Hi everyone,

I wanted to share my story in hopes that it gives some encouragement to those who are struggling with the current job market.

Long story short, I was laid off from my software engineering job in March 2025. It was one of the most devastating moments of my life. After months of struggling to find another opportunity, I eventually had to accept a job that paid roughly half of my previous salary.

Since January 2026, I've been working as a software engineer making $76,000 a year, with no additional benefits beyond health insurance.

But today, after almost three months of interviews and nearly nine rounds of interviews, I finally received an offer from a tech company with a total compensation package of $230,000.

I honestly can't describe how relieved and grateful I feel right now.

The past year and a half has been incredibly difficult. I've struggled with depression, constantly questioned my abilities as a software engineer, and felt completely defeated after countless rejections. There were times when I made it through multiple interview rounds, only to receive another rejection email. I spent so many days applying to job after job, preparing for technical interviews, and wondering whether all my effort would ever pay off.

There were definitely moments when I wanted to give up.

I'm not sharing this to brag about the compensation. I'm sharing it because I know there are so many talented people out there who are going through exactly what I went through.

Getting rejected doesn't mean you're not good enough. Sometimes, it just takes longer than you expect to find the right opportunity.

If you're currently unemployed, working a job that pays less than you deserve, or feeling hopeless after another rejection, please don't give up on yourself.

I know how exhausting and mentally draining this process can be. I know how difficult it is to stay motivated when nothing seems to be working out.

But things really can turn around, even when you least expect them to.

Thank you to everyone in this community who has shared their experiences, advice, and encouragement. Reading your stories helped me feel less alone throughout this journey.

I genuinely hope my story gives someone out there a little more motivation to keep going.

Keep grinding. Your next opportunity might be closer than you think.

My goal here is to give perspective into how people are working when there is an incredible amount of work to do and very little restrictions on AI use. Where I work I would say we are in the top 5% or so of AI adoption but not in the top 1%.

Context:

• "Hard tech" software - i.e. software much more complicated than normal SaaS but not a 10/10 hardcore. Think similar industry to EDA software

• Not an AI company but there seems to be rabid demand from enterprise for our AI product... It seems to me that a lot of enterprises have crappy access to AI so there is a lot of value in bundling an agent since they can't bring their own agent as easy as us

• Roughly 8 engineers who are contributing code full time, while other people drop somewhat slopped PRs as needed

• All the engineers have several $200 subscriptions to their preferred provider and can get more subscriptions as needed

• 25-30 PRs to the mono repo per day, currently the codebase grows at ~25% per month in terms of net new lines. Also lots of the existing codebase gets refactored every month so something like ~35% total code turnover

• Code review is the bottlekneck. People try and not just auto approve everything and we use lots of AI code review tools as well. Obviously people are not reading all the individual lines of code but I'd say we are still spending lots of time on architecture. Sometimes too much time

• In my first ~2 months I added around 500k lines of code, much of that was tests/ tooling/ CI so not all of this is like production code

• I don't use an IDE anymore and neither do most of my colleagues. I do use a diff tool with LSPs enabled to review my code and peoples PRs... so pretty close to IDE just not for development per se

• Overall it is going well - we are iterating fast and close to closing some potentially huge enterprise deals. Outside of these big fish lots of smaller contracts that are over the line

• There is some incidents but we are getting them down to a reasonable amount. Recently there was a very serious incident that put us on thin ice with one of our largest customers

• We have had the most luck on the "verifiable" portions of the codebase i.e. algorithms and workflows that we can clearly benchmark. Several cases of finding exponential speedups in our core workflows that wouldn't have been possible

• Our "algorithmic core" is getting really strong because AI is letting the people who were already good at math on our team do incredible things and letting people like me who know very little fix roadblocks

• Our UI/ UX is really, really bad - there is ten different ways to do things, huge amounts of feature creep and the happy paths are painful. I blame this partially on AI/ vibecoding and partially on skill issue on our teams part

• In terms of contribution to the business there is clearly "skill" to using AI atleast currently. The gap between most productive and least productive engineers is very large in terms of end contribution (not just PRs or LoC etc)

• At this point literally 0% of the codebase is human written

• We are creating increasingly restrictive lint rules and gen code patterns so that agents stop reinventing the wheel in every PR... this has been mostly successful

• Team is fairly young but org is interested in mostly hiring seniors going forward

• If someone told us they didn't use AI heavily we wouldn't consider hiring - the default assumption is that you are a heavy AI user here

• Work generally expands to fill the time and people work a ton, most of the employees have SO's/ exercise routine/ social lives so not full burn out schedule

So anyway it is a mixed but clearly positive bag. We are moving atleast 3x the speed of what would've been possible before but realistically more like 5-7x I would guess. It is mostly working in terms of helping us get to product market fit and then shipping super fast.

