== June 3, 2026 == == Trimmed/Redacted partially on July 16 == hii, if you're reading this, you probably know about me. in short, im a misfit who escalated from a nobody, to someone who is - pretty well known in the indian tech (+twitter) sphere - in contact with multiple deep tech startup founders - works as a researcher (ml-systems) at LTRC, IIIT H and a software intern in a UAE based startup. (edit: i left that startup, i have 5 more offers from hand, mostly SF based ones) all that in first year of college. before you guess anything, - im pretty dumb - come from a remote town in north bengal - parents are far from being techsavvy hence you can safely rule out elite schooling or parental influence for what i did in one academic year. at the time of writing this, im travelling towards hyd to finally work onsite (+ will be attending bangerlore v5 this weekend in blr!) im proud of what i did in 12 months, and simultaneously scared of what's coming next. BUT, i have no publications yet + no shipped product with real users. no proof yet that any of this compounds into something meaningful. what looked impressive to you probably just means your bar was low, or mine was the only story you found. hence, read what i did as a starting point, not a destination. im still in the middle. i might not make it. here is my timeline: june 2025 1. read fluent python end to end, and wrote and ran all the code manually alongside 2. did dsa problems from neetcode150 (upto graphs) 3. wanted to learn c++, didn't understand pointers and references; asked claude to give me practise problems, and real life uses and patterns. wrote them down: 4. referred to winterdev's articles and pre historic code commits of matter.js to learn how to make a physics engine. understood how to write basic c++ by following learncpp, and learnxinyminutes.com. 5. felt tired doing leetcode all day, felt that i need to rejuvenate my love for programming - opened up daniel shiffman's playlist, and started building: - fractals - cellular automata - boid simulation - shaders - perceptrons https://github.com/datavorous/explanations july 2025 6. participated in an online hackathon after a friend forced me to take part, speed ran my way into learning fastMCP and how to work with nginx. won a prize in the first round. https://github.com/datavorous/puch-mcp-hackathon 7. worked on making a mini browser renderer after being trolled by a hater on twitter https://github.com/datavorous/toy-browser 8. built a reddit monitoring tool for marketing but got ghosted aug 2025 9. built a hybrid falling sand simulator + neofetch https://github.com/datavorous/dunefetch september 2025 10. saw sebastian lague's videos, and thought to make a ray tracer - read RTIOW book and started making one in python https://github.com/datavorous/tinytracer october 2025 11. wrote a garbage collector in python https://github.com/datavorous/garbage-collector-py 12. started doing codeforces seriously - daily USACO problems - implementation/greedy/math/construction tagged problems on CF - leetcode revisions from neetcode, and hellointerview - practised problems from tle eliminators - gave all the contests, upsolved every problem after that - wrote code on paper while being in class and not listening to the lecture 13. took part in hackathons and learnt javascript (react) at a rudimentary level - didn't understand anything deeply - lost in the hackathon 14. kept doing cf till mid november november 225 15. made a chess engine backend in python after reading chess programming wiki https://github.com/datavorous/touchgrass 16. built a tinder for my college (don't ask why) - learnt about new algos and how tinder/binge work internally - got interested into machine learning and optimizations - learnt how auth works december 2025 17. college coding club's open source event: took part in it, and worked on a quantization library - implemented all the easy algos in python after understanding it from pytorch's documentation 18. started rewriting my ray tracer in c++, aim was to make it faster and render more complex scenes ended up studying about high performance computing - why problems are generally memory bound and how to structure a program to extract max performance out of it 19. dec 27, collected all the projects I made in a year, and made a year wrap - posted on twitter, reddit and x. post got removed from r/developersindia after 30 mins. someone saw it, and dmed me: "Hey Sagnik, great projects! Want to take it to the next level?" I didn't understand what he meant, said yes sure, and he told me to book a call on calendly. I picked jan 9 - the last one. jan 2026 (new year!) 20. wrote down what i want to do this year: 1. land a serious internship (startup or research adjacent) 2. maintain two flagship projects 3. learn about memory models, cache behavior, allocators, profiling tools, and parallelism 4. reading and implementing from papers without crying 5. eat 3 times a day (lmao yes?) 6. post write ups about my failed experiments on X/HN/Reddit 7. meet/network with cool people 8. i don't want to poison my checklist by