INSTRVMENTVM
What actually changes when a development team puts a coding agent into its workflow — what gets faster, what breaks, and what still needs a human.
Most writing about AI development tools arrives in one of two voices: everything has changed, or none of it works. Neither helps someone who has to decide this week whether to put it in front of a team. This page collects what we have actually seen.
The cluster covers three questions: where a coding agent genuinely saves time, where it creates work that did not exist before, and what a process looks like in which it does not generate technical debt faster than the team can pay it down.
The pieces here come out of running projects, including the site you are reading. Where there is a number, it comes from a source you can check; where there isn't one, we say so.
Article
Review that hunts for syntax errors is redundant once the compiler has caught them. What has to be hunted is decisions: a new file that should have been an extension, a dependency added quietly, and an edge case that vanished.
8 min read ·
Article
A coding agent dramatically shortens the path from intent to running code, and shortens the path to technical debt just as much. The difference is not the tool; it is what the team calls done.
8 min read ·
Answer
No, but the mix has shifted: the repetitive and survey parts shrank, and the parts requiring a decision and accountability take up more room. Demand for experienced developers went up, not down.
5 min read ·
Answer
The difference is not model quality but where the tool sits: Cursor is an editor with an agent inside it, and Claude Code is a terminal agent that leaves your editor beside it. That determines which tasks each one suits.
5 min read ·
Answer
Claude Code's central advantage is that it works across a whole repository from the terminal rather than on an open file, which suits multi-file work. For pinpoint edits that is a drawback.
5 min read ·
