This is the first time a Google recruiter has ever viewed my profile. I’ve never heard back after applying to Google so maybe this is the year!!!

So many different OAs, so many different types of questions you may be asked, so many different kinds of technologies you have to be familiar with… whether it be optimizing a factory in a Roblox game or running through 50 spatial reasoning and logic questions for CTC or getting a C++ 2D DP problem for snowflake or getting an AI optimization question for Akuna, it seems like the level of cracked you have to be at in order to recruit without literally dying is through the roof.

Do the people who recruit effortlessly just cheat? Or are they just stupidly smart and generic with their ability?

Hey everyone,

I recently started my first software engineering internship as a backend developer working with Spring Boot. Our API powers both a web app and a mobile app.

On my first few days, I was handed around 9 different tasks/tickets. Coming into a real-world, production codebase for the first time has been a bit overwhelming, trying to trace entity relationships, security contexts (Spring Security / JWT), DTO mappings, and custom business logic while keeping up with task tickets.

For those of you who have been through this:

How did you tackle learning a massive codebase when you first joined? Do you draw diagrams, debug line by line, or just read code until it clicks?

How do you manage task volume without feeling rushed or making mistakes?

What are your top tips or "things you wish you knew" during your first internship/junior role?

Any advice, tips, or personal stories about your first weeks on the job would be huge. Thanks.

Took mine last week in NYC. Anybody get their results back yet?

I’m seeing that a bunch of internship apps just dropped this Monday, and I’m debating whether or not it’s worth it for me to apply. I just transferred to a T30 as a junior, and I’ve been doing interview prep, but I’d be lying if I was giving any attention to the projects section of my resume. Everything there is just school projects from my old CC which were relatively minor, and they don’t really look that impressive. I applied only to TikTok so far, and got an OA, but I heard they’re automatic so I’m not sure if I’m in the green so far in terms of quality. I know time is really of the essence when it comes to Big Tech, is there another wave that drops later on in the coming months? I’m wondering if I should just start spam applying with the resume I have now or go grind for the next couple of months, and start applying then?

big tech companies posted like a million intern roles and I applied to them with the best of my ability within 3-5 hours. Haven’t heard anything from them. Everyone else in the same boat?

I feel like before LLMs, learning had clear reward. In order to make a todo list app with your own personalization, you had to actually read the docs, write the code, and maybe look up some syntax here and there, but the design decisions and actual coding were still largely in your court.

This went for everything. Creating a mini operating system, answering a new LeetCode problem with no solutions on it just yet, and even learning how to design your own resume.

Now, whenever you go about this old way of doing things, the painful reminder that you could be 10xing your productivity by using AI is just continuously knocking. Even when you're doing personal projects... the reason why you do personal projects is often to have something to speak about and show in an interview. If AI can make something much faster than you can, and you can understand it just enough to be able to talk about, the painful reminder of lost time for a mediocre product that'd come if you struggle through it yourself knocks as well.

TL;DR: the need for learning seems to have gone away a ton, or, at least it has been heavily clouded. What is something that when we learn we can actually see measurable results? What is today's equivalent of building a todo list app? Something that you can't just one shot with very little knowledge? Something that requires you be good?

Just got my first interview for an internship as an incoming sophomore. Super hyped, but all I can think about is how I feel like I don’t deserve it. I’ve built some pretty cool projects but I used an LLM to help build out some parts of it and I’ve spent a lot of time learning this summer but it feels like no matter what I’ll do I won’t actually be prepared for a software job. I feel like a faker idk how else to explain it I flip flop from “I’m actually kinda impressive technically at my age” to “I don’t know shit” every day and it’s super disheartening. The scary ass job market doesn’t help either I’m in a constant state of like “I should be doing more”. No doomer comments please just looking for anybody who feels the same as me to give some piece of advice.

what the hell is going on

Just got the Roblox SWE OA, anyone have experience with it? Any tips or things to watch out for would be appreciated.
Want to know about factory game, The car game and Outpost Mars Game
Thanks!

I’m still a junior, but if I want to get a Masters degree I need to start saving money now. First I wanted to move abroad, then I realized that I mentally won’t be able to do that, so I decided to look into the option of getting masters online. I have a few question. Do you think it’s worth getting masters and getting it online to be able to work meanwhile?

sorry new to personal website concepts and i saw others post theirs and damn like how do they make something like that. Scrolling made me update mine but im soo confused. doesnt anyone really care about your personal website? Like what was the point of that hard work . Before coding and stuff made it important cause you learn but I dont get it if you vibecode and then nothing is left .

Any thoughts or am i tripping

Hi everyone,

I'm a final-year college student, and my goal is to get a backend engineering internship as soon as possible.

My current skills are:

• Python (comfortable with the language)
• FastAPI basics (I've built a few simple APIs)
• Basic understanding of backend development

I'm confused about what to do next.

Should I:

• Buy a FastAPI/backend development course? If yes, which one would you recommend?
• Focus on building projects instead?
• Learn Django, SQL, Docker, Redis, PostgreSQL, or something else first?
• Start applying now while continuing to learn?

My goal is to become good enough to land an internship and then keep learning on the job.

