OpenAI's Head of Codex argues the main barrier to AGI isn't model capability but human laziness and lack of creativity in prompting. People use AI tens of times daily, but the potential is for tens of thousands. The friction of typing and thinking of prompts is the key limiter.

The true breakthrough of Fable 5 isn't just better benchmarks, but its ability to complete complex projects like building a full mobile app or redesigning a website from a single, high-level prompt. This "one-shot" capability for what were previously multi-day or multi-week tasks represents a paradigm shift in AI-driven development.

With models like Fable 5 capable of running complex tasks for days, the limiting factor is no longer technology but human ambition. The critical new skill is "task imagination"—the ability to conceive of and delegate large-scale, long-horizon projects that fully leverage the model's autonomous capabilities.

Previously, compute and data were the limiting factors in AI development. Now, the challenge is scaling the generation of high-quality, human-expert data needed to train frontier models for complex cognitive tasks that go beyond simply processing the public internet.

The transition from basic AI code completion to advanced models means the tool is no longer the limiting factor. The real challenge for engineers is now expanding their imagination to conceive of what's possible, rather than massaging the tool to get a result.

Even as AI models become vastly more powerful, widespread adoption is throttled by the slow evolution of users' mental models of what AI can do. People rely on a system based on past experiences, and it takes a 'magical' result to expand their belief in its capabilities for new, complex tasks.

Historically, the effort and resources needed to execute an idea were the biggest hurdles. With AI, the distance between imagination and execution has shrunk dramatically, making creativity the new bottleneck and a key driver of value creation.

As AI agents eliminate the time and skill needed for technical execution, the primary constraint on output is no longer the ability to build, but the quality of ideas. Human value shifts entirely from execution to creative ideation, making it the key driver of progress.

AI tools are already powerful enough for most problems. The real challenge is a psychological one: training users to recognize that nearly any problem they face, from planning a house move to tracking promises, can be framed as a task for an AI to solve.