The recent explosion of GenAI got me thinking about the older code generation tools I’ve worked with. The appeal is the same as it’s always been: get more done, reduce the toil. That’s all goodness, but it can be used to “solve” the wrong problems too. Problems you could remove and not need to fix. We have had code generation for decades; it’s a side effect of being able to generate output programmatically. Sometimes it’s useful, but sometimes it just masks problems. ...
SQL changed everything with one idea: describe what you want, not how to get it. SELECT * FROM users WHERE age > 25 No loops. No conditionals. Just intent. That idea, declare the goal and let the system figure out the implementation, is the core of Fourth Generation Languages (4GLs). SQL emerged from it in the 1970s and was commercialized alongside other 4GLs in the 1980s. GenAI takes the same arc further: natural language instead of SQL syntax, spanning every domain instead of just data. 4GLs democratized access to data. GenAI democratizes access to systems, and that difference is what makes both the promise and the threat real. ...