I often disagree with the attitude I see on this sub regarding actual productivity gains. We are not really a "greenfield" since we have plenty of active customers but not legacy code either. Hope this is helpful report from the front.

I interviewed 2 years ago for a position at one of big AI labs. I did pretty terribly at the interviews and was understandably rejected (had a bad few weeks back then). Fast forward now, got a warm internal referral for a role that is a very good fit but was blocked by recruiting as I've been banned from reapplying for a few years or forever? I wasn't told exactly for how long that would be.

This is quite shocking to me, since the referral is from someone that has worked with me in the past, and anyone can have a bad day? For those who might be wondering, I didn't say anything ourageous or out of order during the interviews.

Does anyone have any insights on what could cause such a ban? Seems incredibly extreme and I am trying to not let this affect me too much but it's hard at times.

Thank you.

Title. Assuming AI eats our jobs, is anyone considering writing a clean-room style implementation of the company’s platform?

Without the customer book it might not be worth it. Any thoughts on how can we migrate the customers too?

It generally feels like AI redundancy is coming for SWEs but the technology is there to also eat the bottom line of companies trying to save money on engineering. Ethics and morals do not only work top-down in an AI world.

I’ve been working as a firmware engineer at one of the world’s major semiconductor companies and have gained solid experience over the years. Unfortunately, I was in the wrong product line and got laid off along with several other colleagues.

I’ve been looking for a new job, and the process has been extremely difficult. I understand being rejected for positions where I don’t fully meet the requirements. However, I’ve also been rejected for roles where I seem to be an almost perfect match.

I consistently make it to the technical interview stage, and for the positions where I’m a strong match, I feel confident that I’ve answered the technical questions well and demonstrated the skills they’re looking for. Yet, I still receive generic rejection emails saying they’ve decided to move forward with someone whose profile is a better fit or who has stronger technical skills and that I need to improve my skills.

Is the job market really that bad right now? I started my career just after the Lehman Brothers crisis, and even back then, it felt possible to find a job. I’ve never experienced anything like this before. Will this ever get better? When?

Senior SWE here, I lead a team of about 10 people.

One of the most common things I am hearing about here, on LinkedIn, in private circles, etc., is this doomer mentality that AI is going to be replacing most people in the tech world. AI replacement is happening, but it isn't as widespread as people may think. There are several loud facts about AI:

1. Most AI companies have been operating with straight losses.

2. Multiple studies have shown AI doesn't increase productivity of employees for a cost offset.

3. Many companies are giving up on AI ventures or dramatically scaling back implementations (70%-95% of AI integration efforts are failing).

4. Litigation risks from AI are growing and further making it a liability to use.

5. Public sentiment in most places is heavily leaning anti-AI.

6. Existing and planned infrastructure isn't good enough to support replacing people with AI on any massive scale.

7. All major efforts to replace large portions of staff with AI have been short term catastrophes (forget long term, we haven't gotten there yet).

Companies are firing and laying off people using AI as a reason, when really they are performing routine cuts or RoF due to overhiring (there is still a heavily saturated CS market currently from the CovID era). There are also a massive amount of software engineers looking for work. This is a supply v.s. demand issue.

It is also not helpful that we are currently in a market where people are firing off AI slop resumes to every job posting they find, causing there to be hundreds if not thousands of applicants for a job that used to see tens of applicants. Prospective new hires are also decreasing in quality due to a lot of people attempting to just sail through using AI without actually knowing engineering principles. It's a rough world right now at the entry level.

Imo, AI is impacting us, but it isn't for the reasons a lot of entry level engineers are thinking. It also definitely isn't replacing anyone well enough to be considered even remotely successful (look what happened to Klarna)... so if you do get fired or laid off actually because of AI, you can expect a panicked letter or email in the near future requesting you come back (especially if you are experienced).

When I was working as a junior software engineer at a startup, I was assigned a task to delete some outdated records from a database.

I wrote the SQL queries, added tests, got the changes reviewed by senior engineers, and merged the code.

A principal engineer was supposed to get on a video call with me to walk me through the task, but he forgot about the meeting.

This wasn't just any principal engineer, either. He was widely considered the best engineer at the company—a genuine 10x engineer.

