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.

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.

Even within OpenAI, a stark performance gap exists. Engineers who avoid using agentic AI for coding are reportedly 10x less productive across metrics like code volume, commits, and business impact. This creates significant challenges for performance management and HR.

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.

The true building block of an AI feature is the "agent"—a combination of the model, system prompts, tool descriptions, and feedback loops. Swapping an LLM is not a simple drop-in replacement; it breaks the agent's behavior and requires re-engineering the entire system around it.

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.

Instead of focusing on foundational models, software engineers should target the creation of AI "agents." These are automated workflows designed to handle specific, repetitive business chores within departments like customer support, sales, or HR. This is where companies see immediate value and are willing to invest.

Sam Altman's ultimate vision for software isn't AI-assisted messaging but a proactive agent. Instead of managing Slack, users will state their goals for the day, and the AI will handle communication and tasks, providing batched updates. This signals a shift from augmenting existing workflows to replacing them entirely.

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.