I asked around my network recently - in the last month or two basically every large company has put in spending limits per engineer. Curious what their S1 will look like when they go public.
https://arena.ai/leaderboard - I’ve found this company is a pretty good ranker - not sure their exact methodology but during day to day programming with Claude / gpt models I’ve felt qualitatively what they report
When I first graduated I read a bunch of tech focused books: they’re all helpful but I think practice and learning from more senior engineers is the most effective road to mastery! You can probably get away with not reading any of these books if you have good coworkers :).
That being said, these have been my favorites:
- designing data intensive applications (a great way of understanding systems + the basics of SRE)
- the senior engineer (I love the prototyping process he lays out)
- the effective engineer (lots of good gems for approaching prioritization)
- debugging (by David agans)- a great resource for a formalized debugging process if you don’t have one
- on writing well (I’m halfway through this, but it has been indispensable for writing tickets + messages at work)
I think these groups are out there, but unfortunately they are informal (not listed on the web or through a company), and also are not for a beginner level.
For me, I’ve been learning how to surf and cook. I found at an absolute beginner level no one really wants to go out surfing with you, or do dinner parties. I did find once I showed enough commitment, and reached a beginner-intermediate level, more people were willing to join me in learning, and form informal learning groups.
Therapists are trained to help and give you custom things to do based on what you need. I found one that gave me a lot of structured “assignments” and questions to ask myself and I’ve never felt better than I do now.
It's funny how hyped up stable diffusion is on HN right now: reminds me of when style transfer first started making it's rounds in 2017. https://news.ycombinator.com/item?id=13958366
I think as technologists we want to think that code can "solve" some of the problems in the art world... but I think we still have a really, really long way to go.
I tried to get style transfer adopted at work (worked at a creative technology firm in NY) but frankly I think deep learning methods for art generation tend to be really unpredictable, which make them pretty hard to use for professional applications. Imagine deploying production code that only worked 85% of the time... would be a nightmare. I felt, and feel similarly about deep learning approaches to art. They're just so finnicky and unpredictable, for example, add a single extra pixel to that example in this article and the output would look completely different.
Either way, cynicism aside, stable diffusion is awesome :).
As someone who took their first software engineering job as a junior during covid, I have to say I definitely struggled to learn and execute on tasks in a way which I know I wouldn't in an in person setting.
I found asking for help as a junior is definitely harder when you don't have people around (walking up to someone's desk vs slack message with ~20-60 minute delay then zoom call): and I often found myself blocked on tasks.
I found learning is generally harder remotely for me as well: the sheer amount of information + resources + help you get from serendipitous conversations with other engineers should not be understated. It's the same reason people got so angry over paying so much for remote university: it is objectively a worse learning experience.
I think this is just my personal stance: but I think in my perfect world I work in office for the first 5-10 years of my career to optimize for learning + relationship building, and then once I get more senior (or have kids) I transition into either hybrid or fully remote.
I’m a programmer, and my dads a doctor, and for ten years I’d always tell him that something like 20 questions could do his job.
After about 5 years he did this graduation speech and in it he referenced that: “yes, AI is getting great, your phone is a supercomputer, but the truth is that a computer will never be able to hold the hand of a dying patient and tell them it will be all be okay.”