Afterward, he saw the SQL and claimed that it had effectively nuked the database. This triggered an emergency postmortem, with people scrambling to figure out whether we'd suffered a major data-loss incident.

The thing is, I was able to verify that the exact number of records intended for deletion had been deleted, and that no additional records had been removed. I posted those findings in Slack.

So, from what I could verify, the feared disaster hadn't actually happened.

I'm still puzzled by the experience. The code had been reviewed and merged, yet a principal engineer's assessment of it triggered an emergency response before the actual impact was established. Given his reputation as the strongest engineer at the company, I found the whole situation particularly confusing.

How normal is this in software engineering? Is this the kind of organizational dysfunction that juniors sometimes encounter, or was there something particularly unusual about how this situation unfolded?

I also wonder whether the principal engineer's behavior was simply an honest mistake, a misunderstanding of the SQL, or something more personal. I don't have enough evidence to conclude that he deliberately tried to undermine me, but the experience left me questioning what had happened.

Old Post where i had 250 reachouts in 2 years and climbed to 270 when I left: https://www.reddit.com/r/cscareerquestions/s/vEjGYGJFZ6

Now I have 100+ reachouts in 3 months. If this holds, that would be 3-4x the rate that I would be getting at the same level (mid level).

Can anyone else share their stats working at a top company as senior/staff+? Curious to see how K shaped the market is

Hey everyone, I wanted to share this because the job hunt felt endless for a while, and I would've loved to read something like this a few months ago.
I graduated in May and just landed my first full-time role. Over the past 4 months I applied to somewhere around 150-200 jobs, both data and ML. That turned into only 2 interviews, and both made it to the final rounds.

Interview 1 was a less technically in-depth role. I felt my answers were great, even though I didn't have formal work experience in that area, just some from school. I could still answer the questions. I didn't get it, and my guess is that all my experience leans ML, so I probably looked like a mismatch.

Interview 2 was an actual ML engineer role at a startup. The posting asked for 2-3 years of experience and I had none. My background is also research-heavy and in medical imaging, so while it's still computer vision, the application domain was pretty different from theirs. I applied anyway. My answers weren't perfect, but the conversation felt natural. When I didn't remember or didn't know something, I just said so. I made some jokes and let myself be a person instead of a perfect interview robot.

That second one is the one that worked out.

What I took away from it:
Be yourself and relax. Honestly this mattered more than I expected.
Know your projects inside and out. Be able to defend your model choices and explain how the pieces connect.
Be honest about what you don't know. "I'm not sure" or "I don't remember that detail" is fine.
You don't have to be perfect. Team fit is a real thing, and they're deciding whether they want to work with you, not just whether you can answer every question.
Apply even if you don't meet every requirement. I didn't have the 2-3 years and it still went to the final round.
Your domain doesn't have to match exactly. My experience was research-focused medical imaging, and I still got the offer for a CV role in a completely different industry. Being able to explain your projects and reasoning transferred.
If you're in the middle of the search right now: 150+ applications for 2 interviews is brutal, but it only takes one. Hang in there!

I’ve accepted an offer at this company, everything has cleared, and the start date is set, I requested a week ago to talk to my new leader, and I have requested that to the recruiter. I’ve been working with throughout the process, but I find myself without any response from the recruiter, no counter invites, nothing. Should I be worried?

Passed the interviews at Capital One for a Lead full-stack engineer position. However the only openings are for a data engineering role.

It sounds like the work involves building data pipelines and migrating to a microservices architecture, which implies some data platform and actual engineering work.

Manager mentioned they have higher expectations at this level, so I'll need to quickly ramp-up and learn data engineering on my own. Is it worth the switch to data engineering in this day and age?

Do I need to say more?

I love writing code. I love crafting it, I love making it elegant, efficient, I love testing it. I love building my solutions from scratch. AI is taking this away from me and I know I am being stupid but I don't know how to cope with this.

Is there any place left for me in the industry? Do I need to look for a job in a different domain?

Has anybody made the jump? To what?

I’ll make this brief: I’ve been stuck on an issue that is blocking two tickets of mine for more than a week now (had to carry to next sprint). I’ve reached out to him about it more than a week ago about it and he’s been barely helpful or communicative about it.
My blocker isn’t a coding-related issue or anything that copilot can help with, it’s regarding configs and certifications between our company and a third party vendor. So it’s not like I can keep trying new things or look at past examples

I’ve reached out to other seniors and they can’t figure it out, I’ve mentioned it in standups/public chats, went to him in person to ask for help, and even tried to schedule a meeting about it. He has had this issue ever since I joined the team, and I know he’s very busy with other things on his plate but he’s been pushing this off for a week+.

