Andrew Wilkinson argues that advanced AI models have achieved AGI-like capabilities in programming. He quotes Anthropic's CEO, suggesting that the role of a programmer is shifting to that of an architect, and many current programmers are in denial because their paycheck depends on not understanding this shift.

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.

Framing AGI as reaching human-level intelligence is a limiting concept. Unconstrained by biology, AI will rapidly surpass the best human experts in every field. The focus should be on harnessing this superhuman capability, not just achieving parity.

The ability to code is not just another domain for AI; it's a meta-skill. An AI that can program can build tools on demand to solve problems in nearly any digital domain, effectively simulating general competence. This makes mastery of code a form of instrumental, functional AGI for most economically valuable 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.

While AI will make average performers good, its most dramatic effect will be making great performers spectacularly great. By augmenting top talent in fields like coding, art, or science, AI enables a single individual to achieve productivity levels previously requiring large teams, creating a new class of hyper-achievers.

The ultimate goal for leading labs isn't just creating AGI, but automating the process of AI research itself. By replacing human researchers with millions of "AI researchers," they aim to trigger a "fast takeoff" or recursive self-improvement. This makes automating high-level programming a key strategic milestone.

Casado, a lifelong developer, states he never would have guessed AI would become so proficient at coding. He identifies it as the single area where AI has surprised him most, suggesting a multi-trillion dollar market opportunity.