Dylan Patel describes Anthropic's unreleased Mythos model as a monumental step forward, comparing its coding ability to an L6 software engineer—a huge jump from Claude 3 Opus's L4. The capability is so advanced that Anthropic is deliberately withholding its full power, signaling a new era of model performance.

For complex, multi-turn agentic workflows, Tasklet prioritizes a model's iterative performance over standard benchmarks. Anthropic's models are chosen based on a qualitative "vibe" of being superior over long sequences of tool use, a nuance that quantitative evaluations often miss.

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.

With AI models now capable of running complex, multi-day tasks, the limiting factor is no longer technical capability but human imagination. Users need to recalibrate their thinking to conceive of projects at a scale and scope that fully leverage the AI's power, moving beyond simple, short-term requests.

Newer models like OpenAI's 5.2 can solve bugs that were previously impossible for AI by "thinking" for extended periods—up to 37 minutes in one example. This reframes latency not as a flaw, but as a necessary trade-off for tackling deep, complex problems.

The rate at which AI can reliably complete complex, autonomous tasks is accelerating. Previously, this capability doubled every seven months; new data from AI lab Anthropic shows it's now doubling every four months, indicating a rapid increase in AI's practical power.

A key breakthrough for GPT-5.5 is its stability in tasks running for over 7-8 hours, a feat previous models struggled with. This reliability is a game-changer for agentic AI, enabling complex software migrations and ambitious, long-running projects to execute autonomously without failing, fundamentally increasing the scope of work that can be delegated to AI.

Despite a higher price per token, Fable 5 can be more cost-effective in practice. Its ability to solve complex problems correctly on the first try ("one-shot") eliminates the significant token and time costs associated with iterative reprompting, making it cheaper for ambitious projects that require high accuracy.