| It seems far from clear at this point what the dollar value of agentic coding tools is if measured objectively in terms of value delivered. IF they can be shown to be multiplying developer productivity (completing more projects on time, without reduction in quality and associated costs) by some significant amount then they are providing value at current cost, but it's not at all clear whether that is in fact the case, especially since most of the claims of productivity are anecdotal and/or based on things like LOC generated rather than delivered functionality. Meta's "token usage leaderboard" shows how far some companies are from measuring anything meaningful! It'd be exactly like some company in the .com era measuring employee's "productivity" by how many bytes they'd downloaded from the internet each day (even if that was just a cat video). "Woo hoo, we're out-internetting you! Our internet bill is enormous!" (then proceeds to fire the guy coding, and gives a bonus to the one downloading cat videos). There have been some studies/polls done indicating that some very high percentage (90%?) of corporate AI projects are failing. Why is this? Are they ill-conceived, and or ill-executed? Is it the quality of what's being produced that is causing these projects to be abandoned and/or considered as a failure? There have also been some separate studies indicating programmer productivity to be reduced, not increased, by use of AI coding tools, which is easy to understand. The developer struggles with the tool and it's fallibilities, eventually gets it to generate something that works, then closes his JIRA story with an "AI coded" tag (which shows up on the boss's dashboard, and is all that he sees). Was this an AI productivity success story? To the boss perhaps, but not if the developer admits that it would have just been faster to do it the old way by hand or cut-n-paste from stack overflow. |