The developer's role is evolving from a linear workflow (code, submit PR, get review) to a parallel one. At Block, developers now manage multiple AI agents building numerous pull requests simultaneously, acting as an editor and context-switcher rather than the sole creator.

The most significant productivity gains come from applying AI to every stage of development, including research, planning, product marketing, and status updates. Limiting AI to just code generation misses the larger opportunity to automate the entire engineering process.

The term 'vibe coding,' once used to describe AI-assisted development, is now obsolete. The industry has matured to complex, multi-agent systems where AIs coordinate, write, test, and resolve issues across codebases with little human intervention. This signals a new era of 'agentic engineering' that is far more sophisticated than simple prompting.

Inspired by fully automated manufacturing, this approach mandates that no human ever writes or reviews code. AI agents handle the entire development lifecycle from spec to deployment, driven by the declining cost of tokens and increasingly capable models.

AI acts as a massive force multiplier for software development. By using AI agents for coding and code review, with humans providing high-level direction and final approval, a two-person team can achieve the output of a much larger engineering organization.

'Vibe coding' is hands-off prototyping where you don't review the code. 'Agentic engineering' is a deep discipline where professionals use coding agents to build production-ready software. This requires significant expertise to guide the agents and ensure quality, a crucial distinction for serious development.

Experienced engineers using tools like Claude Code are no longer writing significant amounts of code. Their primary role shifts to designing systems, defining tasks, and managing a team of AI agents that perform the actual implementation, fundamentally changing the software development workflow.

AI coding agents like Amazon Q are most effective when paired with senior developers. Their primary skill shifts from writing original code to reviewing AI-generated output. This leverage turns already high-performing developers into significantly more productive leaders, as their expertise in code review becomes the new bottleneck.

The debate isn't between manual coding and blindly trusting AI ("vibe coding"). A new discipline, "agentic engineering," is emerging. This involves creating new best practices, security controls, and governance for using AI agents to build software. This structured approach will replace the current era of unchecked individual developer experimentation.