It's also often just not true. A lot of the tools we use to solve problems today are miles better than what we used in the past. Imagine trying to process terab

It's also often just not true. A lot of the tools we use to solve problems today are miles better than what we used in the past. Imagine trying to process terabytes worth of data with a parallel compute engine before Spark - you would have to write tons of custom scheduling/workflow balancing code, whereas today I can buy a databricks instance from Azure and start writing a massively parallel stream-processing demo in an hour. Now, a lot of companies do over-engineer and cutting edge tools aren't necessary in a lot of cases, but that's a separate problem.