Almost always have to revise or completely scrap AI outputs when I use it for content and design help for the podcast / newsletter

Very different experience from when I was using LLMs for a chrome extension side project I worked on

If you do all the above, you'll increase your chances of getting a return offer dramatically. Good luck this summer!

4. Let people know - Don't work in a silo your whole internship. You're limiting yourself if your internship manager is the only person who can unblock you or knows about your work. Take the time to plug into the team and share updates.

3. Take initiative - If you did (1) and (2), you should have some spare time outside of your main project. Use that time to take on extra work or propose improvements on top of your original project.

2. Quality code - Don't just move fast though, your code needs to also be solid. You can measure this by how many revisions it takes for your code to land. You should aim for your code to land with 0 or 1 revisions by the 2nd half of your internship.

1. Move fast - Your project should be unambigious and not too complex. They're just trying to see if you can unblock yourself and make progress fast. If you can get your project done in half the internship's time that'd be excellent.

Will start sharing more about the hardware side project if you want to follow along, have some stories about flying to China last minute and learning about how manufacturing works

Had a lot of fun at the event and brought Ricky along too since he was UPE president back in the day

If any other college CS clubs are interested in hosting something similar DM me and maybe we can work something out one day

Often the bottleneck for (2) is in how many people there are to delegate to and how hands-on you need to be in guiding them.

I do wonder what'll happen to the "coding machine" archetype of more senior engineers. Their outlier code output will be even crazier...

2. Resolving ambiguity, determining the most impactful direction, and scaling yourself through others - For this type of work, it'll become easier to delegate and scale yourself since you can pass more to AI rather than more junior engineers

Senior+ engineers understand that most scalable impact doesn't come from simple execution

Scalable impact comes from:

1. Writing high-leverage code that no one else can - Not something AI will replace in 12 months. I'm referring to specialists who do deep, domain-specific work