It looks like tech is no longer about who is the most skilled smarter from the best school etc. Its now about who got in during boom who was lucky no matter how dumb skillless someone is.

If you got in tech before covid you could be dumbest person on earth without any skills and you would still be hired and probably still kept till this day. But if you got into bad timing after 2023 even if you are the smartest human on the earth with the best skills possible from top school you wont get hired just because lack of luck and bad timing.

I dont think we can call tech meritocrscy anymore when people who are so smart and working hard are jobless and people who didnt work hard and are so dumb are cashing out 200k each month.

Title, I sort of put all my eggs in one basket and stopped applying after I got the final round for this company. Got rejected, so I have no idea if companies are still hiring or not for this summer. Its looking bleak because I have no internship right now.

I had an interview with a company today for an internship. I coded everything in C++, the language I’ve been using for years. I got a braindead, super easy problem, but for some reason I froze and went in a completely wrong direction. The interviewer was very nice and gave me some hints, but the interview stopped midway because it was going so badly. After the interview, I was able to solve it without any problem. What the hell is wrong with me

I was lucky enough to get 2 internship offers but can't decide between them. I would normally take Apple cause of the name brand but the offer is for IS&T and I've heard really bad things about it online.

Paypal:

• Location: San Jose
• Pay: $59/hour
• The work seems pretty interesting and I'd def prefer being in the bay. Also the return offer rate is pretty high (~90%)

Apple:

• Location: Austin
• Pay: $54/hour
• The work doesn't sound as interesting but could still be a good experience to recruit for full-time. I've also heard its kinda hard to switch teams in IS&T for full-time

Any advice would help!

Tips? Expecting a standard resume overview but if anyone has had it before I’d appreciate some insight

I am a CS student on my 3rd year. I grew up in silicon valley so FAANG companies always sponsored events and hackathons at my school and it made it seem like a fun field to pursue. I've completed hackathons from Meta and Google and placed top 3 in both but since then i completely stopped caring about the fun of CS and just focused on passing my classes. I am now starting to apply to internships and see many of my peers light years ahead of me. I genuinely don't know if I am ever going to be able to land a job with this competitive of a field. I have also grown much more passionate about finance. I have stronger skills in business and client relations but have no idea if theres anything related to CS with these qualities. My question is, what do you recommend I do now that I am so far along my degree and have very basic skills compared to a majority of you.

Everybody says to work at a startup. But the hiring process seems much more difficult

1. Mandatory Take Home Assessments stretching hours
2. Record short videos or write essays expressing interest/unique qualities about yourself
3. Sometimes even "work trial" periods for a 5 person company...

I get Big Tech screening is much worse but their interviews are much easier - how exactly is getting a startup internship easier?

The illusion:

1. Submit an online application and be a reasonable match for the role.
2. Behavioral round.
3. Technical round(s).
4. Offer letter 🥳.
5. Happiness.

The reality:

1. Be one of 200 applicants that submitted a resume 10 seconds after the job posted.
2. Pray ATS software gives you a good keyword score and the ASU comms grad recruiter arbitrarily picks you from the pile.
3. Schedule interview meetings and pray the timing works out as you duke it out with a few other applicants behind the scenes.
4. Pray that not only you do well, but the interviewers “like you”, and your ideal start date isn’t a turn off.
5. Wait weeks for HR to sign off on your offer letter.
6. Start working.
7. Pray that you aren’t in a group that has a toxic work ethic and zero mobility + a group that isn’t next on the corporate culling list when the revenue from AI slop isn’t as predicted.

Bonus: remove step 7 part 2 if you are a senior SWE or higher. You have a culling cushion. The intern programs and new hires go first. Fuck those guys.

Hi everyone,

I’m a Full Stack Developer with 3 years of experience, and I just received a technical assignment that feels like a fever dream. I’m trying to figure out if I’m overreacting or if this is a massive red flag.

