ml infra @nvidia (2x), prev @slackhq & @figma, cs @ ut austin ‘27 love learning & all views are my own
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there are two phases to every internship:
1. eating all of the protein snacks in the office
2. stomach problems
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unironically, i mostly learned how to code through leetcode at first
without it, my systems classes would have been much much rougher to go through
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everything is dsa
everything is a data structure or an algorithm
There is only one thing that is tough to master in tech, and that is DSA. Everything else, from system design to machine coding, is just a joke compared to it. Focus on DSA if you are starting college. All other skills are much easier to learn.
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instead of feeling the need to turn every problem i have into a startup idea, often detracting away from solving the original problem, i’ve loved using ai to create personal software
some examples:
- a site for learning how to sing usetoner.com (the only publicly accessible one haha)
- an app where i can upload contacts from my phone, and keep track of the last time i reached out to selected contacts to help
me keep in touch
- personal email agent (self explanatory haha)
- (currently in progress) my own cloud agent control plane with persistent sandboxes, so that i can code from my laptop, my phone, with my voice, from anywhere.
- a to do list app to help me keep track of the growing stack of things in my life, with integrations to my calendar & email hopefully soon!
doing these for myself have been huge productivity unlocks :)
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but overall, instead of waiting for an existing platform to do what i want, i can just go and do the thing for myself
don’t like a particular user interaction? do it my way
don’t like a particular experience or feature? do it my way
don’t like waiting for an integration? do it my way
so on and so forth
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this is a really interesting discussion for people like myself, who haven’t had a single professional experience without the presence of llms.
writing code use to be a problem in the way of solving problems.
for people who enjoyed writing code, this was awesome.
but i’ve really enjoyed how i’m able to focus more on solving problems WITH code
very interesting times
My software engineer friends say AI has made their jobs mostly grunt work. The models automate the parts they used to enjoy, leaving humans with the hardest, least enjoyable parts of the job.
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if there’s anything that is difficult to estimate, it’s how long it takes to write a design document
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shooting into the abyss @openai re: the gmail connector
- if multiple emails are connected to an account, the UI doesn’t properly show which account the email came from
- replies don’t draft the reply to the original thread it’s in response to
🙏🏾
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as promised, notes on the units of compute are live :)
was supposed to do a homework assignment, but got caught up and spent a lot of time the past couple days on this after taking a closer look into the work @modal is doing in this area.
still have some visuals to add, but core content is essentially done.
tezock.com/bookshelf
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planning on spending some time diving into:
- computer architecture
- gpus
- machine learning
- reviewing operating systems / file systems
- observability
for the immediate future after this, but i feel like im finally hitting that point of, for the most part, understanding a lot of the core design decisions i sought learning when i first got interested in infra.
onwards and upwards!
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