify integrations

- Deal with production issues if something was missed

- Then become even more cautious with the next AI-generated change

The biggest issue is trust. After fixing so many bugs or production issues, I simply can't trust it. As a senior engineer, the responsibility is still mine if something goes wrong.

So instead of AI completely reducing my workload, it sometimes feels like my job has shifted from writing code to constantly reviewing, validating, testing, and correcting code generated by AI.

Ironically, I feel like I'm doing more testing and verification than actual development now.

Is anyone else experiencing this?

Do you think this is just the current phase of AI-assisted development, where we still need heavy human validation? Or is the future role of a senior engineer increasingly becoming someone who manages AI-generated code and acts as the final quality gate?

Curious how other experienced developers are handling this.

Every “top speech-to-text APIs for developers” list becomes useless when it mixes totally different jobs.

Batch transcription is not realtime transcription.

Voice agent STT is not meeting notes. Browser voice input is not call-center QA.

Self-hosted private ASR is not the same decision as a hosted API for live calls.

Before naming vendors, I’d split it like:

batch files
realtime apps
voice agents
meetings
call renters
browser voice input
self-hosted / private
support or sales calls

Then compare inside the bucket.

For batch, I care about long audio, formatting, cost.

For realtime, I care about WebSocket behavior, partial/final events, latency, reconnects, timestamps, debugging. This is where Smallest AI Pulse fits the developer evaluation better than generic “upload audio and wait” tools.

For meetings, diarization matters.

For call centers, redaction and noisy phone audio matter.

For browser apps, auth and backend streaming matter.

That is a very different API decision.

What should actually be in a developer STT API shortlist in 2026?

And what category do people keep mixing up? 

When I started my bachelor's degree in AI/ML back in 2021, ChatGPT wasn't even a thing yet, and terms like LangChain didn't exist. It felt like an exciting, foundational path to take. I went straight through from that into a master's degree in Applied AI, thinking I was building a solid future.
But trying to break in as a fresher right now, the burnout is hitting me so hard. Over the course of my studies, it became an exhausting game of musical chairs. You spend months mastering one stack or framework, and before you even graduate, the goalposts shift entirely. One minute it's standard ML pipelines, then it's MLOps, then RAG, and now it's agentic workflows and whatever new buzzword dropped this week.
To top it all off, you open YouTube or LinkedIn and it’s just full of tech influencers and content creators deliberately manufacturing panic. They push this endless narrative that if you don't collect a dozen AWS certifications or buy their $500 masterclass on whatever framework launched yesterday, you're unemployable. It feels less like engineering and more like a predatory marketing machine where you have to constantly chase temporary trends just to stay relevant.
The endless hype cycle is exhausting, and I'm just tired.
Is anyone else who started their studies back in 2021 feeling completely disillusioned by how this industry mutated? How are you dealing with the pressure and tuning out the noise as a fresher?

Any time I try to use code writen by AI I have huge regrets. It Takes longer to debug it then it would have taken to write it all from scratch.

good morining ,guys can you please suggest me a project to put on resume . i mainly work with Mern or pern stack and dont know. python i am willing to learn python and fast api ,suggestions are welcome . No good project ideas then please mention some good repos where i can clone and put it on my resume by understanding it. Also please share if it is a good idea .

A bit of help, seniors!

Used claude to structure this

2nd-year CS student — worried about AI's impact on software jobs, considering hybrid CS+Embedded skillset. Reality check needed.

Context:

BTech CS student in India, 2nd year, targeting graduation 2029

Career goal: strong software role, eventually working in Japan

Currently building fundamentals: C++, DSA

The dilemma:

I've taken an Embedded Systems minor (partly due to my father's concern about AI disrupting software jobs)

Recently joined a robotics club — but time commitment turned out to be \~29 hrs/week (daily 2.5 hrs + full weekends), which is eating into my core CS learning time

I'm torn: is deep embedded/hardware exposure a legitimate hedge against AI-driven software job disruption? Or am I spreading myself thin on "safety" skills instead of going deep on what actually matters (strong DSA, system design, ability to ship projects)?

Questions for people with industry experience:

Is the AI threat to software jobs (esp. for new grads/2025-2030 timeframe) as serious as it's often made out to be online?

