Most of their job is about people, leverage, and execution. It's not a sit and think job, it's mostly 1:1s and coalition-building
Theyre also utilizing LLMs to augment themselves. And are getting more data, from off-record convos to reports from trusted smart colleagues who used an LLM to refine their intel
they said 90% of it was spent on ideation and exploration
they didnt specifically mean they built a wordle clone, just a game like it. if they wanted just a wordle clone, they wouldve gotten one within a few minutes of using codegen tools.
> I estimate that 90% of the time was spent thinking about the product, directing the AI, and testing
In other words 90% of the time was spent in the proompt-test-proompt loop. Not ideation and exploration.
> they didnt specifically mean they built a wordle clone, just a game like it. if they wanted just a wordle clone, they wouldve gotten one within a few minutes of using codegen tools.
If you really believe that I'm not sure what to say other than: have you tried to use an AI to make a full wordle clone? (not just the checking logic, or rendering - the entire thing)
yes, the quote is what I'm referring to, directing the AI is part of it, people use these to quickly brainstorm and refine ideas. I'd be more charitable and wouldn't hastily assume it was some skill issue, especially them being a principal engineer
Is there any source for first-hand specifics of what she does?
I used to argue in reddit (same username as my HN) basically calling Musk a fraud and Gwynne Shotwell being all the brains 6 years ago, but I've since changed my position after seeing engineers in spaceX give props to Musk at podcasts, twitter, and various interviews.
CP just teaches some familiarity with DSA/algorithms, and there's much more to perf than DSA. Even assessing algorithmic performance requires real benchmarks and profiling, while the complexity analysis people do in CP disregards other factors like hardware, architecture, format, and other abstractions. Squeezing perf via DSA is much more easier/straightforward, people don't need to grind CP to learn that
I guess lots of people find
him interesting (see HN guidelines)
Charlie (and Buffett) are often recommended here for their mental models as their approach to investing and finance are very transferrable in startups/engineering. At the end of the day, large scale software engineering is mostly about managing risk, strategy, and corporate finance/value. Often, Poor Charlie's Almanack is recommended by my top Staff+ colleagues.
Most of their job is about people, leverage, and execution. It's not a sit and think job, it's mostly 1:1s and coalition-building
Theyre also utilizing LLMs to augment themselves. And are getting more data, from off-record convos to reports from trusted smart colleagues who used an LLM to refine their intel