AI coding has increased productivity (98% more PRs) but prolonged review times (91% longer), shifting work from coding to review processes. Various perspectives agree on data yet disagree on implications. Challenges include comprehension debt and the need for robust infrastructure. Strategies vary from spec-driven development to autopilot modes, focusing on context management and oversight. Risks involve reliance on AI without proper guardrails leading to misunderstandings and accountability issues. Ultimately, it's crucial to understand where complexity resides and ensure humans remain engaged in essential tasks.
