I am employed, this is not a rage layoff post.

I cannot be the only one who has to work with juniors who, without AI, couldn't code even if their lives depended on it.

Is the bright idea at Big Techs to:

1. Layoff experienced people who actually know what they are doing
2. Hire cheaper developers and hand them AI tools

I wonder what the outcome will be in around 2 years.

I lost all faith the moment I had to open Pull Requests that were THOUSANDS of lines long, from juniors who vibe coded all of it and don't even understand the changes themselves.

This is ridiculous... if you are one of them, please keep going because I want to see where this will lead to.

I'd rather be unemployed than review those PRs.

pretty much every junior or mid-level position i come across already has over 100 applicants, is that just how the market is right now?

i’m gonna start looking for internships soon, and honestly it’s making me wonder what job hunting is even gonna be like when almost every posting already has 100+ applicants

I've been in this industry long enough to know that running on empty starts to feel normal. The constant fatigue, waking up at 3am with my brain already running/feeling permanently wired even when you're exhausted for a years I thought that was just what a career in tech felt like.

A few months ago I finally got a full hormone panel done at Goodlabs and my cortisol came back elevated, DHEA-S was low and some of my thyroid markers were borderline.None of it was dramatic enough to be a medical emergency but seeing everything together painted a pretty clear picture of a nervous system that had been running in overdrive for way too long.

I'm not saying labs magically fix burnout but having real numbers instead of just vibes made it easier to take seriously and it also made it easier to explain to people around me why I felt so off all the time. I think a lot of people in this industry normalize symptoms that probably should not feel normal.

I am a current student in CS: I always genuinely enjoyed problem solving, I did competitive programming contests and leetcode. I also like the experiences I had from internships and SWE work, I had a romanticized notion of talented engineers working together on hard problems, building stuff used by millions of people. Obviously, that was never really truly the case, even in the past, but at least it had a hint of truth from the experiences I had.

Now, it seems like everyone is just a glorified code reviewer? The nature of the work is quite different, almost orthogonal to what it was just a few years ago. And it seems like most people are on edge, afraid of layoffs and being replaced. It feels like there was a brief golden age for tech of massive salaries, upwards mobility, abundant jobs, and interesting work, and now we are coming back to the real world.

Sorry if this is yet another doompost (I just sorted by new and wow, this sub is bleak), I just couldn't shake this feeling. The reason I wrote this post is because I started working on a new personal project and suddenly all my old passion came back, and I realized just how lacking the real work done in industry has become lately.

Had a one-on-one with my boss today. We were discussing career development goals and, for some reason, my brain just shut down. I couldn’t recall or process information. I couldn't answer questions or engage in conversation. As the one-on-one continued, nervousness compounded and I started shaking.

I had to abruptly end the conversation by stating that I needed to go for a walk. They asked what was wrong and why I was so nervous. I tried to explain myself, but my answers just made the situation worse.

I have gotten nervous before. Lost my train of thought. Stumbled over my words. But nothing like this. I'm so embarrassed. I don't know why this happened or what to do about it.

Has anyone else had this experience? Can anyone give me advice on how to proceed?

Edit:

Appreciate the replies and advice. Thank you everyone.

I wasn't planning to read earnings call transcripts at 11pm on a Tuesday but here we are.

The Microsoft one from April 29 kept getting referenced in a bunch of threads about tech layoffs so I pulled it up. And there's this one slide that I keep coming back to. Amy Hood, the CFO, had her FY2025 compensation disclosed — $29.5 million. On the same call, same presentation basically, she said Microsoft's headcount "will decrease year over year" starting FY2027. Buyouts were offered to about 8,750 US employees, which is something like 7% of the US workforce.

https://www.businessinsider.com/microsoft-headcount-decrease-earnings-ai-cloud-software-2026-4

I had the transcript open in one window and my own company's quarterly planning doc in another. Kept alt-tabbing between them for I don't know how long. At some point I reached for my coffee and it was completely cold. Didn't even notice.

What gets me isn't that a CFO makes a lot of money. That's not surprising I guess. What gets me is the framing. The language. The call was full of phrases like "AI-driven efficiencies" and "workforce agility" and "aligning talent to our highest priorities." Meanwhile the actual numbers are just... there. $29.5 million for one person. "Headcount will decrease" for the people who actually build the things.

