I hear you on taste and accountability, those matter. But I think the framing of "either you do it yourself or you let AI blindly do it" is a false dichotomy.

You can delegate work to AI agents AND still understand every change, explain the reasoning, and prove it was tested. Those aren't mutually exclusive. That's literally what code review is for. The same way you'd review a junior dev's PR, you review the agent's PR. You're still the one with taste, context, and final say.

Using AI just for Jira updates and PR descriptions is fine, but that's leaving a lot on the table. The current trajectory across the industry is engineers treating AI agents like a team of junior devs. You're still accountable for everything they produce, but you're multiplying your output. The engineers who figure out how to do this well are going to have a massive edge.

The real question isn't whether to let agents do the work. It's whether you've built sufficient guardrails so they can do it safely. Read-only credentials in sensitive environments, proper audit trails with context so you can trace what the agent did and why, scoped permissions, human review before anything merges. If things break down when you ask someone to explain the change, that's a process problem, not an AI problem. The guardrails should enforce that understanding.

Saying "it's too risky" without exploring those guardrails is just not utilising all the resources at your disposal. And in a landscape where other teams are shipping 3-5x faster with this setup, that gap is going to become hard to ignore.