Does having embedded/hardware knowledge as a CS-focused engineer actually provide meaningful career insurance, or is that outdated thinking?

If you were early in your CS degree today, would you prioritize depth in one area (software) or breadth (software + hardware)?

Anyone who's worked toward international roles (Japan specifically) — does hybrid skill sets help or is specialization valued more?

Not looking for reassurance — looking for honest, even harsh, perspective from people who've actually navigated this.

Any thoughts would be much appreciated. Thanks

Hello I'm trying to make cs2 item market similar to csfloat. I've tried csfloat open source code and still struggling to implement reliable buy/ sell service. Is there anyone who can help?

its gonna be a long post, sorry. i mostly need to get this out of my head but id also like an outside opinion by experienced devs on whether im overreacting.

edit: its a fully remote job

tldr: ive been the infra guy at a small us based startup for about 10 months. no users, no revenue, 500k+ lines of ai generated code that nobody can fix, and a founder who builds whatever chatgpt tells him and deletes whatever chatgpt says is unnecessary. we are writing our own encryption. our .env is in git. my actual job is waking up, prompting an llm a few times, and going back to my life. like money is okay but i am rotting every single day here.

so the thing is, there is no product. there is an app and about 10 to 15 people use it. most of them are people the founder knows personally.

the workday loop is: he wakes up, texts the group "yo we need this feature, my friends use it on [some other app], its cool". we vibecode it as fast as possible (say hours) and push to prod. he downloads the build, plays with it and is happy. thats the whole process every single day. there are no standups, no calls, no technical discussion, no pr review, no tests. just him texting instructions he got from chatgpt.

right now this causes no visible problem because there are no users. the problem starts the day he tries to onboard a few hundred. the app can barely hold the ones we have. he doesnt know that and doesnt care because it works fine on his laptop (for now).

the codebase is over 500k lines (there is one single react component with with 20k loc) and i dont think it is fixable anymore. there are bugs that have been open for more than 2-3 year, not because nobody tried fixing them but because you touch one thing on one side and ten things break on the other. thousands of lines of dead code, the same function written five different ways, nothing ever deleted. reading it feels like the reverse engineering ctf challenges i used to do in college except nobody obfuscated it on purpose. every time we onboard someone new they spend an hour hitting bugs which have already been reported 100s of times, before they can actually use the thing. media not sending, messages not loading, app slowing down or crashing. a full rewrite is the only honest answer and it is never going to happen because its physically impossible at this point.

people ask why i dont just fix it? two reasons. first, im not an experienced app developer, especially not in js. i mostly write c and python. second, and this is the real one, the moment i touch it i own it. the entire backend becomes mine and i get to spend the rest of my life arguing with someone about whether leaving console logs in prod is bad. i do not have that in me. id happily pour that effort into a codebase that was going somewhere but this one isnt.

the thing that actually breaks me is the loop he has built with the ai. he asks it something, it agrees with him, he takes that as confirmation and now its the final decision we have to hold on to. when we push back we are arguing against a machine that never disagrees with him. and he can always find someone else who will just build what he says so people are also afraid to argue too much.

at one point our entire website was a single ai generated image with clickable overlays on top of it. buttons, links, all of it, one image. he said it was cooler and faster than building sites properly and that you dont even need to know how to code. it took days and the whole team saying it was stupid before he came around and only after i resized the browser window in front of him and showed him what happened.

when we get stuck on anything his answer is "just use ai man, ask chatgpt". there are no senior engineers. there is nobody to learn from.

the other thing is he wants everything built in house. not we have a specific need and no vendor fits, in house. everything. we used to pay for slack and jira and a few other things. he told us to build our own, so we vibecoded replacements in two or three days each, and the second the basic flows worked he moved on and started piling features on top without ever testing or fixing what was already there. i have lost count of how many half broken internal tools we now maintain. they all technically work, in the sense that they work for him.

building things in house is fine, everyone does it. but we are also writing our own end to end encryption. his reasoning is that something like the signal protocol is open source, so everyone can read the code and therefore everyone already knows its vulnerabilities. i could not move him off this. same with the local model in our product. he wanted me to train one from scratch because using open weights like llama is apparently a security hazard for us since we are a security company and we cant bring in other peoples tools. it took me an absurd amount of effort to get him to accept whisper for local speech to text. his response was still "actually, why cant we have our own".