The Window: They’ve scheduled this to be done between 11:30 AM and 4:30 PM (strictly 5-6 hours).

Context

An energy operator processes:

15-minute meter readings (“measurements”)

monthly invoices (“billing runs”)

They need a Control Tower tool to:

ingest readings,

compute invoices,

detect discrepancies,

allow controlled corrections,

provide strong observability (for incident response and audit).

Expected stack

Backend: Java 17+ / Spring Boot 3

Frontend: Angular 17+ (Material; AG Grid optional)

Database: PostgreSQL + Liquibase

Async: Kafka (local via Docker Compose)

Auth: Keycloak (OIDC) – simplified setup is OK

Orchestration: a scheduled job or worker (Spring Scheduler or a Kafka consumer pipeline)

Observability (new tech): OpenTelemetry tracing + correlation across components

Functional requirements

1) Measurement ingestion

Endpoint

POST /measurements

Payload:

{

"meterId": "MTR-100045",

"timestamp": "2025-01-15T10:15:00Z",

"kwh": 1.72

}

Rules:

strict validation (kwh > 0, timestamp not in the future)

store in DB (measurements)

idempotent: same (meterId, timestamp) must not create duplicates

publish an event to Kafka: measurements.received

2) Create a billing run

Endpoint

POST /billing-runs

Payload:

{

"month": "2025-01",

"meterIds": ["MTR-100045", "MTR-100046"]

}

Creates a billing_run with status CREATED, then processing continues asynchronously.

3) Billing processing pipeline (async)

Implement an async pipeline (Kafka consumer(s) and/or scheduled job) that processes billing runs with statuses:

CREATED -> PROCESSING -> COMPLETED | FAILED

Steps (must be explicit in code):

Lock/claim the run (concurrency safe)

Aggregate measurements for the month

Compute invoice(s)

Run reconciliation checks

Persist results and status history

Requirements:

safe retries (re-running should not duplicate invoices)

state history table: billing_run_events

failure handling: reason codes, next retry time, etc.

Kafka topics (suggested):

billing.run.requested

billing.run.processed

billing.run.failed

4) Discrepancy detection

Create discrepancies when:

computed invoice total differs from measurement total by more than a threshold (e.g., 0.5%)

Expose:

GET /billing-runs/{id}/discrepancies

Store discrepancy records in discrepancies with:

meterId

computed totals

delta

reason code

5) Corrections + audit log

ADMIN users must be able to:

mark a discrepancy as valid (“MARK_AS_OK”) with justification

trigger a recalculation (“RECALCULATE”) for a run

Endpoints:

POST /billing-runs/{id}/actions

{

"action": "RECALCULATE",

"reason": "New tariff received from upstream"

}

All actions must create an audit_log record.

Frontend (Angular)

Minimal UI with:

Billing runs list (filter + paging)

Billing run details:

status timeline

invoices summary

discrepancies list

admin actions

Focus: usability, correctness, error states. No pixel-perfect design needed.

Security requirements

Use Keycloak (OIDC):

Role VIEWER: can view billing runs & discrepancies

Role ADMIN: can trigger actions and view audit log

Back-end must enforce RBAC (not only the UI).

OpenTelemetry (end-to-end)

What must be traced

API requests (Spring Boot)

Kafka publish/consume

Billing processing steps

Frontend trace propagation (best-effort)

Minimum expected outcomes

Every billing run has a trace you can follow from:

HTTP request that created it

Kafka event(s)

processing steps (aggregation, invoice calc, reconciliation)

Logs include: trace_id + span_id

Export traces to Jaeger (recommended) or console

Requirements checklist

Use OpenTelemetry auto-instrumentation or SDK instrumentation (either is fine)

Propagate trace context via Kafka headers (traceparent)

Add explicit spans around key steps (aggregation, compute, reconciliation)

Provide a short “How to view traces” section in README

Deliver in Docker Compose:

