my first principle of agi

i don’t actually recommend u use this principle without fully understanding. it’s just a reference to what’s possible

The First Principle of AGI

Any continuous task can be broken down into discrete, small tasks that an LLM can complete without error, achieved through multi-step execution.

Analogy to the human brain: rational logic (task decomposition) vs. intuitive perception (LLM completing error-free small tasks)

---

How Does an Agent Learn Tasks?

Preserve the prompt experience of human pioneers, compressed into skill.md through summarization or hard-coded into code.

Analogy to the human brain: sparse neural connections (summarized into skill.md), dense neural connections (hard-coded)

---

How Does an Agent Decompose Tasks?

Through human pioneers refining the task logic, exhaustively enumerating all cases at the granularity level that an LLM can reliably complete.

---

How Does an Agent Scale?

Continuously persist task experience from all industries and professions to disk, expanding the granularity of the minimum task an LLM can reliably complete.

---

Implement this guiding ideology and become the AI Adventists.