It's passionately interesting for me that the things that I learned in a small town, in a very modest home, are just the things that I believe have won the election.
Margaret ThatcherRead
I always looked up there, because I remember a time when the only things on the walls in Fenway were the Jimmy Fund sign and the retired numbers. Never in a million years did you think you'd ever be up there with those guys.
Interpretation
The quote reflects the journey from humble beginnings to achieving greatness and recognition.
Carlton Fisk's quote expresses a deep appreciation for the journey he took in his career, specifically at Fenway Park. He recalls a time when he viewed the revered signs and retired numbers with admiration, never expecting to be honored in the same breath as the legends of the sport. The quote encapsulates the awe and disbelief that can accompany success, highlighting the importance of dreams and aspirations.
In practice
In a motivational speech about achieving your dreams.
It's passionately interesting for me that the things that I learned in a small town, in a very modest home, are just the things that I believe have won the election.
I don't want to end my career and then start something. I like to do something while my career is still hot and I've always enjoyed designing.
To play 18 years in Yankee Stadium is the best thing that could ever happen to a ballplayer.
Achievers can almost literally taste success because they imagine their goals in such vivid detail. Setbacks only seem to add spice and favor to the final taste of victory.
I think people have learned that Herbie Hancock can be defined as someone that you won't be able to figure out what he's going to do next. The sky is the limit as far as I'm concerned.
The Lean Startup isn't just about how to create a more successful entrepreneurial business, it's about what we can learn from those businesses to improve virtually everything we do. I imagine Lean Startup principles applied to government programs, to healthcare, and to solving the world's great problems. It's ultimately an answer to the question: How can we learn more quickly what works, and discard what doesn't?
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