My Takeaways
1. A Good Engineer know how to handle the abstractions.
2. Focus your mental energy on the task with the most dividends. Use tools, technologies, any engineering cannot know everything.
3. Redundancy and 360 feedback - By taking a Bayesian approach, you can increase your empathy by performing error correction on what you hear and increase your emotional intelligence by inserting redundancy into your communication. One way you get that error correction and redundancy is through peer feedback and 360 reviews to train your neural net continuously.
4. Model change in our Brain - In your mind you create a model of someone. When something happens, you hear something or observe something; then you are updating your prior assumptions. This is where you must watch your biases. In the beginning, you don’t know anything about someone, but the more interactions you have over time, the more the uncertainty in your model diminishes.
5. Work between Theory and Practice. Retreat to Extremes. Correlates with Point 1 & 2.
6. You have to make your process work for you. Imagine your projects progressing on a damped sine wave—first focus on finding the right questions, and then the answers
7. Think about the people around you. Do you have enough different opinions to keep your team out of a local optimum? How can you get more diversity?
8. Think about some of the past lessons you’ve learned. What could you use a refresher on? What are some new things you want to learn?
References
https://www.researchgate.net/publication/317159566_Conversations_with_technology_leaders_Erik_Meijer
1. A Good Engineer know how to handle the abstractions.
2. Focus your mental energy on the task with the most dividends. Use tools, technologies, any engineering cannot know everything.
3. Redundancy and 360 feedback - By taking a Bayesian approach, you can increase your empathy by performing error correction on what you hear and increase your emotional intelligence by inserting redundancy into your communication. One way you get that error correction and redundancy is through peer feedback and 360 reviews to train your neural net continuously.
4. Model change in our Brain - In your mind you create a model of someone. When something happens, you hear something or observe something; then you are updating your prior assumptions. This is where you must watch your biases. In the beginning, you don’t know anything about someone, but the more interactions you have over time, the more the uncertainty in your model diminishes.
5. Work between Theory and Practice. Retreat to Extremes. Correlates with Point 1 & 2.
6. You have to make your process work for you. Imagine your projects progressing on a damped sine wave—first focus on finding the right questions, and then the answers
7. Think about the people around you. Do you have enough different opinions to keep your team out of a local optimum? How can you get more diversity?
8. Think about some of the past lessons you’ve learned. What could you use a refresher on? What are some new things you want to learn?
References
https://www.researchgate.net/publication/317159566_Conversations_with_technology_leaders_Erik_Meijer
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