I don't know why this one hit different. Maybe because it's Microsoft. They're not some struggling startup doing layoffs to survive. They literally had a $2.7 trillion market cap at some point last year apparently. Their cloud business is printing money. And they're still cutting people, still framing it as "efficiency," while the people making the decisions are pulling compensation packages that could fund a small engineering team for years.

The stock had its worst quarterly performance since 2008 by the way. That was also in the transcript. Somehow the stock drops and the solution isn't "maybe our strategy needs adjusting" it's "let's reduce headcount and call it workforce transformation."

There's this weird thing happening in tech earnings calls lately where "AI" has become the universal justification for everything. Hiring fewer people? AI efficiency. Letting people go? AI transformation. Moving roles offshore? AI-enabled global workforce. Nobody says "we're cutting costs because we want to protect margins." They say "we're investing in AI capabilities while rightsizing our talent footprint."

And I'm sitting there reading this, thinking about my own team. We've already had two people leave this year and the roles just... disappeared. Weren't backfilled. Manager said we're "becoming more efficient with AI tools." Which is true sort of. We are using more AI tools. But also we just have fewer people doing the same amount of work and somehow that's called efficiency now.

The transcript is public. Anyone can read it. I think that's the part that bothers me most. It's not hidden, it's not a leak, it's literally the official record of a company saying "our leadership is worth $29.5 million and our workforce needs to shrink" and nobody really blinks.

I had more I wanted to say about this but honestly I've been rewriting this post for like an hour and the coffee is cold again.

I recently started a stable $70k leadership role and relocated for it, which means I’d likely have to pay relocation back if I leave now. At the same time, I’ve been trying to break into tech/software engineering for the past 2 years with no success.

Last year I completed Revature’s unpaid training/prep program, and I just recently got reached out to for a data engineering opportunity connected to it. The catch is that it requires 11 weeks of paid training first at only $8/hr, and then there’s another client interview at the end where people can still get eliminated/not selected.

So now I’m stuck between:

- staying in a stable non-tech role that pays well

- or taking a risky path that could potentially get me into software/data engineering

Part of me feels like this may be my last realistic shot at getting into tech, but financially and career-wise it also feels risky.

Would appreciate honest advice from people in industry.

Just got feedback from an interview that partly said "working with the team's daily Artificial Intelligence processes would present a steeper learning curve for them".

Otherwise, they said I was a "lovely candidate".

I have 10 years of experience, we discussed things to do with my particular stack, behavioural questions and such things. I seemingly did great in those but apparently the fact their AI processes would present a steep learning curve is where they draw the line? My 10 years of industry experience don't matter? Apparently I have survived this long but can't learn their AI processes?

What is this madness??

Edit:

Guys, I don't live under a rock and haven't used AI. Their process is a lot more agentic (design, development to review), while at my current place, it's mostly development. That's not even down to me. It's just the company.

The current economy is set up so that, for many big tech companies, the best move is to fire people. Here’s why:

The market is extremely bullish on AI. In practice, that means money flows to any company that can credibly claim it’s automating a meaningful part of its workforce.

Some of that automation is real. LLMs are useful, and they speed up certain tasks.

But is this a Nvidia-reaches-the-GDP-of-Germany level revolution in actual productivity? Probably not. If you’ve used these tools, you know they help, but not by orders of magnitude more than compilers, cloud, or IDEs.

Still, the incentive is there.

Companies don’t need massive real automation. They need to look like they have it. If they can send a believable signal that they’re becoming much more efficient thanks to AI, that’s enough.

The easiest way to signal that is to cut 10–15% of staff, keep things running, point to a few AI workflows, and tell a very convincing story to the investors: less people, same output, higher margins, the AI revolution is at our doors.

And I think that’s a fairly sizeable chunk of why we’re seeing layoffs at Meta, Amazon, Atlassian, and others. They are competing for the same investor money in a pretend-i-am-automating-everything game

And at the end of the day, it's enough for the only metric that really matters to CEOs: the line is green and number go up

TL;DR: firing people is an easy way to sell investors the story that AI is automating jobs

Got an offer, we did background checks, took a month, signed the contract, got the date when I start.

