How

Woohoo. You just got into some decent school, and want to work at FAANG once you graduate. Maybe you're in this field because you're a die-hard computer or programming nut. Or maybe you're in this field because you've been told all your childhood that "tech is the future" (or more recently: "AI is the future"). Well, as someone who's approaching the finish line of my degree, here's what you need to do to succeed. Step 1: Quit and never look back. Abandon all hope. AI and outsourcing took all the jobs. Pivot to nursing, medicine, pharmacy, traditional engineering, or even trades before it's too late. Just kidding. You're welcome to do all that if you'd like, of course, go ahead. But don't do it because you're worried that CS isn't an absolutely dead field along the lines of Art History or Gender Studies. Because I don't think it is. That said, you do need to be honest about what this degree does and doesn't offer. For instance, thought getting into college was hard? Looked up multiple colleges and their acceptance rates? Well, buckle up, getting employed is 10 times harder. Anyways, on to the tips. For real this time. Tip 1: Be realistic about whether CS is something you're interested in. Are you in here for free money? Are you here to get rich? If so, maybe you could've had a better shot between roughly 2020 to 2022, and found yourself able to break into a decently paying role but like it or not, the times are a-changin'. ZIRP is over. AI is eliminating the need for juniors. And this has been translating into many CS majors - of which some think there might be too many - trotting into universities with smiles on their faces, maybe chiding a few of their classmates who've pursued less "useful" majors, only to find themselves without an offer in hand on the other end, forced to take up low-wage labor and/or move back in with parents after college, partially or totally financially reliant on them due to struggling to even break onto the floor. What interests you about CS? What interests you about this role at that company? You need to be able to have a good answer for these kinds of questions, because you'll have to answer it often. Do you have an answer to this? If you can't answer what interests you about CS, then maybe CS isn't for you. And that's OK! Tip 2: Don't rely on LLMs for everything. Ideally, for classwork, you shouldn't be touching LLMs, period. Most professors don't allow them anyway, even if enforcement may be variable in practice. If you're already using them - and you probably already are - stop using them. And honestly, the rationale against using LLMs lies not so much in the quality of their outputs - AI has only gotten much better at coding over the years, and nowadays the best Claude and Gemini models can "one-shot" many projects - but how you learn. If you're finding yourself in a situation in which you struggle to do much without LLMs, it might be a cause for concern. Personal projects - ungraded projects - are a bit more of a gray area, and I'll hesitantly concede LLM usage there might be more admissible. But ideally you'd need to know what you're doing before "one-shotting" features, or you won't learn. And crucially, you need to be able to confidently talk about your projects during interviews - what you did and why, what you learned, how you implemented features - your ability of which LLM usage might significantly compromise. You might also want to be careful not to approve anything majorly disastrous, e.g. Claude Code wiping a drive or racking up thousands in cloud computing credits, because AI agents have indeed done just that. Don't buy into the "Cluely" hype and feel tempted to use AI assistants during interviews, either. Hiring managers aren't dumb, and now know how to look at your eyes to determine if you're reading off of something, no matter how effectively you manage to hide anything on the browser level. If they probe for details (e.g. "how did you implement this"), they can sniff you out better than you might expect. I will concede that oftentimes, if you do get a job, some companies might encourage AI usage to "boost productivity". In that case, just try to read the room, and be sure you actually understand what your AI agents are doing, because you'd actually be working on production-level code and AI screw-ups - they still happen - can be monumental if pushed to production. But if you're ever in a position where you absolutely need AI to do anything and are helpless without it, it might be time to question whether this major is for you to begin with. Tip 3: CS is more than just SWE. And SWE is more than just FAANG. Colleges and universities aren't trade schools or bootcamps. The goal isn't to "prep you for a SWE role at Google", but to teach you about how data structures or algorithms work, what systems programming is, how databases work, how to design systems, and maybe some more domain-specific stuff depending on what you're interested in. A degree in CS is really, at the heart of it, what you make it. And while everyone wants to become a software engineer at a big tech company and make $200K fresh out of college, that's far from the only path, and not being able to break into those jobs doesn't mean you're a failure. Don't just apply to "tech" companies, and don't just apply to roles called "software engineer" or "developer" in the job description. Banks, pharma companies, and retailers all want people with CS majors - and not just behind a counter. If you struggle to break into any SWE field, consider IT, data analyst, business analyst, or project/product management roles - might not be guaranteed incomes today and may be more competitive, but they're at least more relevant to the field than retail grunt work. Tip 4: Pair CS with something else. So IDK if you trade stocks or watch the stock market, but people often say to "diversify your portfolio". That's because if you invest only (or mostly) in, say, tech stocks / options, well, what if the tech industry collapses and stocks go down? Or pharma, or energy, or whatever industry. Hence, why traders often invest in a multitude of stocks, so that a blow to one industry doesn't mean a blow for your whole stock portfolio. And now, during an age where the CS job market is worsening like absolute crazy, and even some of the best CS majors are struggling to secure internships during college or full-time work afterwards, doing another major alongside CS could open up more career doors, or it could help you present as a more unique candidate and signal domain expertise. For a tech role at a bank, a CS-Finance double-major candidate might pull ahead of a pure CS candidate. For a tech role at a healthcare or pharm company, a CS-Biology