Code analysis firm sees no major benefits from AI dev tool when measuring key programming metrics, though others report incremental gains from coding copilots with emphasis on code review.
Same. AI seems like yet another attempt at RAD just like MS Access, Visual Basic, Dreamweaver, and even to some extent Salesforce, or ServiceNow. There are so many technologies that champion this…RoR, Django, Spring Boot…the list is basically forever.
To an extent, it’s more general purpose than those because it can be used with multiple languages or toolkits, but I find it not at all surprising that the first usage of gen AI in my company was to push out “POCs” (the vast majority of which never amounted to anything).
The same gravity applies to this tool as everything else in software…which is that prototyping is easy…integration is hard (unless the organization is well structured, which, well, almost none of them are), and software executives tend to confuse a POC with production code and want to push it out immediately, only to find out that it’s a Potemkin village underneath as they sometimes (or even often) were told the entire time.
So much of the software industry is “JUST GET THIS DONE FASTER DAMMIT!” from middle managers who still seem (despite decades of screaming this) to have developed no widespread means of determining either what they want to get done, or what it would take to get it done faster.
What we have been dealing with the entire time is people that hate to be dependent upon coders or other “nerds”, but need them in order to create products to accomplish their business objectives.
Middle managers still think creating software is algorithmic nerd shit that could be automated…solving the same problems over and over again. It’s largely been my experience that despite even Computer Science programs giving it that image, that the reality is modern coding is more akin to being a millwright. Most of the repetitive, algorithmic nerd shit was settled long ago and can be imported via modules. Imported modules are analogous to parts, and your job is to build or maintain the actual machine that produces the outcomes that are desired, making connecting parts to get the various components to interoperate as needed, repairing failing components, or spotting the shoddy welding between them that is making the current machine fail.
Same. AI seems like yet another attempt at RAD just like MS Access, Visual Basic, Dreamweaver, and even to some extent Salesforce, or ServiceNow. There are so many technologies that champion this…RoR, Django, Spring Boot…the list is basically forever.
To an extent, it’s more general purpose than those because it can be used with multiple languages or toolkits, but I find it not at all surprising that the first usage of gen AI in my company was to push out “POCs” (the vast majority of which never amounted to anything).
The same gravity applies to this tool as everything else in software…which is that prototyping is easy…integration is hard (unless the organization is well structured, which, well, almost none of them are), and software executives tend to confuse a POC with production code and want to push it out immediately, only to find out that it’s a Potemkin village underneath as they sometimes (or even often) were told the entire time.
So much of the software industry is “JUST GET THIS DONE FASTER DAMMIT!” from middle managers who still seem (despite decades of screaming this) to have developed no widespread means of determining either what they want to get done, or what it would take to get it done faster.
What we have been dealing with the entire time is people that hate to be dependent upon coders or other “nerds”, but need them in order to create products to accomplish their business objectives.
Middle managers still think creating software is algorithmic nerd shit that could be automated…solving the same problems over and over again. It’s largely been my experience that despite even Computer Science programs giving it that image, that the reality is modern coding is more akin to being a millwright. Most of the repetitive, algorithmic nerd shit was settled long ago and can be imported via modules. Imported modules are analogous to parts, and your job is to build or maintain the actual machine that produces the outcomes that are desired, making connecting parts to get the various components to interoperate as needed, repairing failing components, or spotting the shoddy welding between them that is making the current machine fail.