To be clear, I aimed to avoid prescribing certain routines through most of the book. I wanted to basically provide a knowledge foundation for readers to evaluate routines or create their own. So instead of saying eg you should campus board, I try to explain that power has to be trained separately from max strength if you care about increasing power

I was ready to self publish but found a publisher who was interested. I had to make some changes to make it more readable, but you might have luck approaching publishers yourself

If the gripe is with processed foods containing protein, then sure maybe there's a risk compensation argument, but personally speaking I buy Halo Top when I'm craving ice cream, not as a way to avoid eating chicken.

I also imagine that the target audience for these products are people who are relatively active and in that case the ideal protein consumption numbers are generally accepted to be significantly higher than the 0.8g/kg cited in the article.

EDIT: After skimming the paper, I don't see anything immediately wrong with it. But there are some important nuances to note: the subjects were all fasted and given milk protein (casein in milk protein is known to take longer to absorb than pure whey protein which is a popular choice for these studies), and the measurements were made after an hour of exercise. This would skew the results towards more protein sensitivity than in normal settings where a person is pretty much always somewhat well-fed and not always eating after exercise. This is still encouraging because the results for post-exercise protein metabolism have still indicated a much lower limit than a 100g dose. Their report that oxidation rates didn't increase significantly is also notable since the belief has generally been that excess protein is oxidized and burned for energy instead of being incorporated into muscle. However, it would've been nice for them to include a 50g group as well to see if the dose-response relationship was really still linear between 25-50-100

Ultimately, this result seems encouraging for increasing post-exercise protein consumption for muscle gain, but we shouldn't discount the fact that the subjects were fasted before exercise. It would be interesting to see this study prolonged over the course of a day with further protein ingestions to see if the area-under-the-curve of muscle protein synthesis would eventually equalize in both groups, or if the larger immediately-post-exercise dose made a lasting difference. Existing research seems to not indicate such an "anabolic window". I might speculate that there is a daily limit for protein ingestion, but it doesn't matter if you hit that limit in one meal or five. That said, I have previously come across a paper that found medium-sized, spaced out doses to be more effective than infrequent large doses and overly frequent small doses, so there's still more to discover here

You should read "All else being equal, those highest on cognitive ability experience a 22% (53.2%) increase in the probability of realism (pessimism)" as as a 22% increase in realism and a 53.2% increase in pessimism

Location: Los Angeles

Remote: Either way

Willing to relocate: Probably not

Technologies: python (django, pandas), scala, AWS, GCP, MySQL, PostgreSQL

Resume: http://blog.austinsteady.com/resume.pdf

Email: asteady23@gmail.com

I'm a backend engineer with about 5-6 years of experience. I've been programming since I was about 13. Recent side projects have focused on using GPT to automate fuzzy things like scraping Twitter and dealing with customer service bot menus. Over the last year or so, I also read a few hundred papers related to strength training and turned that research into a book on climbing training, which I'm currently shopping around to publishers

- scraping is relatively dumb and straightforward. I use playwright to login and just scroll my timeline for the first 100 tweets. I run the thing every 3 hours right now, but definitely could tweak the number of tweets vs frequency

- I only care about AI tweets really on my timeline, so filtering to that is pretty straightforward just passing it to GPT

- I included the prompts in the link. Definitely far from perfect, but it works well enough. It does surprisingly suck sometimes, like I've noticed that it doesn't always pick up on tweets about LangchainAI despite AI being in the name etc

https://github.com/purpleladydragons/ai-sanity

If you are a CTO, this will output your productivity ten fold on the upcoming years. Now you don’t need to hire managers and can just build the product of your dreams with very limited capital.

If you are a VC, this will output your productivity ten fold on the upcoming years. Now you don’t need to hire anyone and can just build the product of your dreams with very limited capital.

Agree it'll definitely be amazing for creatives and solo founders, but how many ideas are really out there to be had compared to the reduction in workforce?

https://twitter.com/paulg/status/1600119268858744832

My first job out of school was at a really top-notch place. I grew a lot early on but growth started to slow a bit already by 1 year. I became frustrated with things and wanted to leave. In retrospect, I still think that was probably fine / the right move for me at the time - but what I'd really like to have known is how to make better of the current situation. I lacked the emotional maturity and perspective to take things more into my own hands. Admittedly, I've gained most of my wisdom from job-hopping and seeing things at different places.

I would advise you to be prepared to leave, but have an honest conversation with your manager about your frustrations (and also what makes you happy there). If it's a good place, they'll reciprocate by helping you towards your goals. If not, then you tried, and you can feel good about leaving.

Also just in general, I find average tenure is a very strong indicator of things. Crowd wisdom is important. If most people leave after X time, there might be good reason for it. If your company's average tenure is much longer, then you should try to figure out why those people are happy to stay so long