sadly with all the labs benchmaxxing I feel like you just have to try the model for a while to really evaluate how good it is, especially for each individual use case
100%, if someone from a no name school does well on the interview I’ll happily recommend them to be hired. However idk how HR filters resumes, and they likely use certain heuristics to try and minimize false positives
Do you need to do tier 1 and 2 work before tier 3?
If they are structurally different, and there’s a way to train people directly into tier 3, then it doesn’t seem unreasonable to automate t1 and t2 as from my experience the vast majority of the tickets are either simple or repeated workflows. Taking the idea to the limit, you’d automate all tiers, and have the ai escalate to the individual teams within the company for any truly meaningful edge cases
I feel sort of the same about SWE, which is much more complex, but juniors can ostensibly grow into seniors with AI
I joined a new company 6 months ago. I interviewed at 16 companies and got 5 offers from a mix of ai cos / big tech / trading firms
Background is SWE at an AI co that's in the news sometimes
It felt about the same in terms of grind effort from my last search in 2022. the main difference was ai companies cared a lot about your understanding of agentic systems and harness / context engineering, and had much more practical rounds with less leetcode (usually 1 medium). More legacy firms (finance / some big tech) still expected you to solve 3-4 leetcode medium/hards throughout the process
you can get 1% as a founding eng at seed, and its not uncommon for a 5 at 50 seed
dilution is also dependent on the opex, founder negotiating power, and growth of the company. There are startups raising monster rounds at <5% dilution a round
If you are an employee however and your co is raising highly diluted rounds with poor growth probably best to jump ship
Even if not, there's pricing pressure between chat, gemini, and claude. The products seem to be comparable for laypeople which is why OpenAI has been investing a ton in their memory feature to try to lock in users
It's unclear to me how this will play out because LLMs don't have the same network / platform effects as the other examples (Uber / Facebook), nor is there one dominant LLM that is overwhelmingly better than the competition for consumers (Google). There's overwhelming competition from the open source cheap models especially for the lower-mid intelligence use cases
in rare occasions it might go the other way around, like someone who has so much experience they dont need a pretty resume because their work speaks for itself
New grads are the biggest offenders of the resume slop
I'm very optimistic. I think most diseases being cured, extended lifespans, physical abundance, and zero poverty are within reach in our lifespan, due to technology.
I think humans will be about the same in terms of happiness, due to how quickly to acclimate to our situation. But they'll look back on us with shock at how we ever lived like this!
obviously vol is not the end all be all but one of your main advantages as a startup employee is access to the insider info and being able to walk away
it seems like Chinese people have much more faith in their govt than Western countries, and subsequently trust them more in distributing the benefits of AI (in aggregate ofc)
How much of this is due to AI vs. the government and corporate structures in society? (Saw elsewhere that Chinese people were also much more optimistic)