Product Management Resources
A lot of people ask me how to break into product management or what resources I recommend to improve on the PM craft. Here are a few of those recommendations, along with content I consume myself on a regular basis. I will caveat this all by saying that consuming resources will never make up for the learning experience of shipping products, so I encourage you to do just that - first and foremost, and then again and again, and to check out the below in parallel.
- Ken Norton's blog posts, newsletter
- Book: Inspired: How To Create Products Customers Love
- Masters of Scale Podcast
- Marty Cagan's SVPG Blog
- Book: Competing Against Luck, and generally, the Jobs to Be Done framework
- Stratechery Blog - it's the best $10 I spend every month. Ben Thompson provides his deeply thoughtful analysis on what's happening in the tech landscape right now. You will learn something new in almost every article he writes.
- Book: Managing Humans
- Hacker News
- Talking to engineer friends. My closest circle of friends and family (mom, dad, uncles...) are almost all software and hardware engineers... coincidence? #blacksheep
- I use many different products and apps on a regular basis for research and for fun - this includes apps I wouldn't normally use as a consumer. Do it! It's a great way to build up product design intuition.
- Read the release notes of the apps you admire
- While using all these different products, I mentally catalog -- or, if it's really good, screenshot -- design elements & interactions that I find are beautifully designed and/or are clever solutions to a common problem, such as... graphs (line weight, popups, animations, everything), custom date pickers, nav with horizontal scroll, onboarding tours, push notification copy, good information hierarchy especially on a nav bar, icon designs, native ways of collecting user feedback, ways of presenting machine learning features in a product - including the copy (e.g. Slack Highlights' "sorted scientifically"), how products ask for permissions...
- This is a topic that I am very bullish on - I think machine learning has the potential to 5-10x improve solutions for almost every product problem across many different industries. I've given several talks on this - here's a slide deck with some of my thoughts.
- I compiled this resource list from an event I co-organized/hosted called Building Machine Learning Products at Squarespace in July 2017. The field changes quickly though, so it might not include some recently developed resources, like Andrew Ng's Deep Learning Specialization.