double-major candidate might pull ahead of a pure CS candidate. And so on. If AI is devaluating the locked-in code-monkeying, the best thing you can do might be asking yourself how you can make yourself look less like a locked-in code monkey. Doesn't have to necessarily involve "pivoting" per se, but some realism about the value of pure CS during an age of rampant automation in coding and software development might prove useful. Tip 5: Act today, not tomorrow, and be wary of applying the past to the future. "Traditional" career advice dictates that getting an internship was relatively chill and not obscenely difficult, as they pretty much just fetch coffee for superiors more often than actually doing important things, and the aim is to prepare them for full-time employment. However, nowadays, getting experience in as early as possible might be more important. Internships - really in any white-collar field, but especially SWE - are not easy to get, and significantly harder to get compared to what was often seen as a past "golden age" (2020-2022). And from (the summer after) year 3 to year 2 to year 1, they get harder to land. So at least try to get an internship, I kid you not, starting (the summer after) freshman year. If you can't land an internship despite your best efforts, that's more forgivable as a freshman than a sophomore or junior, as you'll still have 2 more chances (or even more, if you account for less-common fall/spring internships/co-ops). Leverage connections if you can - they're more important now in opening up doors which might've been locked, and the value of networking might be another difference between the "traditional" recruiting meta vs. now. Talk to your professors outside of class. Sign up for those online webinars companies host from time to time - even if they might not seem valuable, one of my classmates secured an internship at a company one summer while I did nothing, and one of the factors which led to his success was consistent engagement with one company's webinars again and again. Attend hackathons, and aim to participate in them rather than necessarily "win" if the competition factor deters you from engagement. Do all of these during college, and you'll be better than me. Scope out opportunities through a variety of job boards, or sources. Some are better than others, I'd say. Prioritize roles published within the last 24 hours, ideally less. Try to look at some every weekday between: * the start of fall semester, or a week or two before (e.g. August), until Thanksgiving break. Won't give out "a set number per day", since I know from personal experience that some days can be rougher or more tiring than others, but try to go for about 25 per week if you're a 2nd or 3rd year, though maybe tone down to somewhere near 10 per week if you're a 1st year. * from Thanksgiving break to around New Year's, you can honestly chill out a bit, since applications themselves do slow down around that time, so that you can work on finals and not absolutely stress out, e.g. maybe checking every other day instead of every day. * from around New Year's through spring break to early May, there's a smaller and more obscure wave of openings. Typically none of the absolute hot-shots, but not nothing either. (My mistake during my own sophomore year was giving up around January, conceding that "internship recruiting is over". Avoid this, and keep applying down the road. The next internship I got was during May. It ain't over till it's over.) No internship? Some other ways you can get experience without an internship: * Personal projects (ideally non-school, well-understood and articulated, and maybe even with end users): can go on resume * Undergraduate research: can go on resume, and can help boost graduate school applications * "Idea labs", if your school has one (mine does) * Interview prep: LeetCode can help prep for OAs or technical interviews; if formidable, start with Blind 75 or NeetCode 150 - this is something I started a lot later than I should've. * Study or use things that might not be directly covered in university course material, e.g. learning C++ if all your university classes are in Java, working on a Cloud cert, learn about distributed systems (e.g. Redis) By the end of freshman year, you should have, at the very minimum, one major accomplishment of some kind, that you can talk about with hiring managers or professors. It doesn't have to be curing cancer, but it shouldn't be nothing (or only school projects everyone else in your class does). If you don't have anything like that, you'll be at a severe disadvantage when recruiting. The absolute last thing you need to be doing is "coasting" all freshman year: no drilling, no building, no networking. If you're pursuing SWE, ideally you'd also have completed the Blind 75 by end of freshman year and the NeetCode 150 by end of sophomore year. And what if I fail? (Assuming "failing" is defined as being unemployed or underemployed immediately following graduation) Then unfortunately, you might legit be better off doing a trade or nursing or whatever. Perhaps that might be ample deterrent from failing. But it's not always in your control, and even some decent candidates fail and get unlucky. Sometimes, during hiring, it might actually just come down to dumb ol' luck. Just think about it. If everyone could successfully break into FAANG or make $100k fresh out of a 4-year college by following a list of steps, "FAANG" wouldn't even be an acronym. Even well before the emergence of generative AI, COVID / the remote work revolution, ZIRP, or any of the more fueled presidential elections, Google has a 0.1% admissions rate. If it doesn't seem fair, perhaps it's because nothing was fair to begin with. (A Master's can be another option, but a quite expensive one, perhaps wisely avoided unless you know exactly what you're doing. They're great for giving you the elevated credentials to break into certain specializations, like data science or machine learning, but if you've been struggling to land a job, there's no guarantee a Master's is going to give you a job unless you actually put in the effort to get one.) What might be the most important advice is not to act like just having a CS degree (and potentially GPT-ing your way through it) means you deserve an office job. Because in today's day and age, especially in a world where virtually everyone has access to AI agents that's probably better at LeetCode, companies care more about what you've done rather than what degree you have. Good luck. Lock in. P.S. I handwrote this 100% - not even 50% or 99% - without touching any LLM even once. I just like spoopy formatting. (And no, I'm not trying to sell anything either.)