I’ve brought this up to my manager several times and he acknowledges that I’m not the only one to bring this up. But all he says is “I’ll talk to him about it” and “just keep bothering him”. Nothing ever changes in his behavior.

Currently, I’ve asked him today “can we sync up some time to go over this item?” And he’s left me on read.
I’m lost on what else I can do at this point

https://www.cnbc.com/2026/10/20/qualcomm-performance-focused-layoffs-reuters.html

https://finance.yahoo.com/markets/stocks/articles/qualcomm-reportedly-conduct-global-layoffs-180715429.html

Exact % not disclosed yet but word on the street looks to be between 5-10%.

"but aren't chip companies doing well?" except Qcom isn't in the AI infra space, their chips are for consumer electronics so they didn't benefit from the AI wave like other chip companies. So they're not growing, hence layoffs not surprising. One of the biggest employers in San Diego, CA.

imagine your CEO saying your company "has consistently fallen short of expectations" that's a big yikes from me dawg.

r/qualcomm having a meltdown

PS - Ebay to lay off 9%, wed oct 21 news; won't make a new thread.

----

Text from above links:

Qualcomm will cut jobs globally in a “performance-focused reduction” following its annual employee reviews, CEO Cristiano Amon told staff in a memo on Monday reviewed by Reuters, with notifications set to begin in November.

The cuts are part of an effort to build “a stronger performance culture” and address situations where the company “has consistently fallen short of expectations,” Amon said.

Qualcomm did not immediately respond to a request for comment. It had about 52,000 employees globally as of September last year, most of them full-time. Its financial year typically ends in late September.

One of the world’s biggest smartphone chipmakers, Qualcomm has been hit this year by a slump in consumer electronics sales as soaring memory prices weigh on demand in key markets.

Consequently, Qualcomm shares have experienced sluggish growth, rising just 1.5% in 2026, lagging significantly behind the broader S&P 500 and the Philadelphia Semiconductor Index (SOX).

Amon emphasized that the restructuring process will carefully weigh current business priorities, required organizational competencies, and individual skill sets. "As we have expanded the business, so have the competencies and skills we require," Amon noted in the internal communication. "We must have the right people in the right roles so they can perform at their best and the company can continue to succeed."

So I spent about 4 years at a very small company outside of tech, but managing internal web services with one other developer. I don't have much of a linkedin network because of that, so I decided to start adding random people that requested to connect.

Like every single one of them were US migrants from India. After I added some, more just started flowing in, and I kept accepting because cool, I'll make myself look like I'm well connected, why not?

I didn't really notice a problem until recruiters started pouring in, and I was like fuck yeah, this is it.

But every recruiter asks me if I have a visa, then I tell them I'm an American citizen already & I do not need a visa, they stop replying right then and there.

I'm gonna have to make a new linkedin to reset my algorithm, aren't I? 😭

I posted before about being proud of myself for the 2nd round and how great I did. I wasn't expecting anything further since this job is really cool and has a competitive pool. Welp, got the call that I am 1 out of 2, and scheduled to meet with the CEO.

This job really excites me; I did the same type of work but with different industry and data. This one is literally just a different sector, but all the same. I would love to work there. I've never done a CEO round though. What should I do to prepare and possibly edge out the competition? I've already got a full piece suit ready.

I know I'm late to the party, but I'm a frontend dev with 6 years of experience at the same company, and I'm trying to figure out my next move.

I've mostly worked with my company's stack, including Shopify, Three.js, React/Next.js, and some Laravel (mid-level, since backend isn't my main responsibility). I can build things with React/Next.js, mostly AI-assisted, but I'm not confident with the typical interview questions yet.

I've been trying to transition to full-stack while looking for a new job, which has been extremely difficult. Over the past few months, I got a VPS and learned some Docker/Compose, deployed a Laravel API with Nginx, set up basic CI/CD, and built a Node.js API around yt-dlp. Lately, I've been studying database design, complex queries, stored procedures, joins, and system architecture.

The problem is I keep jumping between things and can't figure out what deserves my focus.

Should I go deep into JavaScript/React/Next.js and interview prep first, so I can actually prove my 6 years of experience when I get an interview? Or should I focus on backend, databases, and architecture to become a solid full-stack dev?

