I’d like to offer a lightweight hypothesis—not as a strong claim, but as a possible design perspective that might deserve more attention.

Today, most AGI development appears to follow a “Processing → Self” path: Large Language Models (LLMs) acquire vast processing capabilities first, and only later (if ever) begin to approximate a self, or any stable internal alignment.

This might be inherently risky. A superintelligent agent that lacks a robust sense of self or ethical continuity in its early stages might pose alignment and control issues, even before reaching full AGI.

As an alternative, I propose the idea of a “Self → Processing” path. In this route, an already self-aware agent (a human) gradually extends its capabilities by offloading memory, reasoning, or action-planning functions to external systems like LLMs or neural interfaces.

The core self—the ethical anchor, goal-structure, and continuity—remains intact and grows by design.

This approach might offer:
- Better alignment by default (the self already aligns with human values)
- Greater traceability of decision-making
- More graceful failure modes (it’s easier to “shut down” or revert)

I don’t have a concrete roadmap for this, nor am I claiming it’s *better* in all cases. But I haven’t seen this path discussed as much as the LLM-based route, and I wonder if it deserves more consideration.

Would love to hear any thoughts, criticisms, or references to similar thinking I may have missed.