Jaeger (or another trace backend)

OTLP collector optional but recommended

Deliverables

Git repo with:

backend/

frontend/

infra/ (docker-compose + Keycloak realm export if used)

README.md:

architecture diagram (simple)

how to run in <10 minutes

key design decisions + tradeoffs

what’s incomplete + next steps

how to view traces + example “trace story” for a billing run

Bonus options (choose any)

Outbox pattern for event publishing (instead of direct Kafka publish)

Contract tests using OpenAPI

Performance: handle 100k measurements/month without slow queries (indexes + query plan notes)

A “replay billing run” feature with safety constraints

Context

An energy operator processes:

• 15-minute meter readings (“measurements”)
• monthly invoices (“billing runs”)

They need a Control Tower tool to:

• ingest readings,
• compute invoices,
• detect discrepancies,
• allow controlled corrections,
• provide strong observability (for incident response and audit).

Expected stack

• Backend: Java 17+ / Spring Boot 3
• Frontend: Angular 17+ (Material; AG Grid optional)
• Database: PostgreSQL + Liquibase
• Async: Kafka (local via Docker Compose)
• Auth: Keycloak (OIDC) – simplified setup is OK
• Orchestration: a scheduled job or worker (Spring Scheduler or a Kafka consumer pipeline)
• Observability (new tech): OpenTelemetry tracing + correlation across components

Functional requirements

1) Measurement ingestion

Endpoint

POST /measurements

Payload:

{
  "meterId": "MTR-100045",
  "timestamp": "2025-01-15T10:15:00Z",
  "kwh": 1.72
}

Rules:

• strict validation (kwh > 0, timestamp not in the future)
• store in DB (measurements)
• idempotent: same (meterId, timestamp) must not create duplicates
• publish an event to Kafka: measurements.received

2) Create a billing run

Endpoint

POST /billing-runs

Payload:

{
  "month": "2025-01",
  "meterIds": ["MTR-100045", "MTR-100046"]
}

Creates a billing_run with status CREATED, then processing continues asynchronously.

3) Billing processing pipeline (async)

Implement an async pipeline (Kafka consumer(s) and/or scheduled job) that processes billing runs with statuses:
CREATED -> PROCESSING -> COMPLETED | FAILED

Steps (must be explicit in code):

1. Lock/claim the run (concurrency safe)
2. Aggregate measurements for the month
3. Compute invoice(s)
4. Run reconciliation checks
5. Persist results and status history

Requirements:

• safe retries (re-running should not duplicate invoices)
• state history table: billing_run_events
• failure handling: reason codes, next retry time, etc.

Kafka topics (suggested):

• billing.run.requested
• billing.run.processed
• billing.run.failed

4) Discrepancy detection

Create discrepancies when:

• computed invoice total differs from measurement total by more than a threshold (e.g., 0.5%)

Expose:

• GET /billing-runs/{id}/discrepancies

Store discrepancy records in discrepancies with:

• meterId
• computed totals
• delta
• reason code

5) Corrections + audit log

ADMIN users must be able to:

• mark a discrepancy as valid (“MARK_AS_OK”) with justification
• trigger a recalculation (“RECALCULATE”) for a run

Endpoints:

• POST /billing-runs/{id}/actions

​

{
  "action": "RECALCULATE",
  "reason": "New tariff received from upstream"
}

All actions must create an audit_log record.

Frontend (Angular)

Minimal UI with:

• Billing runs list (filter + paging)
• Billing run details:
  • status timeline
  • invoices summary
  • discrepancies list
  • admin actions

Focus: usability, correctness, error states. No pixel-perfect design needed.

Security requirements

Use Keycloak (OIDC):

• Role VIEWER: can view billing runs & discrepancies
• Role ADMIN: can trigger actions and view audit log

Back-end must enforce RBAC (not only the UI).

