Software engineers will be obsolete by 2060

-
In response to an article on Medium, Software engineers will be obsolete by 2060, I responded with the following:

Interesting article on The Economist titled Automation on Automation Angst, http://www.economist.com/node/21661017, that looks at several publications that look at the historical effects of automation, and although there is always a fear of being replaced, ultimately more jobs are created than destroyed. Software engineers disappear? So what! There will be other jobs, with different titles, and in the interim, the more people use tech, the more there will be a need for software engineers.

Because of this, a person asked for my opinion on maintaining their career as a .NET developer, to which I responded:

Although I am a .NET developer as well, I focus on expanding my project management and leadership skills, as well as developing skills in AI/ML. Rather than bore with all the details of my background, here is what I think:
  • You should develop your skills in AI/ML, if only by familiarizing yourself with TensorFlow and CNTK. Even if you are not the expert, you should understand it.
Somewhat more generally:
  • Develop your leadership and management skills, if only to become a better developer, even if you don’t aspire to a higher rank, since having those skills will make one a more hireable developer.
  • Although the landscape might change, it is unlikely that you could not find a job with .NET skills in 5 to 6 years, but the most important thing is to keep in touch with the changes, developing as needed.
  • Consider what would put you out of a job, say automation that builds the things you already do and do that. Stay ahead of the wave that is going to crush you, by becoming part of the wave itself.
  • Create an online presence via blogs, codeshares, NuGet and GitHub repo’s, contributions to other projects, and career sites. Make recruiters come to you.

Comments

Post a Comment

Popular posts from this blog

Charting Correlation Matrices in R

-
Image
I noticed this very simple, very powerful article by James Marquez, Seven Easy Graphs to Visualize Correlation Matrices in R , in the Google+ community, R Programming for Data Analysis , so thought to give it a try, since I started some of my current analyses a decade ago by generating correlation matrices in Excel, which I've sometimes redone and improved in R. Some of these packages are only designed for display, or as extensions to ggplot2: corrplot: Visualization of a Correlation Matrix GGally: Extension to 'ggplot2' ggcorrplot: Visualization of a Correlation Matrix using 'ggplot2' These two are focused on more complex analysis: PerformanceAnalytics: Econometric tools for performance and risk analysis psych: Procedures for Psychological, Psychometric, and Personality Research As for data, I used Hofstede's culture dimensions, limited to developed countries. Using a broader and larger set of of countries would significantly reduce the correlation...
Read more

Cultural Dimensions and Coffee Consumption

-
Image
Photo by Viktoria Alipatova from Pexels Responding to a Treehugger article, Why Americans will never love tea as much as coffee , I initially wrote my personal preferences for tea and coffee , ending with, BTW, this has just given me an idea for comparing Hofstede's cultural dimensions and coffee and tea consumption. Afterward, I did some analysis in Excel, then ran the same processes in R using Visual Studio, then converted that to a Jupyter Notebook on Microsoft's Azure Notebooks . Although this analysis is limited to 45 countries that have Hofstede's Cultural Dimensions , as well as per capita consumption for both coffee and tea, it would seem that coffee consumption correlates with power distance, individuality, and masculinity. Tea had small correlations with the dimensions and sometimes in the same direction as coffee. A fuller analysis is available on Microsoft's Azure Notebook , but some quick findings: Higher power distance, lower coffee consumption...
Read more

Developers in New York City by Zip Code

-
Image
Photo by Lukas Kloeppel from Pexels In 2016, after reading a Dice Insight article, I downloaded data that had technology professional numbers by zip code, along with density. A recent NY Times article How Big Tech Is Turning New York Into a Silicon Valley Rival prompted me to resurrect the data, decorate it a bit with neighborhood names, and then import it into Google Maps , which was surprisingly easy. The original data is available in Excel .
Read more