mentioning anything about uni - but i got to take things a little bit seriously and wrote a blog on how I optimized my ray tracer 21. got on the before mentioned call, he was a cto of startup who work on risk moderation for buymeacoffee. i said sure. got an assignment to make one at small scale. - learnt basic regex - learnt how to make APIs, use postman - figured out fuzzysearch, caching, routing prompts to heavy and lighter LMs etc. - fault tolerance and logging - tested on actual profiles he was impressed, got an internship. low pay as per my current standards, but I was happy ^ - ^ 22. worked on the codebase - I can't reveal much but I worked on a lot of scrapers (read blogs from Exa, and similar stuff for information retrieval), and classifiers. understood how to deal with Jira tickets (lol), handle merge conflicts and attend meetings 23. couldn't get over the high i got from optimizing my ray tracer - my python version was slow af, numpy could make it faster then I thought, let me try to make numpy from scratch opened the codebase got fucking scared and went to chatgpt to suggest me - something with vectors as the main data format 24. started working on spheni - my biggest project of first year - read 3-4 research papers, utilized gemini to help me understand them - learnt to implement papers, make modifications and measure modifications - read cpumemory.pdf, and jason turner, got introduced to hpc - faced difficulty with build systems Feb 2026 - implemented flat and ivf search after lots of struggle and google searched and claude prompts to help me visualse memory layouts (voronoi cells) - used copilot to add a python extension - built a lib, pushed to pypi made a beautiful demo (dynamic image search) and posted on reddit, x, hn and linkedin. - gained 100k impression on linkedin, 300k on reddit, 150k on X. - got 2 inbounds - h2loop.ai's CTO and one another 25. got bored with all these, made a small chess engine in 8 hours and posted everywhere again - viral again + front page of hackernews. - 1.2k followers in a week on X - didn't get offers, but requests to work with fellow programmers on their chess related projects - 26. h2loop was looking for an intern to do IR and inference - I chose inference as it sounded cool. Speed ran my way into learning about GPUs and what exactly prefill/decode, kv cache, spec dec were. Didn't qualify in their technical assignment. Other offer didn't suit me, felt too generic. 27. Was enraged that I couldn't qualify, I followed karpathy's llama2.c, and built a simpler version in C. 28. Added PQ to my vector search lib. Around that time, saw a tweet that they are looking for interns to work at LTRC on edge ai, information retrieval, language models etc. i applied under the post for information retrieval. that guy told me to send my resume. impressed - he told mail the prof after adding his name. 3 weeks silence. 29. prof got on call, asked me if im really in first year - i said yes, then we directly went to discuss what i would like to do. I said ml sys (cause I was angry at me for not qualifying my last technical assignment) 30. got bored with my current internship, resigned. march 2026 31. read beej's guide to c, modern c, build systems, relied on man pages, re built linux tools without any help 32. networked with people by going through their work and asking them questions 33. polished older projects, cold emailed at 3 startups. 1 soft rejected, 1 didn't reply, another scheduled an interview. 34. on screen interview on c + memory + dsa, technical assignment with harness enginnering. qualified. got on a call with the ceo - projects felt too much of higher abstraction - i declined. pay was more than last time. april 2026 35. got accepted for summer research officially. 36. studied about Inference, gpu programming, how LMs work at a surface level 37. got a new offer to work on hw/sw codesign - analog circuits (accepted it). model distillation, harness engineering yada yada. i was contacted by the startup. may 2026 38. studied about gpu programming, gpu arch - did initial work for gpu cluster setup for the lab. 39. prof told me to work for a different project alongside the distributed training one - edge ai. snapdragon npus. gemma4, LiteRT. Spent a lot of time analysis how LiteRT works, NPUs and how SoCs work. Wrote articles and published on X. niche work. made good connections. 40. worked on building a retrieval layer for PDK files, improved the distillation pipeline by implementing papers, built static analysers. 41. built a tool to analyse computational graphs and figure out what causes fragmentation. june 2026 42. onsite work time. waiting at the station. dms drop: "hey! would love to talk sometime!" fair enough. I had shared a tweet a few hours back with a massive list of links for my "side quests". after a 2 hour talk on my internet in DL x proteins. i got invited to lagrange point and bangerlore. very cool! got introduced to the ceos of popvax and altcarbon - then they invited me to their labs, and said that they'd introduce me to more people. currently im in a train. work stats tomorrow.