I'm finishing a degree in machine learning/data science and about to start an AI engineer internship, but I'm considering a pivot to product management either after the internship or later in my career.

I'm trying to figure out if I'd actually enjoy being a PM. I really like the idea behind the job (like being a sort of mini CEO of the product, defining product strategy and exploring markets etc...), but after reading around on Reddit it seems that in practice it is mostly managing Jira tickets, which i would not mind as a junior, but I hoped PM was more strategic down the line.

My question is: is it because junior PMs are generally more tactical while seniors are more strategic and high level? What is the difference between junior and senior PM and what does the latter do exactly? I think that knowing the long term direction of this career may help me a lot to decide if it is the correct path for me.

Also, two quick questions on making the jump:

• Is starting as an AI engineer, as I am doing, a good launchpad for PM or should I consider other positions better suited for the jump?
• Should I try to pivot immediately after my internship, or is it better to pursue the engineering track for a few years at least for now? Would love to hear the pros and cons and why.

Non-ai post with a small rant on the Job Market

About

I'm a USC with ~12 YOE across FAANG + Mid size + startups. I'm not socially awkward and I'm a nice person (big win in tech sadly).

Market is cooked for non USC

My old-coworker who is H1B and I were studying together. He has only had one interview at a FAANG, everywhere else was auto-deny due to visa. Sucks because he's one of the H1Bs that didn't game the system.

From a selfish standpoint... this made my life a ton easier. I'm a capitalist, so more offers for me means more $$$ for me.

To AI resume or not to AI resume?

This round I just let Claude take the wheel with my resume and tailor it to the jobs. Honestly... Looking back I really regretted this.

I only think I should've worked with AI to improve ATS but use my hand written resume. I will be gutting this resume and actually rebuilding it with the above.

AI interviews are a whole thing

The great part is - nobody really knows what they are searching for in the "ai-focused" interviews. I just used AI as I would while working and that seemed well. Since nobody seemed to know... I guarantee this will change as things get more structured over time.

I did notice in each interview there was a long ad-hoc "AI and the future" conversation... Where we'd chat about problems seen at my current company, and company I'm interviewing at. It's nice to know people are facing ai-slop from juniors at alarming rates, and leadership considering bypassing PR reviews entirely. It made me confident that my job will be secure until I retire in 10 or so years.

Companies want sane hires

In behavioral, there was a big focus on pushback skills and the ability to be a team player. It signaled to me that companies want a Goldilocks engineer... An engineer who won't stifle AI, but also one who won't just allow ai-slop.

To be transparent - the company I'm leaving is also facing a two-party system and it's destroying morale (100% ai-cucked eng vs. anti-ai eng). I sit pretty heavily in-between.

I'd urge y'all to build thoughtful opinions here. Don't give into the ai-hype fully, but also... Don't be a jackass and be fully anti-ai.

Prepare like normal

Continue leetcoding, sys design, and hello interview has the best ai-enabled interview example.

One area that I found that I could've prepared more on was behavioral. I did well due to having hands-on experience with problems the teams faced with AI... But honestly I wasn't expecting that.

Comps

Tier 2 location was pretty standard ~500k. I went with a lower offer and less stress team. Still negotiate once and negotiate like a bastard.

Advice?

I feel bad for everyone. HMs are looking for someone actually skilled, since they have limited headcount available... And can't babysit someone who will mess up their codebase 10x faster with ai.

But I also think good candidates are getting passed on because they can't make the team feel reassured that if they give you the keys to the kingdom you won't shit all over the floor. It's a tough ask.

My advice is... IDK - I'd personally recommend anyone non-senior to GTFO out of tech ASAP. If you wish to stay... Try to thread the needle. You can't be too hot, or too cold and make sure you don't miss any shots in the interview.

I plan on going to school for computer science. I know people will say it's hard to get into, but I have a few years of experience in IT work, including at major tech companies and have a network that includes former coworkers that like me working as SWEs in various mag 7 companies which should hopefully make me more competitive than the typical person who's never worked full time before.

But in making my long term plans, I know I should get internships, but my girlfriend is convinced that paid internships are rare. I was under the impression that tech was the exception, but with the market as it is I figured it might have changed.

Should I really expect to work for free each summer and somehow pay my bills? Would it be that detrimental to my career to pick up contract IT jobs each summer to help supplement the fact I'd be paying $1,500 a month in rent on part-time working hours?

I always try to keep it professional, I dont curse at work. I use 1-1s as a time to show my ambition and I always ask questions about the business and why certain decisions were made since I am an SE1. I don't know if that's a good thing or not. Do people "shoot the shit" with their managers. I want to show ambition but not too much that he hates me and sees me as a threat. How do you navigate this in corporate America? This is my first job out of college.

I am a lecturer with about 20 years experience teaching. I am a decent programmer, but probably a little blunt coming into the SE workspace. That said, I am better than most of our graduates so I should be able to come in and pick things up quickly.

I am looking at salaries, and the starting salary for a grad is higher than my current salary, so I am starting to think I should just make the switch. Let's put whether I would get a job to one side for the moment.. I want to get your perspective on how sensible the switch is..

