Conversation

I wish I could go back to engineering school for an intensive 1 year reboot. 6mo refreshing basics like calculus, physics, chemistry, coding, stats, basic mech/elec/chem hands on, and 6 months high-level refactoring of engineering principles based on megatrends since graduation
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Both are bad states to be in. As a fresh grad, I had terrible intuitions about big picture stuff, but was good at solving problems that mapped neatly to specific skills like say linear programming or soldering or computing eigenvalues. Now it's reverse.
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"Big picture stuff"= things like: Should we add more sensors or more compute to a solution? Is the bottleneck the noise in the signal or the jankiness in the UX? How much is the relative effort of software vs. hardware? Is there uncanny valley between 0 and 100% automation?
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Very few people mature in a balanced way. They either "graduate" to the big picture and let hands-on skills atrophy, OR they develop blinders around hands-on skills and never develop any intuitions for big-picture problems, instead developing insecure identity issues.
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The most interesting and effective (which is NEVER the same as "best" in an engineering vanity sense) senior technical leaders come closest. They are maybe a 7/10 in my experience where most are a 3-4/10. 10/10 would be depth+balance while low scores would be shallow+imbalanced.
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But if feels like the right injection of mid-career reboot education could take the people at 3/10 to 5/10 and the 7/10 to 9/10.
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Another way to put it. Between 18-22 (1993 - 97) I was very good at learning, but very bad at deciding what was worth learning. Now I'm very bad at learning, but very good at figuring out what's worth learning. I think I've been good enough at both for like 6 months in my career.
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When you're in a state where you're good at both, the effectiveness leverage is unbelievable. In the 6 months of my life when I was good at both, I suspect I did 90% of all the valuable things I did.
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A career in technology is basically trying to add value as you age from good at learning/bad at choosing --> bad at learning/good at choosing. The area under that curve = value you add. Time spent in "good at both" quadrant = spikes of value creation.
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What makes this hard is that BOTH low-level and high-level are changed by evolution in megatrends after you leave school. The rise of "AI" for example, impacts both the value of knowing linear algebra (low-level skill) and rewires intuitions around tradeoffs between data/compute
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And continuous experience in an industry/problem area is no guarantee that you'll keep your head in the game effectively. Entire companies and industries can get out of sync with impact of megatrends, taking entire buildings of engineers and engineering managers down with them
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I've been in rooms full of smart engineers and managers discussing tech problems in fundamentally wrong-headed ways that doom the company. The frogs-in-skill-wells don't know their identity-pride skills have been John Henryed, the big-picture people are ignoring key variables.
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