Engineers love to experiment, but is experimenting with your career a good idea? In this episode of Programming Leadership, Marcus talks with salary negotiation expert Josh Doody about how this counterintuitive decision can benefit you over the long term. According to Doody, the key is to stop thinking in binary terms of “good” and “bad” outcomes and optimize for learning, instead. Doing so gives us a broader spectrum of results that we can use to decide how to proceed. This will allow us to better calculate risk while also avoiding Old Timer’s Disease and falling victim to loss aversion.
Show Notes
- “Decision science” (3:55)
- Thinking of outcomes as a spectrum rather than “good” or “bad” (5:13)
- Optimize for learning, not outcomes (7:31)
- How career experimentation has helped Josh (11:17)
- Understanding the long game (16:23)
- How to avoid Short-Timer’s Disease (18:53)
- Using expected value to calculate risk (23:41)
- Loss aversion can impede our ability to accurately calculate risk (27:59)
- “Good” and “bad” are subjective terms when it comes to experimentation (32:39)
Links
- Josh Doody on Twitter
- Antifragile, Nassim Taleb
- Should Belichick have gone for it on 4th and 2? by Josh Doody
- Marcus’s interview with Josh on Software Engineering Radio
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