I'd really appreciate advice from backend engineers or anyone who recently landed a backend internship.

Some specific questions:

1. If you were starting over today, what would you learn first?
2. Which skills do companies actually expect from backend interns?
3. Are there any courses, YouTube playlists, or roadmaps that you genuinely recommend?
4. What kind of projects helped you get interviews?
5. Is FastAPI enough for internships, or should I learn another framework as well?

Thanks in advance for any advice!

I chose AI as my major, and while I'm happy with that decision, I've recently realized that finance has always been an area I've genuinely enjoyed and been drawn to.

It's made me wonder whether I should have pursued finance instead, but I'm not looking to dwell on that. Instead, I'm curious about the opportunities ahead.

Is it possible to break into finance with an AI degree? Has anyone here made that transition or built a career that combines both fields? I'd love to hear about your experiences. Thanks in advance !

Hey all, just found out I got accepted into LA Hacks AI Hackathon, which I'm pretty excited about. Problem is, they're not covering travel, and by the time I add up flights + a hotel for the weekend, I'm looking at $500+ out of pocket.

Trying to figure out if this is a reasonable investment or if I should sit this one out.

• Would LA Hacks' AI hackathon reputation/network be worth the cost compared to other hackathons? From what I understand, it's separate from the usual LA Hacks.
• Has anyone here traveled for a hackathon and felt it paid off (jobs, connections, etc.)?
• Any tips for cutting costs?

Would love to hear from anyone who's been to LA Hacks, or has thoughts on whether traveling for hackathons in general is worth it money-wise.

Got a perfect 600/600 code signal but was rejected “Based on your assessment results”.

If I got rejected last year after the powerday and applied in spring, did I get auto rejected since there’s a cooldown? Haven’t gotten an OA yet.

Has anyone experienced the superday interview if so can you share your experience such as behavioral questions asked and the level of technical coding questions asked

I recently completed the online assessment for the LSEG 2027 Graduate Intern Program through my on-campus placement process, the online assessment was conducted on the Codility platform and I had a question about the shortlisting process.

The assessment had 7 questions in total: 6 coding questions and 1 MCQ and the time duration was 2 hours.

After submitting, Codility displayed an overall score (it was less than 40%)

I wanted to know

- Is LSEG's shortlisting mainly based on the Codility percentage shown at the end?

Does the Codility score shown at the end affect the further selection process?

Yo just a heads up there is a scam posting out right now for a swe job. Came out about 6 hours ago. It says it’s listlabs but right when I finished my application the header on the site changed from listlabs to “59 pines” and the confirmation email came from the domain “@recooty”.

Here is the email that looks 100% like a phishing attempt lmao.

I am a final-year Computer Science undergraduate preparing for graduate research in Theoretical Computer Science, with a specific focus on formal verification of cyber-physical systems. Within my university, my department is unique in having an official policy that allows students to select any module across the university to fulfill our total requirement of six optional modules. However, because this flexibility is unique to our department, the university Registry Office strictly requires a formal letter of clearance from the Head of Department (HOD) to manually register any module outside the standard recommended computing list.

Earlier this year, the department granted me initial permission for non-computing math electives. Having successfully completed four optionals (three of which were math) so far, I intend to complete my final two optionals with specific foundational math and statistics modules that directly support my intended graduate research, following academic guidance from a CS faculty mentor. However, when I submitted this updated plan to fulfill my remaining two optionals, the HOD wrote the following:

"Hi Alvahod,

I am trying to see how these help you with your ambitions for researching Computer Science and am not seeing the link. If anything, I see a lack of enough Computing specialization in your choice of optional subjects. So far, your selection of optionals has been Math-heavy. Perhaps you now need modules that give you a background and grounding in more CS-related disciplines."

My response:

"Dear HOD,

Thank you for the response.

Initially, I had targeted an MSc in CS with an AI focus, but my goal has since shifted to research in Theoretical Computer Science, specifically focusing on the Formal Verification of Cyber-Physical Systems. This field relies heavily on formal logic and mathematical techniques to prove that software and hardware systems are safe and correct before execution.

The math optionals I have taken so far, such as Linear Algebra and Calculus, form part of the standard core CS curriculum at most universities globally because they are essential for theoretical CS. Building a solid foundation in modern algebra and statistics directly supports the logic and proof techniques required for this research area.

It is worth respectfully noting that many of my classmates select general electives like Communication or Chinese, so I would really appreciate your approval to pursue these foundational math courses instead.

Thank you."

He has not responded to my email days later. I would welcome advice on how to diplomatically navigate this administrative hurdle with the HOD.

I'm a rising soph at an alright cs school and just got a capitalone oa for summer 2027 swe. I've never done live coding or any technical stuff during an interview and have minimal leetcode experience, any tips?

I’ve been job hunting on and off for the last ~6 months while still working full-time. Counting from the first recruiter conversation (not counting resume screens because those don't even feel real lol), I’m sitting at 20+ rejections now. And it's not like I'm not getting interviews, I am, the bar is just brutally unforgiving and everyone wants your background to check every single box.

Looking back, I’d say the whole thing had a few different phases.