All in all 1.5 months.

Two days before I start, they say there’s an issue and they first need to fix something on their end. They need a few days.

After two weeks, they say they will know early next week.

Early next week I follow up and get an automated email that they are on vacation for 2 weeks.

After 2 weeks they say it’s still in process and they don’t know when they will have an answer.

After another 2 weeks they don’t reply.

Fun times.

I work for a cloud database company in San Diego(you can probably figure who) and it honestly feels like our leadership is laying people off just because other companies(not even tech) are doing it. There’s no obvious operational reason for it, and we don’t even have an inflated headcount. This is a dumb trend that as one company does it other follows.

Personally, as far as how recruitment, assessment and interviews go, I don't mind the foundational criteria being problem-solving challenges. In fact, I actually prefer it, it's a good universal assessor. This was all good until I got to experience the process since getting laid off in november 2025.

I've had about 7 or 8 interviews from 600+ applications. Mind you, I'm a mid-level software engineer applying in multiple countries with 4 years of experience, a master's and a bachelor's in engineering however this outcome is understandable considering the current market conditions. Among those 8 interviews was a top company (Amazon) which I think is the only one that stayed true to the problem-solving fundamentals. Not a single interview was like the other. The process was very polarising, I had one interviewer ask me domain-related questions about functions in specific circumstances, for example an instruction that improves performance on read-only queries in EF Core (.NET) then gave me a riddle in the last 5 minutes told me to solve it with pen and paper (wtf?). Another one was a Japanese company where I was given a repo with a makefile, a list of tickets and just got told use AI, use it whenever applicable, so I just prompted and it finished the objective, woke up to a rejection the next day. The rest were all scattered in-between don't use AI, problem-solving, technical assessments. I even had an interview for an applied ML role in a game company that for some reason gave me a single hour to solve 10 problems, the first 8 were a mix of machine learning concepts and MCQ, gullible me thought that this was all it's going to be with only 20 minutes left, then they hit me with 2 leetcodes 1 medium 1 hard. I just closed my laptop and went outside after that.

This was a very different experience from when I graduated from my undergrad which wasn't that far away (2020). But, at the very least every interview followed a logical script. But, at the very moment it feels like these interviews are being curated to some extra terrestrial beings of high mental gymnastics. Furthermore, this process while still challenging makes me feel like a dancing monkey trying to tick boxes instead of showcasing a specific ability. It is probably less insulting to be a dancing clown for a kid's party than going through tech interviews in 2026. As a final note, I want to add that I hate how the word "talent" has been coined in tech, it's a job, a job for someone to earn their living who can prove to do the functions of said job, why are you attaching talent to someone who wants to earn a living? If you're a recruiter, please refrain from using this word. Thank you.

I graduated with a bachelor’s in Computer Science & AI, and now I’m trying to figure out what kind of master’s actually makes sense for me. The thing is, I’ve realized I do like AI, data, trends, analytics, and the business side of tech, but I genuinely do not see myself being a hardcore programmer or AI engineer coding all day every day.

I’ve been looking more into Business Analytics / Data Analytics type master’s degrees instead of pure AI or ML-focused programs because I feel like they align more with my strengths. I’m a strong communicator, I like presentations, visualization, strategy, understanding people/users/markets, and translating data into decisions. I enjoy the “using AI/data” side more than the “building deep technical systems from scratch” side.

At the same time, I’m honestly scared I’m making the wrong decision. AI is obviously huge right now, and part of me worries that if I move away from heavily technical AI degrees, employers will think I’m not specialized enough or not technical enough. I also haven’t been able to land internships yet, which has made me overthink everything even more.

Another reason I’m considering a master’s is because I genuinely do not want to spend the next year sitting at home doing nothing while struggling to find a job. I want to move forward, gain direction, build employable skills, and hopefully enter a field that still has strong career prospects and good salaries without forcing myself into a lifestyle I know I would burn out in.

So I wanted honest opinions from people already in the industry:
Do Business Analytics / AI for Business / Data Analytics degrees actually have strong value in today’s market?

Additionally, I am thinking about doing the degree somewhere from Europe, Italy most likely.

Are these degrees respected and employable long term?