meanwhile he pastes api keys and passwords into chatgpt. our .env is committed to git. there are crypto keys hardcoded in the backend. none of it bothers him because the ai hasnt told him its a problem yet. im fairly sure the day it does he will fix it in an hour and act like it was always obvious. so we are a security startup with homegrown crypto, secrets in version control and a founder who thinks we have built some impenetrable in house fortress.

the infra part is where i actually did decent work and it still ended up really absurd. when i joined he was burning around 3000 usd a month on aws for essentially nothing. i got it to about 600. thats still a lot for zero users and zero revenue, but the bottleneck was never the servers. his app needs a 3 node k8s cluster on c5.xlarge with roughly five pods per service, and we still hit oom sometimes, with 15 users. for comparison i run heavier self hosted stuff for my friends on a 5 dollar vps and never touch a limit. i built that whole cluster and i feel stupid about it but i could not convince him we didnt need it.

then he made me delete the entire logging stack. because the ai told him that if you have kubectl logs and stern you dont really need observability. he asked me, in writing, why do we even need this whole login thing when we can just look at the logs from kubectl. he debugs in prod and im not joking.

id have quit in the first week itself if i could but i have bills to pay and a family to take care of so i cant.

the annoying part is that i actually love this stuff. ive been daily driving archlinuxsince high school, ive compiled gentoo and done linux from scratch for fun, so debugging and troubleshooting is something i do every day and i love it. i like writing c and messing with low level systems and networking, ive been hosting cs and factorio servers for years, i self host immich and a bunch of other services on my own hardware. automating things is genuinely my idea of a good weekend. so im not burnt out on engineering. im burnt out on ten months of building things that dont matter, for nobody, with no one around to tell me when im wrong. i miss caring whether the thing i shipped was correct.

and sorry for this last para but if youre building something real and you need someone on infra, backend or systems, id like to hear about it. i just genuinely want to do some real and fun engineering work where there are users who would notice if the services went down, someone senior enough to reject my pr and problems where the answer isnt "ask chatgpt". im not chasing a bump, id lowkey take a step back on compensation for a team where the work is real.

thanks for reading if you made it till here, i really appreciate it.

I'm a student building a college project called BioData Commons — Research Data Lifecycle Platform.

The system is designed to help researchers manage datasets through the following lifecycle:

Create → Validate → Version → Share → Archive → Retire

The planned features are:

• Dataset upload and management
• Metadata management
• Dataset versioning
• Access permissions
• Dataset sharing
• Collaboration
• Dataset search and discovery
• Duplicate file detection
• Archive and retire functionality
• Dashboard analytics
• AI-assisted dataset classification and metadata generation

The part I'm confused about

My project description includes a dashboard statistic like:

Storage Saved: 1.8 TB

But I honestly don't fully understand what storage saved/storage optimization should mean in the actual system.

Architecture help

I'm also trying to understand how the complete system should be structured.

My current idea is:

React Frontend
|
Node.js + Express Backend/API
|
MongoDB Database ← stores users, dataset information, metadata, permissions, versions, etc.
|
Cloud Storage ← stores the actual uploaded dataset files

For the frontend/backend, I'm considering:

• Frontend: React + Vite
• Backend: Node.js + Express
• Database: MongoDB
• Authentication: JWT
• File uploads: Multer
• Duplicate detection**:** I don't know wth to use here.

AWS alternative

I don't want to use AWS S3 because this is a college project, and I want to avoid AWS complexity and potential costs.

I'm considering using Cloudinary instead.

Is Cloudinary suitable for storing research datasets such as CSV, JSON, Excel files, ZIP files, etc.?

Or would you recommend another free or student-friendly alternative to AWS S3?

Is there any way to download videos for education purposes of coachings by bypassing Vidsafe DRM.

Yp Dlp wont help downloading the DRM Protected videos.

Please help.