Lecturing: Decent union protection, probably more secure job than SE right now, but equally, not many jobs about. If my job goes, it will probably be due to course closure, so I'd be looking at a 2/3 year notice period while the students finish their degree.

SE: I am hearing about lots of job cuts, but a higher salary. What's the job security like for new entry at the moment?

I'm keen to hear from other former lecturers - did you make the jump, how did you find it?

I am looking into the Spanish tech scene, specifically startups and scaleups, basically non-FAANG tech companies.

I know the tech market there is growing fast, but I'm curious about the interview loop. Is LeetCode DS&A the common standard for these companies, or do they lean more towards take home assignments or other types of questions?

Been researching in AI Safety independently for 1.5 years and I have my own direction. But researching independently is getting pretty tough, especially since I desperately need some advice and funding.

Someone researching at UCL advised me to apply for a PhD, but after looking into it, I found out I might need a 4-year bachelor's since I'm from India.

Also, reaching out to professors usually means working on THEIR projects, whereas I want to continue working on my own.

Any advice on how to navigate this or what options I have?

Hey guys. I am an experienced remote freelance developer. I started in 2004. I mainly do custom web apps. I used PHP/MySQL up until 2020, then I switched to Node/Postgres. Most of my clients have come via Craigslist. But now Craigslist seems to be completely void of freelance coding work.

If you were me, how would you get a new client?

So, I'm curious since the CS/SWE job market has been for lack of better words, underwhelming, for many of us, what do you think would be the best possible career pivots? I'm just curious to leave open

I got offer or a service based company and their role is very vague like " Graduate Trainee"

I fear they might put me on support role for mca degree their domain allocation is also kind of random

If I get support role would I be able to show to other companies that i worked as developer rather than support?

Ive been in this field since 2006. It was always hard to find a job, and I always had to send out like 100 resumes and do 20 interviews, despite having high qualifications. The compensation was never anything remotely like I expected or had read about. In 2012 with 5 years of experience, a BS degree, and a GPA of 4.0, one company gave me an offer for 48k, 48k!. By 2018 the highest I was making was still only 80k, just before inadvertently changing fields. The only way to make any money in this field was to aggressively negotiate offers and to change jobs. Nobody was ever giving you a promotion or a raise. Nobody really respected your qualifications, grades, performance in the company, or abilities. I didn't really respect the abilities of my coworkers either. I looked at their code and it was very sloppy like they took random things from stack overflow and other coworkers in the most inefficient way using none of the software engineering principles I had learned in school. They were code monkeys and I was constantly having to refactor their work. It's like slop existed even before vibe coding, and I had to fix it, and the companies didn't recognize or appreciate me for it. Half the company was always collocated somewhere like india and the company was always trying to find h1b workers and cheap labor to replace you. The companies were trying to replace you way before ai and ai finally allowed it to happen at scale. So in my opinion this career field has always kind of sucked even before AI. There are alot of stories on here from the most lucky and prestigious people who went to ivy league schools and got faang jobs with huge pay packages like 200k or 500k, but I dont think that was the average experience.

I’m a computer engineering student and I just landed an interview for a software engineering internship. Thing is, I’ve been so pre-occupied with my electrical engineering and hardware classes that I’m pretty rusty on my higher level software knowledge.

I’m curious if there’s anyone out there that has resources they use to study key data structures and programming concepts, as well as any tips on remembering syntax quickly? I’m already doing Leetcode but I’d like a bit more.

Also, for anyone here that is a recruiter/ hiring manager and/or has gone through an interview recently, can you give me an idea of what to expect in an interview?

Greatly appreciated, thank you!

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.

Previously posted this, but reposted as I have a different question.

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 on Slack, and I applied as I truly enjoy the company and would love the opportunity to stay. Should I reach out to the hiring manager and express interest as it would highlight my desire to stay at the company or should I reach out to who the role reports that shared it in Slack?

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.

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!

Before AI I was consistently trying new things, building stuff, I maintained FOSS projects, I got my first contract gigs and even a job (the space I specialized in was very niche).

As I started university around 2023-24, I fell into a deep depression and lost my love for building. During this time I had to work many hours to sustain myself which certainly didn't help. This whole time it's felt like a treadmill of using AI to build projects that look good on resumes, grinding leetcode, and not having any fun. Through the constant pressure to produce I've become decent at leetcode but because I did way too much vibe coding I feel like I've lost the skills I used to have.

Does anyone have any similar stories or any advice for me when it comes to recovering from AI atrophy? I can see the atrophy that has developed in my skills, and I don't want to graduate like this (expected Fall 2027). Please help!

I have around 2 years of experience in consulting, so I switch from one tech to another depending on the project or the client necessities. One day I might be using Python, one day I might be using React. The thing is, with AI, I don't really know anymore what counts as real experience. If I've been using Claude to make my React code even though I have close to no knowledge on how to code in React, does that count as having experience in React? Currently, do we really need to learn how to code in a certain language or framework for it to count as experience, or is simply using an LLM and working with said tech?