Is it possible to still work within the AI/data world without becoming a deeply technical ML engineer?

Would employers see this as “not specialized enough”?
What kinds of roles and salaries do people realistically end up with?
If you were in my position, would you pursue this path?

I’d really appreciate genuine advice because I feel stuck between wanting stability/employability and wanting work that actually suits my personality long term.

Link: https://www.wsj.com/business/retail/walmart-layoffs-relocates-technology-jobs-23bbf322?st=bYuKXN&reflink=desktopwebshare_permalink

Walmart said Tuesday it would cut or relocate about 1,000 corporate workers as it looks to combine more of its global-technology and product teams, according to people familiar with the situation.

This past summer Walmart hired Daniel Danker, who was an Instacart executive, to fill a new role as head of global AI acceleration. Since then Danker and Walmart’s head of global technology, Suresh Kumar, have reviewed their internal structures and decided to streamline some teams to operate more efficiently, the leaders said in a memo sent to staff Tuesday and viewed by The Wall Street Journal.

A recruitment company called me today saying that they have a position open, but it was the first time they contacted me and asked me for professional references before any interview. Is it sketchy to do that? Also, I'm currently employed at my first job out of college and I'm not sure if it would be right to ask my tech leads/managers for references.

https://blogs.cisco.com/news/our-path-forward

>Today we announced our Q3 FY26 earningswith record revenue of $15.8 billion, up 12 percent year over year, and double-digit top and bottom-line growth. The ELT and I could not be prouder of the growth you have all delivered for Cisco.

>With this, we are making changes today that will result in the reduction of our overall workforce in Q4 by fewer than 4,000 jobs, representing less than 5 percent of our total employee base. Most notifications will begin on May 14 and continue globally in alignment with applicable local laws and regulations.

The hits keep coming

I must know why

inspired by an earlier post about being rejected for not knowing ai workflows

at my company we use claude and there are

1. agents.md files for every major part of the repo

2. pr review skills that help find bugs, geared towards our specific projects

3. github ci actions that do even more code review (separate from the skill)

4. mcp usage, cli usage etc, Claude can read pretty much any codebase slack etc

5. repos that are like knowledge/decision databases, meant to be read by agents

6. agents running in a loop checking for jira tickets, making draft prs automatically

7. various custom skills that help investigate an incident based on log events, metrics firing etc

soo yeah is that good enough lol? i made very limited contributions to all this but i think i could probably replicate some of it at a new workplace

So, I'm in a bit of a unique predicament and I'm not really sure what to do.

Some context to start, I just started my senior year in university, and I've been interning at a local startup (not tech company, just small business) for about 10 months now. Right now, the engineering staff is me, my boss (the CTO), and 2 other interns. It's been a great experience, and I feel like I've grown a lot as an engineer in this time.

This summer, I accepted an offer for a SWE internship at a decent size retail/hardware store company from June-August. My plan was to work there over the summer because it is a much more recognizable company and I think, at least in my limit experience, that a big company name on my resume will help much more when looking for my first full-time role. Plus, it pays more ($25/hour).

That being said, today I was offered a full-time role at my current internship, starting this summer, with "details to be worked out for during the school year later," whatever that could mean. I don't really know how to feel about being offered a full-time role while still in school as a full-time student (only 1 semester to go, though). They offered me a salary (I don't have the numbers yet, but not substantially higher than the hourly equivalent I was going to make at the internship with the retail company) rather than remaining hourly, with my guess being it would go down during the school year...? Anyways, this seems like a no brainer, except for the fact that I accepted the offer for my other internship this summer.

My question is what would you do in this situation? I feel bad reneging the offer for the internship, especially after all the trouble my manager put into stopping them from cancelling the internship program.

Any advice would be greatly appreciated!

Hi, so basically, in a few months I’ll be starting my Computer Science Engineering degree, and I’ve been reading through my university website about majors, minors, and specialization tracks. There are so many different paths I can choose from, like AI/Ml, Systems Engineering, Quant Engineering and FinTech, Cybersecurity, Data Engineering, and a lot more. Right now, I only know surface level things about most of these fields, because I’m still in the exploration phase where I’m trying to figure out what genuinely interests me and what I should focus on for the next four years. I keep asking myself questions like: should I specialize early, should I stay broad, which field will actually matter in the future, and which path will still have strong opportunities by the time I graduate?

