What I learned from quitting my SWE job to getting a T10 CS PhD offer in 2026

I first became interested in CS research in the spring of senior year (sp2024) after learning about neural radiance fields. This is quit late to start doing research and even though I had a job lined up, I found SWE boring and not for me. Like many, I floated through undergrad and fell into the rat race of chasing internships, taking as many hard classes as possible, and trying to find a high paying job. In the long term, this can be boring, unfulfilling, and can lead to extreme burnout + unhappiness.

#1: You only have one youth, you don't have to play the rat race

When I discovered research in a field I liked, spending time in it was natural and fun. I worked a swe job from spring 2024 to spring 2025 and quit to apply for a masters. Even during work I was spending time on research: reading papers, running experiments. I never really cared about my performance reviews - the job was low-bandwidth on learning, the tech stack was old/repetitive, it wasn't cutting edge or new and I felt myself becoming a soulless, lifeless husk of a person. I used the job as a temporary income to fund my masters, and when my masters began, I solely focused on research and phd apps, which became the most enjoyable time of my life.

#2: Working with friends on something fun is truly meaningful and is highest bandwidth of learning

I recall waking up, going to lab, and working the whole day and yapping about ideas with other graduate students about what ideas we thought were worth pursuing. I would get home at 3am, sleep, and do it all over again. The days fly by and you learn an incredible amount while having fun. The best researchers are the people who live in the present: they enjoy the process itself. I believe everyone has a purpose, you just have to find it and explore it with the right people. When you do, you realize you learn at a rapid rate. You pick things up instantly because you are genuinely interested in learning/using them.

#3: It's never too late

As aforementioned, I started doing research in my 4th year of undergrad. I've met multiple Korean students who went to undergrad, then did military service, but still came back to do phd because they like it. This is not a survivorship bias situation. In research, your age does not matter. While it is advantageous to get started early, doing real science is what really matters. If you want to conduct science and contribute to a field of knowledge, it is never too late.

#4: Deep intellect in a subfield is infinitely valued. It only takes 1 good paper

When doing graphics/vision research, I felt like there were a few names everyone mentioned. When I pivoted to robotics, the same thing happened. I realized how small the world is: there are a few dozen names and labs that everyone talks about. When those names come up, people usually only recall 1 paper from a person which was drastically impactful. While there are those with multiple astounding papers, if you focus deeply on an important problem and make a meaningful contribution, it gets noticed. Robotics researchers at frontier labs + neo-labs are paying easily into the 7 figures for PhD new grads. If you develop a knowledge at a subject few know about but is important (many opportunities like this exist in CS research today, especially AI), people will throw huge money to hire you, and your skills will always be in demand.

#5 The research world is small. Connections matter

Academia is heavily based on rec-letters. PhD candidates are 90% weighted by rec letters, and this definitely spreads into hiring. Because industry research is heavily interconnected with academia, job offers come often through nepotism and word of mouth. You can flunk a research interview but if a researcher within a company likes your work, you can easily be hired. I recall an interview where my friend alreadu knew he was going to be hired because his paper was appreciated by the head research scientist.

#6 Standing out in a small world seems easy, but is actually very hard

I applied to 16 schools and interviewed at half of them. In PhD interviews, a professor usually interviews around a dozen students and accepts 3-4 (assuming a yield of 50%). I kept noticing the same names in the interview email list across all my interviews, and I was getting mogged by the same 5-6 people. During the Phd visit days, I saw the same few people! In the end, the top 3-4 students in a subfield get almost all the T4 offers: Stanford, MIT, Berkeley, CMU all accept the same pool of people.
What this means: It's hard to stand out, but once you get to the cream of the crop, all the offers will start rolling in. There is an inflection point where everything skews your way. Many recall the same happen with SWE jobs: once they land one job, all the sudden more recruiters / interviews start lining up. The demand for the top 1% is extremely high, but getting there is extremely hard and requires hard effort and talent.

#7 Research and engineering are heavily interconnected. AI made engineering easy, and research has accelerated. Taste is what still matters.

Having good research skills is knowing how to search an intractable space for insight. Good engineering skills allow you to implement and test any hypothesis' you might have. As a result, the best researchers are already extremely good engineers. In 2026, AI agents like claude code and codex are incredible efficient at implementation, AI research is only accelerating. This has made research incredibly exciting, as you can parallelize dozens of experiments at a time. Many times I find the challenge is not "Can Claude do it?", but rather "How can I frame the problem in a way that Claude can solve it?" because claude will solve it. However, these agents still can not replicate the high level planning and research taste of the best scientists. I believe this may not be the case in the future, and the research itself may be automated soon enough.

#8 Live in the present

While it may sound sexy to get into a top PhD program like Stanford, publish a groundbreaking paper at a top conference, then landing a 7 figure salary at a frontier lab; true happiness is not from these milestones but actually the little things like talking late to your labmates about what approaches you believe in, checking your experiments for a possible bug, or trying to interpret your results. The process of research can come with spikes of joy when a milestone is achieved, but there are often months and years when nothing happens. If you enjoy the process itself and make yourself really live in each moment, life always has light at the end of the tunnel. However, don't be fooled. The meaning of life is not to reach the light at the end, the meaning of life is approach the end. The journey is always more important than the destination