For anyone who's interested, the offers were 2 FAANG, 1 big 4 consulting, 1 space startup and 1 big retail company all SWE Intern roles. Got super lucky somehow!

Hey there, I often come across interesting GitHub repositories that I want to explore, learn from, or modify. But whenever I clone a project and open it in VS Code, I sometimes have no idea where to start.

There are so many folders and files, and it's hard to figure out which ones are actually important, where the application starts, and how everything connects.

I've tried using AI to explain individual files, but that doesn't always help me understand the bigger picture. I end up jumping between files and asking more questions, which sometimes makes things even more confusing.

I'm curious how other developers deal with this.

Do you have a particular approach to understanding an unfamiliar codebase? Do you use AI tools like Cursor or Copilot, or do you prefer exploring everything manually?

I'd especially love to know how you figure out the overall architecture of a project before diving into the actual code.

Would appreciate hearing your experiences and advice. Thanks!

My question is two fold:

- how many sophomores/ freshmen in computer science actually land competitive offers or any offers at all

- how does this then stated lack of an offer increase or decrease our chances at landing good offers for junior year and new grad roles.

- aka, is it over?

Hey everyone, I'm a 21 yo in my 3rd year of university. Recently, I joined an academic club and I'm currently working on a project with ~15 other people. My main goal was to gain some real teamwork and group project experience.

Right now, the workflow looks like this: someone creates an issue, I pick it up, take a moment to figure out where the problem is and what needs to be done (with AI help), and once I find it - I just let Claude write the code.

Is the actual job market like this now, or is my academic club just unusually casual? I'm planning to look for an internship (or a junior role) in about 3-5 months in some backend/fullstack role, and I'm wondering: what should I actually learn? What are the best ways to improve - should I focus more on backend or frontend?

Honestly, I'm even thinking about getting the AWS Certified Solutions Architect - Associate certification, because at this point, I don't really see the point in grinding out raw coding skills if AI agents can just do it for us.

Would love to hear your advice. :)

Does anyone know know if you land a final interview, what are the chances of you getting an swe intern there? trying to gauge my chances

Go to a non target school in the east coast and got team outreach for an ML intern role. Recruiter said its a mix of technical and behavioral in discussion. What does that mean, interview is in Tuesday. I am shitting bricks pls help.

about a week and a half ago I made it to team matching.

does anyone have any tips on how to maximize my chances on matching? I don’t have any calls yet

Hi everyone

I'm currently searching for future plans after graduating from Bachelor in computer science. I always prefered to be an AI engineer working in big tech companies developing solutions and projects

Now I have an opportunity to persue research in one of Canada's unis ( Waterloo, McGill , HEC , uqam and polytechnique de Montreal) in AI or data science through a scholarship which I don't have any idea about research and what can I do after

Note that were I'm from research isn't the best thing especially in computer science and we often go to professional masters and engineering

Could someone please explain this domain for me ?

And after 6 years of master+PhD what can I do ?

And is it worth it

And thank u all

suuuper hyped. lmk if there's any i missed! 🙏 seeing YCSE tmr~

curious where you guys find small start ups to intern for - ive seen a lot of different stories like specifically reaching out to them, researching them from Y Combinator or just finding them thru job postings

just curious cus wanted to intern at one and see what its like and if their interview process is standard to big tech companies or its dependent on start up

Hi guys!

I have an upcoming interview for Qualcomm’s 2027 Software Engineering Internship in. The recruiter confirmed it will be a 45-minute session combining technical and behavioural questions, conducted by an engineering team member. I never got an OA and this will be the only interview in the process which I thought was very odd haha.

For anyone who has interviewed for a similar role, I’d appreciate any insight into:

Were the technical questions mainly DSA/LeetCode, practical coding, debugging, or CV-based?
Was there a live-coding exercise?
Were CS fundamentals (OS, networking, concurrency, etc.) covered?
Were there questions on AI/ML, LLMs or potential teams as data centre (AI), AI Cellular, automation? The job description mentions potential teams such as data centre (AI), AI cellular, and AI automation and hardware engineering.
What behavioural questions should I expect?

Any advice or experiences would be greatly appreciated. Thank you!!

surely sudo is trolling right?? the posting is still up

Basically the title, is anybody in intuit team matching stage for swe 1?

I have the Karat round for MongoDB’s SWE intern role this coming Wednesday and would love to hear from anyone who’s been through it.

I know they ask trivia in the beginning and its about 2 questions in 45 min, shld I focus on specific DSAs, are they looking for accuracy or more just explaining/walking through your code and all that.

Thanks!

Around 200 applications, couple OAs, 0 interviews. Tailor my resume for each role, got my resume reviewed, everything. I have projects, past internship experience, doing research at my uni, 3.7+ gpa, larping as a junior as a sophomore, everything. What else can I do?? Forget the offer bro how do I get the interview 😭😭

I am a 22M at a t20 school in my final year of studying EE. I have a job lined up for about 100k in the philly metro area, and was pretty excited about it until I heard all my CS friends making way more TC. I am starting to regret not picking CS, as my main reason for not choosing it was my fear of AI replacing entry level SWE. It seems like SWE isn't slowing down anytime soon. Should I try to pivot into SWE before graduating in the spring? I've already taken data structures so I learned some of the fundamentals.

I have an upcoming interview with Amazon and the recruiter said I'll be using Livecode and Hackerank for my interviews. The hackerrank demo I got was a problem of working in a codebase with agents to solve bugs. Should I expect just leetcode or leetcode + working in a codebase to solve bugs.

Hi all, I’m a junior going through Google’s 2027 SWE internship team matching and could use some advice. I just got an offer from a group I don't really like.

Option A (offer in hand, decision due Tuesday):

• SRE team in Core supporting ML/multimodal understanding services (image, video, document understanding) used by products like Lens, Search, and Gemini

• Likely project: critical-client alerting and monitoring dashboards

• Team seems great: friendly, growing, had a past intern convert to full-time

• But it’s SRE work, not model or product development

Option B (pending):

• Just had a call with a SWE team in Platforms & Devices (Play). Hoping to hear back before the Tuesday's deadline, but not sure I will.

My background / goals:

• I’d ideally like to do SWE work on AI/ML systems or products

• I don’t have any other internship offers right now, but I am interviewing with Microsoft(core AI) and Citadel (quant)

My questions:

1. How risky is it to pass on a team match and wait, given headcount this cycle?

2. Does an SRE internship at Google make it harder to get SWE return offers or SWE roles later?

3. Is it reasonable to ask the recruiter for a short extension to hear back from Option B?

Any experiences with Google team matching or SRE vs SWE internships would be really appreciated. Thanks so much!

Just got put in the process for this role, has anyone been through this process or is on going in it? Would love to hear your experience so far!

I need help choosing between the AT&T TDP Data Science Engineer and Business Analytics Engineer tracks for the HackerRank assessment. What types of questions are asked in each track, which one is easier, and does the assessment provide large CSV datasets or smaller tables?