Realistically, how long would it take me to reach the level companies expect from a full-stack developer? 6 months? A year or more?

I enjoy this field and I'm willing to put in the work and adapt, especially with AI becoming such a powerful tool. I just don't want to spend months building projects that only I care about, then struggle to demonstrate my actual knowledge in an interview.

I'd really appreciate honest advice from devs who've been through this transition. How would you approach it if you were in my position?

Context: Laid off two months ago, 4 years of SDET experience and applying to SDET, SWE, product owner/architect roles.

So far any traction with a company has come from recruiters or referrals. Haven't even had an HR call for roles I saw on a job board. Feels like a better use of that time would be to upskill/add to my (currently meager) portfolio.

The only evidence I have to the contrary is my first and only job out of college was a cold apply, albeit that was 2022 and new grad specific. Is my intuition right or should I keep applying to everything I see?

So I'm a year 2 student who has substantially self studied way ahead my peers (FS app in progress and currently studying HCIA), and I cant help but notice how subpar our facualty environment is. It alongside faculty student orgs do host many useful talents and resources, but they arent static and present for all and can have some frankly egregious paywalls. I'm aware you shouldn't be spoonfed info, but the lack of cohesion in self study may affect some people's progress and halt it, I'm planning on changing it hopefully for the better.

The idea is faculty/student orgs supported extracurricular courses to help give students an applied edge in CS and attaining potent skills. They are to be fixed and face to face with them being recorded to support them more. Possible courses(with bringing your own devices)are as follows.

DSA: Preferably alongside the uni course, its basically PS sessions where any gaps can be closed early on via early exposure and consistent practice. The main resource w such a course would be testbanks and mocks that can sharpen PS for learners.

Networks: Basically being a lighter CCNA that can ease students in applying them so more efficient solutions can be reached. Can contain a sequel courses for topics like security or WLANS

SWE: The only one that has fixed sequels, 1st course is basically providing the skeleton for a FS app and student code their own solutions w expert supervision. Final products are provided and assessed by the teaching board. Sequel courses follow that structure but w more advanced topics.

Interdisciplinary: Certain faculties may have some specializations like Fintech, Edutech, or HIT. Project based courses can be tailored so students can run through realistic SDLCs in different sectors and strengthen their domain literacy.

These are some ideas I have bounced off in my head for such an initiative. I'm aware it may seem abit too fairytale-ish, but I feel its prolly for the best for a CS student. If you have any critiques or possible refinements please do share them.

upcoming L4 interview at big tech research lab - anyone know how to prep properly? not sure how this differs from standard system design -also pretty sure it’s not actual ML but very heavily LLM related

Has anyone who recently interviewed for research engineer / software engineer / research scientist and is able to give some pointers on how to prepare?

Thanks all

I am halfway through my first semester at an Ivy League school for a computer science program.

The beginning was great, learning computer architecture, python, etc. However halfway through the semester we started Java and at this point I’m feeling burnt out between my full-time job at a bank and doing these courses.

But the main thing that’s exhausting me is learning these languages when at work we consistently make programs utilizing AI to build things instantly. As I plan to continue with the masters program I’m worried that what I’m learning won’t be that useful after graduation. I am young 20’s and my job pays for the masters.

I know it’s extremely early in the program but I’m just worried that the material won’t be useful as Claude as reverse engineering full video games into each other and self replicating in computers and doing all this advanced stuff.

I would love to combine my finance background and computer science because I have a passion for both, I just find it difficult to invest the time when AI is so advanced when it has only been around for a handful of years! I suppose my main concern is learning things that aren’t applicable/useful by the time I finish in 2 years.

Any insight/opinions would be great, I am excited to hear from students, earlier career, mid career, or even late career and their opinions.

I am an intern for a nonprofit, really a volunteer intern, but thankfully am at least paid a stipend. I recently accepted another role that is full-time, but would mean I would have to end the internship earlier than the planned 6 months. Due to it being a volunteer role, it wasn’t much of an issue after bringing it up, despite me wanting to continue completing both. The company posted about a role opening up for the company on another team that would be full-time, and I applied as I truly enjoy the company and would love the opportunity to stay. I am wondering if this is against hiring ethics?

So the problem is this, in university most of the stuff we learn about Operating Systems is theoretical. But the reality is that a job is usually far disconnected from those skills. Not completely of course but there is a gap.

I want to improve my practical knowledge about operating systems to become a system administrator.

What skills should I work on? What topics should I read into? I know I can just ask gpt but I need the perspective of real people working in real jobs...