The most immediate AI milestone is not singularity, but "Economic AGI," where AI can perform most virtual knowledge work better than humans. This threshold, predicted to arrive within 12-18 months, will trigger massive societal and economic shifts long before a "Terminator"-style superintelligence becomes a reality.

Dan Shipper proposes a practical, economic definition for AGI that sidesteps philosophical debates. We will have AGI when AI agents are so capable at continuous learning, memory management, and proactive work that the cognitive and economic cost of restarting them for each task outweighs the benefit of turning them off.

The popular conception of AGI as a pre-trained system that knows everything is flawed. A more realistic and powerful goal is an AI with a human-like ability for continual learning. This system wouldn't be deployed as a finished product, but as a 'super-intelligent 15-year-old' that learns and adapts to specific roles.

A practical definition of AGI is an AI that operates autonomously and persistently without continuous human intervention. Like a child gaining independence, it would manage its own goals and learn over long periods—a capability far beyond today's models that require constant prompting to function.

Hassabis argues AGI isn't just about solving existing problems. True AGI must demonstrate the capacity for breakthrough creativity, like Einstein developing a new theory of physics or Picasso creating a new art genre. This sets a much higher bar than current systems.

OpenAI's CEO believes the term "AGI" is ill-defined and its milestone may have passed without fanfare. He proposes focusing on "superintelligence" instead, defining it as an AI that can outperform the best human at complex roles like CEO or president, creating a clearer, more impactful threshold.

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.

Cutting through abstract definitions, Quora CEO Adam D'Angelo offers a practical benchmark for AGI: an AI that can perform any job a typical human can do remotely. This anchors the concept to tangible economic impact, providing a more useful milestone than philosophical debates on consciousness.

A useful mental model for AGI is child development. Just as a child can be left unsupervised for progressively longer periods, AI agents are seeing their autonomous runtimes increase. AGI arrives when it becomes economically profitable to let an AI work continuously without supervision, much like an independent adult.