Peter Yao

🚀 🚀 How I helped build a rocket as a software engineer 🚀 🚀 Full Article: https://lnkd.in/gFavf3eY Last year, Shawn Wei Chew and I had the amazing opportunity to serve as software leads for our school’s rocket team, Rocket Project at UCLA. We wrote code for a hybrid propellant rocket that reached an apogee of 19,200 ft, making it the most successful flight in our team’s history. Coming from a traditional SWE background, we didn’t know what to expect, and from our first outing messing with microcontrollers, multi-threading & communication protocols - we’ve learnt tons along the way So we wrote this article hoping that it would be helpful for prospective club applicants, future batches, or at the very least, interesting to the average reader. Enjoy! Acknowledgements - this article (and rocket) would not have been possible without: • The larger Rocket Project organization, who helped build every single other part of the rocket from scratch that was not code — to me, software is tremendously easier than engineering so I don’t know how they do it LOL • Shawn, my fellow co-software lead and one of my best friends, who helped review and proofread this article. • Angela & Yifan, our amazing electronic leads who helped read this article and put out countless of fires when Shawn and I couldn’t • Our two other software leads who helped build this software system with Shawn and I • My wonderful friends who I roped in to build the web app with us • The electronics team, who were all extremely fun to be around and helped us figure out the hardware side of things so I could just write code

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𝗧𝗵𝗲 𝗯𝗲𝘀𝘁 𝗔𝗜 𝗰𝗼𝗱𝗶𝗻𝗴 𝗹𝗲𝘀𝘀𝗼𝗻 𝗰𝗼𝘀𝘁 𝗼𝘂𝗿 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿 $𝟲𝟬𝟬 𝗮𝗻𝗱 𝗮 𝗺𝗮𝗿𝗿𝗶𝗮𝗴𝗲 𝗮𝗿𝗴𝘂𝗺𝗲𝗻𝘁. Our VP of Engineering, Xiaofan(James) Luan, was supposed to buy his wife a Dior bag for their anniversary.  Instead, he bought three Claude Code subscriptions and spent the holiday trying to cross-compile 2 million lines of C++. Every fix on one platform broke two others.  $600 later, the only output was "git reset --hard" — and a very cold dinner table.😂 "Make it compile on Windows" is a trap. The real goal was "compile everywhere without hacks" — no AI is going to figure that out for you at 2 am. What worked: constraints before code, review tests not code, bottom-up, one layer at a time. Same task, two days. Then he ran six parallel Claude sessions across three machines with git worktree. The bottleneck stopped being intelligence and started being how fast one person can alt-tab. AI solves exactly the problem you give it. Engineering is in knowing which one to give. His wife is still waiting for that bag. Full story: https://lnkd.in/gtsW_Wvk ——— Follow Milvus, created by Zilliz, for everything related to unstructured data

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If you're a Senior Engineer looking to move up, the next role will likely be a Staff Engineer. And in this guide, Shruti shares tips from her own experience of getting promoted to Staff Engineer at PayPal and Slack. She talks about what Staff Engineers do (and how it's different from Seniors), why you might not be getting promoted, and how to take that next step. https://lnkd.in/g58dnFEG

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Advice I would give to a Junior Engineer just starting out if I weren’t afraid of hurting their feelings. (Based on my experiences from Jr -> Sr. Engineer during my last 8 years at Amazon, Google, Microsoft & Currently Meta) [1] Getting interviews is its own skill Do not only focus on solving problems. In this market, getting noticed is often harder than clearing rounds. Treat visibility as a separate track: polish your LinkedIn, write a focused resume, and actively chase referrals instead of only applying on job portals. [2] Referrals multiply your chances A lot of shortlists happen through internal referrals, not cold applications. Build relationships with engineers in target companies, show them your projects or open source work, and then ask for referrals with a clear, short pitch and a specific role link. [3] Build a profile that actually stands out Before dreaming of big switches, spend a year making your profile hard to ignore. Things that help: internal awards, top performer tags, company hackathons, meaningful ownership in your current project, cloud or tech certifications, and visible impact that you can list on resume and LinkedIn. [4] For freshers: first get into the industry If you are about to graduate with weak projects and basic DSA, the first job is the hardest jump. Aim to get any solid software role first. Once in, keep upskilling in DSA and projects and switch after you have some real experience. [5] In college, use a simple priority order If you are still in college, this is a practical stack: • Keep a decent CGPA so you do not get filtered out. • Practice DSA regularly so you can clear online rounds. • Build around 3 serious projects in the tech area you actually like. System design can stay basic at this stage. [6] Development and DSA should support each other Do not rely on DSA alone. Pick one tech direction like full stack, mobile, ML, or DevOps and build real products. Try to integrate the logic and patterns you learn in DSA into these projects so it all feels connected, not like two separate lives. [7] Open source and global programs are serious cheat codes Contributing to real open source projects and getting into programs like GSoC or similar fellowships can lift you out of the crowd. You get: tougher problems to solve, strong resume lines, global collaborators, and people who can later refer you in top companies. [8] Stop treating Netflix clones as “projects” If your projects look like everyone else's, recruiters ignore them. Move from tutorial clones to things that solve a real problem, have real users, or integrate interesting tech. Even a small app with a few hundred real users beats five copied UIs. [9] Consistency in DSA beats intensity Two problems a day for a long time will beat random 10 problem bursts once a week. Choose a sheet or roadmap, stick to it, and build a routine you can continue even when work or college is stressful. Continued in COMMENTS !

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Everyone is hyped about AI. Companies are hyped about AI. Many people are thinking, “Why do we need juniors if AI can do the work?” But the real fact everyone is ignoring is this: Who will become the next generation of senior developers if we don’t have junior developers today? The impact of AI might not look harmful right now, but in the long run, we may not have enough strong senior developers, because many companies are not focusing on the importance of hiring and growing junior developers today. The biggest damage AI has already done is this: it has broken the junior-to-senior developer pipeline.

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