I definitely agree with the sentiment of this article, give or take. I've seen it at the place a previously worked at and now the place I currently work at: everybody wants AI to make coding faster and more efficient, but nobody is willing to take the risk of changing course and bending the firm's processes around what would actually make the agents more useful. Maybe this is more general than the qualms against "software factories," but it's pretty apparent that agentic development doesn't mesh with most of the development processes everyone was following prior to LLMs. Whenever a human is in the loop, it creates THE bottleneck which ultimately sets the pace. When humans can't fathom not being in the driver seat, then they're constantly in the loop, and nothing actually improves.

I DO see small instances where this is overcome, albeit, it occurs when risk is minimal, the work is non-critical, and the required environment is already available. For example, exploratory research of new features. Before, this would be quite costly and particularly cumbersome since the results may indicate that the new feature isn't viable and the work is basically "wasted." Now, you can send some agents to explore it for you and give you a "first pass" on the validity of the concept. You still end up with humans taking over immediately after (often to verify that first pass), but this has allowed a bit more efficiency in terms of understanding when investing that human time in exploratory investigation is appropriate and when it isn't. People are willing to give agents this level of control because the alternative is usually just a default "no."

Regardless, it seems obvious we're in a painful transition period where everyone in software can see that there's a ton of value here, but where everyone is simultaneously constrained by existing infrastructure, processes, expectations, etc., so as to not be willing or able to tap into that value. I suspect it won't be until there's just more new companies coming in without these existing constraints will the actual new version of these processes start to emerge and MAYBE some of the existing companies will be more willing to shake things up as needed to take advantage of it.

Was this written by AI?

My experience, with the latest models, they do write code that looks correct/polished, but often do not fully solve the problem, or solve the wrong thing, or introduce un-needed complexity. By often, I mean at least 10%-15%, which is still a high enough error rate, that you don't want to let loose in even a trivial service, let alone a service that is on the critical side.

For now humans are absolutely needed in the loop.