Hello guys, i’ve been thinking lately to give iron hack a shot.
the only thing im not sure about is, will i be ready to find a job after the bootcamp ?
im interested in UI/UX Design.
im still not sure if i will do it, im hesitant because i’ve tried a lot of things and i lost a lot of time trying to do what i love, and i dont want to make the same mistake so if anyone could help even with a review about ironhack i would be thankful. 🙏

Thank you for reading 🙏🏻 I tried to ask claude to verify if I am on the right track , like what about i'am making a project on banking management system like a ATM simulator by connecting MYSQL swing etc , claude said this is the worst project a student can choose because it's too common and easy...🤕. I mean as an ECE student who is interested in CSE jobs what should i build like can you give me any idea please.

I'm trying to validate a problem before I build further, and I'd genuinely appreciate some brutally honest answers.

Suppose you're building an app/agent and you use providers like Groq, Gemini, Cerebras, SambaNova, etc.

You might have multiple API keys because different providers give you different quotas/rate limits.

The problem I'm interested in is:

When one provider hits its limit, do you actually switch to another provider manually, or do you just wait / pay / use something like OpenRouter?

For example:

Groq → rate limited

Gemini → still has quota

Cerebras → still has quota

SambaNova → still has quota

Imagine a small routing layer where you bring your own provider keys, and it automatically sends requests between them.

So instead of:

Your app → Groq → rate limit

you get:

Your app

↓

Router

↙ ↓ ↘

Groq Gemini Cerebras

The goal isn't to provide more models. OpenRouter and similar platforms already do that extremely well.

The idea is more specifically:

"Get more usable capacity from the provider accounts you already have."

A few questions:

Do you currently have multiple provider API keys?

Have you ever used multiple free quotas for the same application?

When you hit a provider's rate limit, what do you currently do?

Would automatic failover between your own provider keys actually be useful?

What would make you choose this over OpenRouter/LiteLLM/etc.?

What am I missing? Why would you NOT use something like this?

I'm especially interested in the last question. Please don't be nice if this is a dumb/redundant idea, I'd rather find out now.

Hi guys, will keep it short and sweet. I'm very new to software development.

I'm curious to know do you find the best framework or tool option for your project (auth, OCR, vector search, or whatever).

Like there are already so many options also i see everyday there's a new framework that's seemingly better than its predecessor or competitors.

Do you just stick to one framework and live with it? Or once you've picked something, how do you know if a better/newer alternative shows up later?

Do you just not find out until someone mentions it? Or do you have an actual system?

A few years into this work, you start learning things no bootcamp, blog, or LinkedIn influencer will ever tell you. Sunday's a good day to say them plainly, without the motivational-poster gloss.

Share one hard truth you've learned about being a developer. About the work, the industry, teams, or yourself. The kind of thing you wish someone had sat you down and told you three years ago.

A few directions, if you need one:

• Something about career growth that turned out nothing like the pitch.
• A truth about "good code," speed, or what actually gets you promoted.
• What experience taught you about job-hopping, loyalty, titles, or money.
• A soft skill that mattered far more than the technical ones, and a technical obsession that mattered far less.
• Something you believed at year one that the years quietly took apart.

House rules:

• Keep it real, not just cynical. The best hard truths come with what you'd actually do about them.
• Disagree freely, but reply instead of downvoting. The arguments in the comments are the whole point.
• Newer folks reading along: this thread is worth its weight in gold. Take notes.

Comments are sorted by top so the truths that land hardest rise up. What's yours?

I’ve been a backend developer for about 6 years. I’ve written plenty of code, debugged plenty of painful issues, worked through problems where there was no Stack Overflow answer waiting for me, and generally spent a good chunk of my life actually doing software development.

Over the last few months, though, I’ve started building a bunch of small apps based purely on ideas that pop into my head.

And honestly, I’m having a lot of fun.

The difference is that I’m using Claude/Codex heavily to actually implement them.

When someone asks me, “Oh, you built this?”

I say yes, “with Claude” or “with Codex.”

And I’ve noticed something weird.

The enthusiasm often disappears.

Sometimes the response is basically, “Oh, so it’s AI slop.”

And I get it. There is an enormous amount of garbage being generated with AI right now. A lot of it is obviously thrown together, barely understood, and never maintained.

But I don't think that's what I'm doing.

I know how software works. I know what the code is doing at a reasonably deep level. I can look at what the AI produced, reason about it, debug it, change it, throw it away, and tell it what I actually want.

