I don't want to be that contrarian guy, but I find it energizing to go faster. For example, being able to blast through a list of niggling defects that need to be fixed is no longer a stultifying drag.
I recently used a coding agent on a project where I was using an unfamiliar language, framework, API, and protocol. It was a non-trivial project, and I had to be paying attention to what the agent was doing because it definitely would go off into the weeds fairly often. But not having to spend hours here and there getting up to speed on some mundane but unfamiliar aspect of the implementation really made everything about the experience better.
I even explored some aspects of LLM performance: I could tell that new and fast changing APIs easily flummox a coding agent, confirming the strong relationship of up-to-date and accurate training material to LLM performance. I've also seen this aspect of agent assisted coding improve and vary across AIs.
I recently used a coding agent on a project where I was using an unfamiliar language, framework, API, and protocol. It was a non-trivial project, and I had to be paying attention to what the agent was doing because it definitely would go off into the weeds fairly often. But not having to spend hours here and there getting up to speed on some mundane but unfamiliar aspect of the implementation really made everything about the experience better.
I even explored some aspects of LLM performance: I could tell that new and fast changing APIs easily flummox a coding agent, confirming the strong relationship of up-to-date and accurate training material to LLM performance. I've also seen this aspect of agent assisted coding improve and vary across AIs.