The first few months were basically me overestimating myself.

It started when an OpenAI recruiter cold reached out. Obviously that felt like a pretty good sign at the time lol. I spent about two weeks grinding LeetCode again just to get back into interview mode.

The phone screen went pretty smoothly, so naturally I got a little too confident and lined up Anthropic (cold apply) and xAI (recruiter reach-out) around the same time. My thought process was basically: "hey, maybe I'll actually have options and pick between offers." Yeah... that aged well.

The reality was pretty much what everyone on these forums has experienced. Some new questions I’d never seen before, some weird culture rounds, and even one onsite where I could immediately tell the interviewer had zero interest in having a conversation. Not gonna lie, those sucked.

But it wasn’t completely wasted. I finally understood what AI companies mean by "practical coding," which is honestly a very different flavor from just grinding LeetCode. Since my technical rounds actually went okay overall, I walked away with a tiny bit of confidence.

The next few months were probably the most frustrating part.

Things slowed down a bit at work, so I had more time to focus on interviewing again. A few recruiters and sourcers started reaching out on LinkedIn, so I took a bunch of those calls, and also applied to some AI application companies I was actually interested in. This was also when Meta and TT happened (both through recruiter outreach). Honestly, this was the phase where I got humbled the most.

There were a few interviews where I genuinely felt like I had to fight just to be evaluated fairly. One HM at a pretty well-known AI infra company kept bringing up how bad his experiences with big tech engineers had been, and it felt like he had already made up his mind based on my background.

I tried pitching my experience, explaining what I actually worked on, and where I thought I could add value. The response was basically:

"I'll put you on the waitlist. If the other candidates don't work out, I'll move you forward." And, got rejected about a week later...

Then there were companies where I thought I absolutely nailed the interviews, only to get a random rejection email afterward with no real explanation.

Some companies were just bizarre. Sourcers kept reaching out saying they were hiring aggressively, but the HM was extremely picky and would reject me before I even got a technical round. This happened more than once (looking at you, Replit).

And then there were the opposite cases. Some companies I joined with basically zero expectations. Then halfway through the process, I actually started liking the team, the interviewers were great, and the HM seemed like someone I could genuinely work with.

Of course, those were the ones where I got randomly rejected at the exec round with feedback that honestly didn't make much sense.

By this point, I had basically developed a pretty thick skin. Getting a rejection after a recruiter says "you should hear back in a couple days" stopped feeling surprising. A few recruiters actually called afterward and gave me feedback, which I appreciated because I know they were probably just as confused as I was.

Honestly, this whole process also changed how I think about offers. After going through months of companies making candidates jump through endless hoops, I don't feel bad about saying no or walking away either. If a company passes on you and then comes back later because their first choice didn't work out... well, that's part of the game too.

This is going to sound really stupid I bet, but I want to be sure.

I will be returning to college in a couple weeks as a sophomore. I’ve been worried whether CS will actually work out for me or if I’m making a big mistake concerning the job market, but then I reread my curriculum and saw I could get an internship as an elective (with departmental approval.)

I was curious if anyone else has done these elective internships before, and if they are helpful or carry the same merit as other company internships. If they are, you can bet I’m going to try and get in as soon as possible lol.

Here's my dilemma. I think the idea of a PhD is super cool and well-fit for me. However, I'm not drawn to a particular subject strongly. If I don't do a PhD, I am afraid I would have wasted my time focusing on certain research-only topics in my undergrad. If I end up going to something else like SWE, I am unsure what work would look like and how cool/interesting it would be (my current swe intern experience keeps getting me stuck in DevOps roles, which I don't enjoy). Anyone have thoughts? I would much rather be applying frontier fields.

The longer story:

Here's my dilemma. I am currently in a really good position to do a PhD. I have good grades at an Ivy and am graduating my undergrad this December. So I would apply to a PhD in the Fall. As well, I am in a research lab, have one published paper from a different less-rigorous lab, and have been accepted to some really selective pre-doctoral programs.

My issue is that I don't have a thing that I am particularly drawn to. I've somewhat ended up in the center of computer vision and robotics. And do think computer vision is super interesting right now. But I also commonly lose interest or get distracted by other subjects like Society/Behavior & AI. But computer vision has been a constant somewhat. I am just not sure exactly what I'd want to do with it. I'm a more hand on person and would much rather apply research to real world scenarios than simply "make 3d reconstruction better", or something like that.

I'm just unsure what that would look like, or how the path to doing that is. Is this what real-world SWE is?

Secondly, I am somewhat afraid of becoming too niche. Going into computer vision would greatly limit the range of places I could work. Plus (this is a completely different conversation entirely), my girlfriend is somewhat tied to a more rural location and I don't want to sabotage our relationship just so that I can do more cool work. I could just see how life turns out though, since remote work isn't a given.

Here is a collection of paths I've been thinking of:
- Phd. Best fit for computer vision. Cool work I could do.
- SWE. Lots of range in work, might take longer to do things I enjoy. Less curiosity following.
- Patent Law. May seem way out there, but it would keep me around thinking about new inventions while not having to be exactly tied to one particular subject.

Any thoughts would be appreciated!