The workflow with an AI coding assistant is described as feeling like the human is the robot, not the programmer. The primary role shifts from writing code to shuttling information between different contexts and the AI model, which performs the heavy lifting of code generation and problem-solving.

The new Codex app is designed as an "agent command center" for managing multiple AI agents working in parallel. This interface-driven approach suggests OpenAI believes the developer's role is evolving from a hands-on coder into a high-level orchestrator, fundamentally changing the software development paradigm.

AI coding has advanced so rapidly that tools like Claude Code are now responsible for their own development. This signals a fundamental shift in the software engineering profession, requiring programmers to master a new, higher level of abstraction to remain effective.

New IDEs like Gastown, with roles like 'overseer' and 'mayor' managing AI agent 'convoys,' reveal the developer's future. The job is becoming less about writing code line-by-line and more about high-level orchestration, prompting, and reviewing the output of specialized AI agents to complete complex tasks.

As AI agents handle the mechanics of code generation, the primary role of a developer is elevated. The new bottlenecks are not typing speed or syntax, but higher-level cognitive tasks: deciding what to build, designing system architecture, and curating the AI's work.

Leading engineers like OpenAI's Andre Karpathy describe recent AI tools not as incremental improvements but as the biggest workflow change in decades. The paradigm has shifted from humans writing code with AI help to AI writing code with human guidance.

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.

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.

As AI generates more code, the core engineering task evolves from writing to reviewing. Developers will spend significantly more time evaluating AI-generated code for correctness, style, and reliability, fundamentally changing daily workflows and skill requirements.