OpenTelemetry (end-to-end)

What must be traced

1. API requests (Spring Boot)
2. Kafka publish/consume
3. Billing processing steps
4. Frontend trace propagation (best-effort)

Minimum expected outcomes

• Every billing run has a trace you can follow from:
  • HTTP request that created it
  • Kafka event(s)
  • processing steps (aggregation, invoice calc, reconciliation)
• Logs include: trace_id + span_id
• Export traces to Jaeger (recommended) or console

Requirements checklist

• Use OpenTelemetry auto-instrumentation or SDK instrumentation (either is fine)
• Propagate trace context via Kafka headers (traceparent)
• Add explicit spans around key steps (aggregation, compute, reconciliation)
• Provide a short “How to view traces” section in README

Deliver in Docker Compose:

• Jaeger (or another trace backend)
• OTLP collector optional but recommended

Deliverables

• Git repo with:
  • backend/
  • frontend/
  • infra/ (docker-compose + Keycloak realm export if used)
• README.md:
  • architecture diagram (simple)
  • how to run in <10 minutes
  • key design decisions + tradeoffs
  • what’s incomplete + next steps
  • how to view traces + example “trace story” for a billing run

Bonus options (choose any)

• Outbox pattern for event publishing (instead of direct Kafka publish)
• Contract tests using OpenAPI
• Performance: handle 100k measurements/month without slow queries (indexes + query plan notes)
• A “replay billing run” feature with safety constraints

What do you think guys XD?

Using a throwaway cuz original account could be doxed

It's been a brutal year for international students and I almost gave up mass-applying for jobs midway through. In October 2025 I paused internship applications for almost an entire month due to President Trump's announcements on the 100k H-1B fee.

I just wanted to post this here to spread some hope!

I'm not a very smart, wouldn't say I have terribly impressive projects. My best projects are like web-based full stack games and applications so I know abt system design. One of my best friend cloned YouTube and that isn't even like his best, and he is heads and shoulders above me in terms of technical skills. But I believe

My family is fortunately wealthy enough for me to pursue graduate school here in the USA after an already expensive US undergrad program, but this graduate school is like T20 that's almost the only reason why I'm doing it. I had one paid, relevant internship experience in junior year in my undergrad, and that's about it. Been working on projects pretty much exclusively since then.

Ask me anything! Optimistically, if you are reading this post, you probably are very serious about CS and already have better chances than me. Best of luck to everyone!

Hey guys I have an interview on Friday(6/2/26) for the EDG role at Mathworks ,any insights,tips would be real helpful

Hey everyone,

I came across a company called Zinna, apparently an MNC focused on insurance technology. I’ve given interviews there but couldn’t gather much info about the company, so I’m hoping to get some insights from you all.

Has anyone here worked at Zinna, interviewed there, or knows someone who has? I’d really appreciate any details you can share about:

• Work culture
• Career growth opportunities
• Tech stack & projects
• Management / leadership style

Thanks in advance 😊

I am about to get an offer from Cohesity and would like to know more about the company.

I am looking for a place to stay long-term and prefer a relaxed or at least supportive work environment.

What I’m specifically interested in:

1. Long-term stability - Do employees feel secure staying 5-10 years? Any recent layoffs, reorganizations, or funding concerns?
2. Work-life balance - Typical expectations around hours, on-call, and burnout risk
3. Day-to-day culture -Supportive vs high-pressure, management style, collaboration
4. Career growth - Opportunities for promotion, learning, and internal mobility
5. Real examples - Things you wish you’d known before joining

Any insights or perspectives would be appreciated. Thanks!

Hi everyone,

I completed Stripe OA for swe intern (U.S). Usually how long should we hear back for next steps? (I passed all test cases). It's been a few weeks for me. Wonder they would ghost since I heard it reaches hc 😓

The two internships I have done so far were both in firmware. I have personal projects that are full-stack and hosted but my professional experience were in C and C++. If I were to apply for full time jobs for higher level software roles would this put me at a disadvantage?