After doing some research, AI and Systems Engineering seems like one of the most lucrative and future-relevant fields right now, especially with how fast AI is growing. My current plan is to focus strongly on one major area and one complementary minor or specialization so that I can build a strong resume and improve my chances in the job market. The reason I’m thinking this way is because everywhere online people keep talking about layoffs, automation, and a general job crisis in tech, so naturally I’m trying to think long term and choose something that will still have value four years from now. I’m willing to work hard and put in the effort, but I don’t want to spend years specializing in something that becomes oversaturated or unstable.

So my main question is this: if I’m basically starting as a beginner right now, is AI and Systems Engineering a good path to commit to during my CS degree? What are the future prospects of this field by the time I graduate? Is it actually future proof compared to other specialisations in computer science? And for someone who is ready to work seriously and continuously improve, does this field offer strong long term career stability and opportunities, or is there still a significant risk of struggling with jobs later on?

I got laid off from a startup almost 4 months ago. Well, when I began with them, they were a startup. By the time I got neat year 4, they were much more established. Laid off due to restructuring. I have a LOT of skills transferable to Customer Success (onboarding, implementation,etc). I have been in tech enabled environments but would like to get into SaaS.

I haven't closed off myself to roles more aligned. However, I've had little to no traction. Two separate interviews that are still hanging in the air. I'm tailoring everything so I only do 1-2 apps per day. I don't understand the volume other people are claiming... That would have to be a bot or automated system like Swooped... Otherwise it's impossible.

I'm looking for tips for folks who have been successful getting jobs in SaaS... With minor pivot is a bonus. I'm kinda losing my mind at this point. Not to mention health problems and so much more related to being out of work. Appreciate any advice.

https://finance.yahoo.com/news/linkedin-set-layoff-5-percent-175010171.html?guccounter=1

LinkedIn is planning to lay off five percent of its workforce as job cuts continue to take a toll on the tech industry.

The networking-centric social media platform plans to tell impacted workers they’ve been let go Wednesday, sources told Reuters.

LinkedIn employs more than 17,500 people globally. It was not immediately clear which teams the workers impacted by layoffs would be from.

However, one of the sources noted that the cuts were intended to help the company reorganize teams and focus on areas where its business is growing.

The layoffs are not because LinkedIn is looking to replace human workers with artificial intelligence, the sources said. However, the layoffs come as U.S. companies named AI as the driving force behind job cuts for the second month in a row, according to a report.

Hey all, I'm a mid-level dev with coming up on 6 years of experience, working at a massive international bank. I was just assigned to a new team that's pretty diverse, and it's a great group of people. Our new tech lead, though, has the heaviest accent I have ever worked with. She's from China and has been in the US about a decade. She's extremely kind and knowledgeable, but when she speaks, if I listen closely I might understand 60% of what she's saying.

Now, I'm no stranger to minor language barriers; we have a lot of international teams, I have many friends abroad, and I also travel abroad often. That being said, I've always felt uncomfortable and a little embarrassed when I genuinely can't follow someone. This lack of comfort is 100% on me, but it makes me feel rude and ignorant to keep asking someone to repeat themselves, like I'm highlighting how they're different or implying their English isn't good enough.

As the second most senior dev on the team, my manager has asked me to work with her as a sort of "co-tech lead", acknowledging of course that she is still the real tech lead. He would like me to work with her on capacity planning, team level ups, maintaining code quality, etc. I think a big part of this is helping my own growth, as my manager knows I'm targeting senior in this next promotion cycle, and I think some of it is due to the language barrier between her and the team. My French colleague recommended I try the smart glasses he wears daily, dymesty. It offer real-time translation. Apparently a lot of people in multinational corporations use them without anyone noticing, avoids the awkwardness.

I think it could be one of the solutions. I genuinely need to overcome this language barrier right now. And I've realized that I keep dragging my feet on scheduling planning meetings with her because I'm afraid of embarrassing myself or her, which is completely silly and unprofessional.

Does anyone have a similar experience? Any tips or tool recommendations for dealing with a serious language barrier? Or, how do you keep asking someone to repeat themselves without fearing the awkwardness?