Instead of a single "AGI" event, AI progress is better understood in three stages. We're in the "powerful tools" era. The next is "powerful agents" that act autonomously. The final stage, "autonomous organizations" that outcompete human-led ones, is much further off due to capability "spikiness."

Moving beyond chatbots, tools like Claude Cowork empower non-coders to create complex, multi-step autonomous workflows using natural language. This 'agentic' capability—connecting documents, searches, and data—is a key trend that will democratize automation and software creation for all knowledge workers.

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.

Claude Code can take a high-level goal, ask clarifying questions, and then independently work for over an hour to generate code and deploy a working website. This signals a shift from AI as a simple tool to AI as an autonomous agent capable of complex, multi-step projects.

The core task of writing code is no longer a significant challenge for AI. The focus is shifting to adjacent tasks and higher-level problem-solving, as demonstrated by Boris Cherny, who hasn't manually written code since November 2024.

Anthropic CEO Dario Amadei's two-year AGI timeline, far shorter than DeepMind's five-year estimate, is rooted in his prediction that AI will automate most software engineering within 12 months. This "code AGI" is seen as the inflection point for a recursive feedback loop where AI rapidly improves itself.

Recent updates from Anthropic's Claude mark a fundamental shift. AI is no longer a simple tool for single tasks but has become a system of autonomous "agents" that you orchestrate and manage to achieve complex outcomes, much like a human team.

The latest models from Anthropic and OpenAI show a convergence in capabilities. The distinction between a "coding model" and a "general knowledge model" is blurring because the core skills for advanced software development—like planning and tool use—are the same skills needed to excel at any complex knowledge work.

According to former OpenAI founder Andre Karpathy, the default programming workflow has become unrecognizable in just the last few months. The paradigm has shifted from developers typing code into an editor to managing and orchestrating autonomous AI agents who are given goals, not step-by-step plans. The new critical skill is managing agents effectively.