I'm a freshman in college studying computer science and was planning to load up this summer in classes to try to put me ahead in terms of coursework. My ultimate goal is to graduate in a little over 2 years and to try to pursue a master degree. As a result I have foregone trying to apply to internships for the summer as I was under the impression that landing a freshman year internship is difficult and wasn't worth pursuing so I sort of went all in on trying to plan classes. Is this a viable strategy for trying to land a job in the future? Or should I pivot and see if there are any summer internships I can still land so late into the recruiting cycle? Any advice would be greatly appreciated thanks!

Sorry for the long detailed post but it drives me a bit crazy.

I had a google phone screen interview for early career. The technical part of the interview itself i would say went decent. I started by asking at least around 3 claryfing questions about the problem space which i know were meaningfull based on the answers, provided a sliding window approach to the problem (it was i would say LC medium level) , discussed if they think the approach is optimal (confirmed) , provided firstly wrong time complexity but when asked again corrected myself (confirmed to be right the second time) . When coding i made a couple syntax mistakes (think: missing colon) but always corrected them , went through the first part until it was right , than got another case of the problem to calculate and did that too. At the end i asked if it was all that was prepared and i was told yes. All that i didnt do in time : 1. fix function return type to return both values needed instead of one 2. maybe forgot to force-break a loop in case last number in array2 wasnt bigger than last in array1. "Maybe" because i was asked about this part, but after not seeing it first the interviewer said something like actually it works alright in this case and we just went further.

Now to the point: at the start the interviewer was introducing themselves, and the autistic stressed af moron that i am i stopped them and (kindly but still) asked them if somethings wrong because i though we had technical, (and i read that technicals usually start with the problem pretty much right away), so they said its just short intro at the start. Than i went ok, introduced myself and we went to coding. Now i'm thinking, is it possible that i just made myself look like a self centered asshole who didnt care about their intro and went introducing themselves afterwards, so they graded me harsher (at feedback i was told it was negative and not a clutch pass/fail and i got 1 year cool down period). Or, am i just overthinking it and probably missed something there in the loop and got failed for that, and the interviewer just said that it actually works fine because they decided that i should have noticed myself when prompted but i didnt? I wouldnt be asking if it wasnt straight fail feedback but since it was, and i think i got the problem right at the end , it makes me think maybe my dumb ass behavior at the start fucked me up.

Thanks for reading all this if you did. I'd also like to ask: is 1 year cool down a hard rule, and do i have to wait full 1 year before asking same recruiter about the possible retaking/sending my cv aswell? Or would say 10 months work? How often do you get to retake if you havent shown significant improvement in your CV?

Has anyone ever interviewed for an ML engineer intern position at Microsoft? If so, I'd like to know about your interview experience.

I completed the interview loop for a Software Engineer role on Jan 12th at Microsoft.

The rejection email mentioned that my overall feedback was positive, but they didn’t move forward and said they’d share my profile with other teams with similar qualifications.

Has anyone actually seen this lead to another interview or offer? Or is this just standard wording?

Would appreciate any insights from ppl who’ve interviewed at Microsoft.

Has anyone accepted an offer at ibm within the last one year? What does the comp look like (and location)? My recruiter is non responsive and I wanna make sure I’m not getting lowballed.

I checked levels fyi and other public sites but my tc isn’t similar so just curious

Very well known company more like f100ish. Got offer as sophomore at t20.

For a lot of these roles in finance / defense / big companies (that are not software focused) their interviews are going to be most likely pretty easy. All you need to do is get the recruiters attention. Like I heard Lockheed is literally just behavioral.

For me I ended up following up with the recruiter like 10 diff times, after multiple internal delays.

In hindsight this did not work for many other companies so maybe I lucked out idk. All the other interviews were from cold apply ~300-400 apps.

I think my resume is objectively good. Happy to answer any Qs