In the past decade or so, there has been an explosion of interest in coding. Will more coding make computers better able to serve our needs? Many students, people interested in changing careers, and hobbyists have turned to coding—has this improved our productivity? Are we creating more value?
In the present century, we are richer than ever in terms of computing power. People from decades ago would dream of the computing power available on even a lower-end PC of today. The “PC revolution” really made computers ubiquitous, giving normal people (not just research scientists) access to things like spreadsheets, desktop publishing, databases, and international communication—whether through e-mail, chat software, or (video)calling. Evidently, people do not become more productive in proportion to the speed of their computers or even how recent their software is.
This is where the power of creative thinking comes in and we can be more efficient in whatever projects we undertake—getting more done with fewer resources.
When people talk about “coding”, what they often aim to do is to use the latest, most popular tools to do something which existing tools are already able to do. One example is the multiplication of many so-called web-frameworks in the past decade or so. Companies like Facebook invested heavily in projects like React for building “web apps”. While these tools are cool and certainly offer value to the companies that created them, more often than not people in smaller businesses don’t need a fancy “web app” like Instagram or Messenger—a simple website will do.
Similarly, a company that isn’t dealing with a very high volume of traffic may actually benefit from not having a custom web app for doing things like taking orders from customers. A simpler solution like an e-mail form pre-populated with some useful questions can suffice. Better yet, such a solution can help smaller businesses form relationships with customers.
When people decide to code, their code needs to runs somewhere. One problem with a lot of people “learning to code” today is that they optimize themselves to work with highly specialized systems that may be fitting for large companies like Google or Amazon, but which are actually less efficient and more cumbersome for smaller businesses.
Before investing in “artificial intelligence”, “machine learning”, or even “data science” broadly, business owners can ask—is this thing I am investing in doing more for me than just sending out a few extra e-mails and making a few more phone calls? Thousands of dollars sunk into a simulated Python 3000 receptionist could perhaps better be routed in good old fashioned meet-and-greet.
While “learning to code” may be a useful skill set to acquire to start meeting people or maybe break out of a bad situation and build some discipline, coding (bossing around computers) must be put in its place relative to the many other activities of a value-producing business.