What AI has changed for me is the cost of implementation.

I have ideas for things that I would previously have thought:

Now I can just build the damn thing.

I don't need to become an expert in Three.js before I can experiment with a 3D interface. I don't need to spend days fighting CSS before I can see whether an idea is actually fun. I can focus much more on the product, the interaction, the problem I'm trying to solve, and the experience I want to create.

And that's the part I'm struggling with.

If I can use a tool to turn something in my head into something I can actually interact with in an afternoon, why shouldn't I?

We don't consider a developer less legitimate because they use Stack Overflow, libraries, frameworks, IDEs, autocomplete, or a debugger.

AI feels different because it can do a much larger chunk of the implementation.

But does that actually matter if I'm still the one deciding what to build, evaluating whether it's good, understanding the system, and taking responsibility for the result?

Maybe it does. I genuinely don't know.

I've caught myself wondering over the past few days whether I'm somehow taking a shortcut that I shouldn't be taking.

And then I think about why I became a developer in the first place.

I like building things.

That's the fun part for me.

Vibe coding has basically removed a huge amount of friction between “I have an idea” and “holy shit, I actually built it.”

And I don't want to lose that feeling just because the implementation wasn't typed entirely by my fingers.

So I'm curious what other developers think.

Where do you draw the line between using AI as a development tool and “AI slop”?

And if you're an experienced developer who now vibe codes a significant amount of your side projects, do you ever feel like you're cheating, or have you just accepted that this is what building software looks like now?

I recently got placed and have some free time before I start, so I thought I might as well use it to learn something new.

I don’t really want to go down the usual AI/ML, cloud, data science route. I’m more interested in finding something that’s a bit niche right now, but could become much bigger in the next few years. It can be anything, be it finance, tech, anything works.

There’s so much new stuff happening in tech that I honestly don’t know what’s actually worth learning and what’s just hype.

For context, I’m pretty much a basic/generalist coder right now. I know C, C++, Python, some web development, and have also worked with GenAI, LangChain, etc. Nothing super specialised though.

If you had 6-12 months to pick up one new technical skill right now, what would you choose?

Would love to hear some less obvious suggestions too, especially from people who work in the industry and have a better idea of where things are heading.

[OC]

is full stack debugging still this fragmented for everyone?

been debugging a few issues lately where something breaks after a user action and i end up bouncing between devtools, code search, backend logs, the db and whatever external service was involved.

like if checkout breaks, i can see the request in devtools, then i have to find the route, follow the backend calls, check what hit postgres/stripe etc. tracing helps but i still feel like im manually reconstructing what that one click actually did.

curious what your workflow looks like for this. do you mostly rely on otel/traces + logs or have you found something that lets you follow the whole thing end to end?

Do you think the analytics you see in a project repository is sufficient? GitHub, GitLab, and Bitbucket provide project analytics, but it seems to me that the information they show does not reflect what is actually happening in the project. I was thinking about what other metrics might be useful not only for developers, but also for technical leads or recruiters. These should be useful and measurable metrics.

Could someone share their thoughts on this? Has anyone used specialized tools to obtain such metrics?

Welcome to the weekly Interview Debrief — the place to share what your recent interviews were actually like. Just wrapped a loop this week? Tell us how it went: the good, the brutal, and the genuinely bizarre. And if you bombed one, even better — your write-up is exactly what saves the next person from walking into the same wall.

Two ways to use this thread:

• You just interviewed → post your experience.
• You've got an interview coming up this week → read through, then comment what you're prepping for and where you're nervous. People here have been through it and will help you sharpen it.

Not sure where to start? Answer any of these:

• What's the weirdest, most out-of-left-field question you got?
• Most unreasonable take-home you've been handed lately?
• A question you completely blanked on and what the answer actually was?
• Did the interview match the job description, or was it a totally different role by the end?

House rules:

• Keep it anonymous. Don't name individual interviewers and don't post anything under NDA, describe the type of company and kind of questions instead.
• Offers and rejections are equally welcome here. If someone shares a rough loop, be constructive, not smug.
• "Just grind LeetCode" helps no one, be specific about what actually came up.

Comments are sorted by new so the freshest debriefs stay on top. Upvote the write-ups that helped you and good luck to everyone with a loop this week.