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's impact on coding is unfolding in stages. Phase 1 was autocomplete (Copilot). We're now in Phase 2, defined by interactive agents where developers orchestrate tasks with prompts. Phase 3 will be true automation, where agents independently handle complete, albeit simpler, development workflows without direct human guidance.

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.

Frame AI agent development like training an intern. Initially, they need clear instructions, access to tools, and your specific systems. They won't be perfect at first, but with iterative feedback and training ('progress over perfection'), they can evolve to handle complex tasks autonomously.

A new software paradigm, "agent-native architecture," treats AI as a core component, not an add-on. This progresses in levels: the agent can do any UI action, trigger any backend code, and finally, perform any developer task like writing and deploying new code, enabling user-driven app customization.

Successful AI products follow a three-stage evolution. Version 1.0 attracts 'AI tourists' who play with the tool. Version 2.0 serves early adopters who provide crucial feedback. Only version 3.0 is ready to target the mass market, which hates change and requires a truly polished, valuable product.

Traditionally, building software required deep knowledge of many complex layers and team handoffs. AI agents change this paradigm. A creator can now provide a vague idea and receive a 60-70% complete, working artifact, dramatically shortening the iteration cycle from months to minutes and bypassing initial complexities.

To effectively interact with the world and use a computer, an AI is most powerful when it can write code. OpenAI's thesis is that even agents for non-technical users will be "coding agents" under the hood, as code is the most robust and versatile way for AI to perform tasks.

Visual AI tools like Agent Builder empower non-technical teams (e.g., support, sales) to build, modify, and instantly publish agent workflows. This removes the dependency on engineering for deployment, allowing business teams to iterate on AI logic and customer-facing interactions much faster.