In a world where anyone can generate software to solve a problem, the primary constraint on progress is no longer engineering capacity ('who can code'). Instead, competitive advantage shifts to creativity, judgment, and the quality of ideas. This fundamentally breaks traditional organizational structures built around resource allocation for execution.

An AI's ability to code complex games and physics simulations is a strong indicator of its overall power. This showcases its deep understanding and ability to handle sophisticated, multi-layered logic required for complex business applications, not just simple tasks.

Researchers from Anthropic, XAI, and Google are publicly stating that Claude's advanced coding abilities feel like a form of AGI, capable of replicating a year's worth of human engineering work in just one hour.

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.

The next major advance for AI in software development is not just completing tasks, but deeply understanding entire codebases. This capability aims to "mind meld" the human with the AI, enabling them to collaboratively tackle problems that neither could solve alone.

The process of building AI tools is becoming automated. Claude features a 'Skill Creator,' a skill that builds other skills from natural language prompts. This meta-capability allows users to generate custom AI workflows without writing code, essentially asking the AI to build the exact tool they need for a task.

Moving away from abstract definitions, Sequoia Capital's Pat Grady and Sonia Huang propose a functional definition of AGI: the ability to figure things out. This involves combining baseline knowledge (pre-training) with reasoning and the capacity to iterate over long horizons to solve a problem without a predefined script, as seen in emerging coding agents.

As AI makes the act of writing code a commodity, the primary challenge is no longer execution but discovery. The most valuable work becomes prototyping and exploring to determine *what* should be built, increasing the strategic importance of the design function.

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.