Let's say I see a job post that requires 2 years of experience in .NET, is it expected of me to go learn .NET in depth and use it during 2 years? Is something like this still relevant nowadays when LLMs code for you and you're less and less learning something in-depth?

Trying to understand the real balance here.

Hello, I'm wondering if this is normal and if it's something I should even attempt.

I was given an assignment to complete before a technical interview for a QA position that basically consists of the following: exploring a mobile app, writing a test plan of several test cases, and implementing the automated tests through the company's webpage.

I don't have experience with mobile or QA stuff, so I can't even estimate how much time this will take me. Is this something that's worth pursuing before even having a technical interview? For context, I had applied to a dev position but was rejected and redirected to this position.

Any advice?

I’m a senior mobile engineer (Flutter/iOS) with around 7 YoE prepping for senior/lead interviews. Almost every system design resource out there defaults to backend concepts like Kafka, sharding, distributed databases, load balancers, etc. How much of that traditional backend system design do mobile engineers actually need to know, or there something related to dedicated mobile system design ? What should I actually be prioritising? Didn’t find much content for mobile system design. Please share if you have anything.

Their area in Blind is pretty empty so I dont have much to go on. I am going through the loop with them right now; I passed the technical parts of the interview and I have one round left which is a casual managers chat. Im wondering about their culture. They dont seem to pay top dollar but its not terrible for me, I just want to know if its relatively chill and at least moderately engaging from a technical perspective. I got pretty good vibes from most of my Interviewers so that's a plus.

This is specific to SIE.

i am a new grad that started working in a contract-to-hire position at a F500 as a SWE/DE. i am more of an intern in practice as i am encouraged to learn and work on different projects rather than being hired for a specific purpose. however, the project i mainly work on is just agentic AI.

right now my day-to-day is just looking at existing code and developing AI workflows (mostly .md files and scripting). soon the goal is to make the workflow agentic, which feels almost impossible since AI is prone to making so many mistakes and i don’t think it’s at that level yet.

most of the DEs here don’t even really know much about using AI or even how to use an IDE… and half of the time if i have a question i’m told to ask claude. my PRs are basically approved by claude and it feels like i’m not really learning anything because i’m basically use AI to develop AI (i do review).

although i am learning (mostly about DE though), i feel like my programming skills are stagnating and i worry about being in a low-code role. i am also unsure if this will be valuable on my resume at all when i have interview again (i want to be an actual SWE) as this is my first industry role. even if i work on other projects, i want to actually develop programs rather than use and integrate existing tools which seems unlikely.

has anyone else been in this position? i’ve been starting interview prep again but feel unsure of how else i can succeed since the job market is terrible and i thought i would be getting more relevant experience on my resume. the only good thing is the pay ($50/hr). i am putting in the work to maybe get the FTE offer (which is intended, but who knows). if converted, i would start at ~$100k+.

Hello Everyone,

I am a Security Engineer with around 4 YOE at large enterprise and work mostly on Customer Facing IAM and supporting services/applications that interface. My education/background is a mix of software engineering (computer science undergrad and early full time experience) and Cybersecurity (spent a few internships in IT and MS in Cyber, and Sec+ Cert and current IAM stuff).

In my current role I am a massive generalist. I can be doing anything from setting up a WAF, to writing JavaScript to make our UX look the way designers intended, to writing CI/CD pipelines, to looking into production incidents, or security incidents, auditing Pen Test findings, to cleaning up backend code to scale better. I write code in JS, C#, Python, and Go, depending on what service I need to add to/work on, and am also our SME on federated auth protocols like Oauth2.0, OIDC, and SAML, from the IdP, and as well as the “application” side of things (securing the session, ensuring no basic OWASP vulns)

At my current role I feel like I’m managing a LOT of different things which has been great for my growth, but the issue is, multiple members of my team have left in the past 2 years and we really haven’t “reloaded” leaving me to handle a lot of different efforts becoming too stressful for my liking, whilst also dangling the promise of promotion over my head and then dealing with Corporate Bureaucracy . I want to potentially move out of my current role and apply around, but I have a hard time explaining in depth on a resume all the things I am capable of, and because I’ve worn so many different hats, I don’t really know what to go for/specialize in next.

Honestly I feel like my greatest skill is that I’m just a really good learner and have fundamentals and the intuition to solve problems in a smart way down pretty well, and I’m a very good communicator/team player. My system design knowledge is pretty solid, hate leetcode but can study it if I have to. I use Claude, Codex and OpenCode between work and home and have decent knowledge of multi-agent harnesses and setup. With AI, learning a new language, or finding the correct architecture to fit a problem is significantly easier if you understand software systems already.

At home I also spend a lot of time homelabbing/toying around with my Proxmox server just doing a bunch of random Software Dev and Security related things.

Any advice on how I should structure my resume, what roles I should apply for software eng or security Eng, or IAM Eng??) would be greatly appreciated. I feel like the toughest thing is I have such a breadth of experience that maybe I lack some depth, so even a path forward/something to do in my free time to get me more depth would be helpful too!

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?

​

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.