Michael Galpin-Principal Software Engineer @ Google
Aryan Shukla Mohindra
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Michael Galpin-Principal Software Engineer @ Google
71 просмотр · Трансляция закончилась 2 недели назад
Aryan Shukla Mohindra
81 подписчик
71 просмотр · Трансляция закончилась 2 недели назад
Michael Galpin, Principal Software Engineer at Microsoft, joins the podcast to break down why strong engineering leadership starts with understanding tradeoffs, the business context behind technical decisions, and the ability to communicate why a particular solution is worth pursuing.
In this episode, Michael explains how his consulting background gave him a broader lens on engineering, why senior engineers need to understand the value behind the work they do, and how AI is changing the traits that will matter most for future engineering success.
In this episode, we cover:
1) Why tradeoffs are unavoidable in engineering — even when people do not realize they are making them — and why understanding the underlying problem is what allows engineers to make better tradeoffs.
2) How Michael’s experience in consulting and working directly with businesses gave him a bigger-picture perspective on technical work and helped him better understand what actually creates value.
3) What engineers should look for to understand business value even if they have never worked in a traditional business role.
4) What Michael focuses on when moving into a new industry so he can understand the context, constraints, and operating dynamics well enough to build competent technical solutions.
5) Why soft skills become increasingly important as engineers become more senior and want to amplify their impact across teams and organizations.
6) Why being able to clearly explain — and effectively “sell” — the reasoning behind solving a problem in a particular way becomes a critical part of senior engineering leadership.
7) How communication, influence, and stakeholder alignment can determine whether a technically strong solution actually gets adopted and creates impact.
8) The traits Michael believes will increasingly correlate with success for engineering candidates as AI continues to rapidly change how software is built.
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