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**Interesting connection to AI Training / Research:** The overall approach / objectives of the WBR seem very similar to how Ilya Sutskever described how they approach AI training / research. The focus is less on “new ideas,” and more on understanding the behavior of the system. Here’s the quote:
> “Coming up with new ideas is actually just a modest part of the work. Even more important is to understand the results…to understand what’s going on…figuring out the next experiment to run. A lot of the time is spent on that. Understanding what could be wrong, what could have caused the system (neural net) to produce a result which was not expected.”
The real driver of progress / execution / performance/ superior results comes *less* from the generation of the new ideas, *more* on the ability to understand WHY the outcomes are happening. To put it another way: the better you understand the system, the better your innovation and performance will be.
The Amazon Weekly Business Review - Commoncog
The Commonplace Community
The larger the organization, the more essential it is to be relentless at evangelism, and it's important for the leaders to understand that evangelism is something that is never finished. It needs to be constant.
The philosopher and educator John Dewey went a step further: “We do not learn from experience … we learn from reflecting on experience.”
Here are some reflections for closing out an OKR cycle:
• Did I accomplish all of my objectives? If so, what contributed to my success?
• If not, what obstacles did I encounter?
• If I were to rewrite a goal achieved in full, what would I change?
• What have I learned that might alter my approach to the next cycle’s OKRs?
Measure What Matters
John Doerr
...catch up on these, and many more highlights
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