The Paradigm Shift: From Static to Evolutionary AI

The entire AI tech stack is currently evolving through a five-layer paradigm, which is moving us from “static AI” (the knowledge compressed in an LLM doesn’t update unless it gets retrained) toward agentic AI.

But there is more to it.

As highlighted by the team at Sakana AI, we may be moving towards a Darwin Gödel Machine (DGM), which represents a fundamental leap beyond the traditional AI stack, transforming AI from a static, deployed system into a continuously evolving organism.

While the previous layers (Base LLM, Tools, Memory, RL) create increasingly capable AI agents, the Darwin Gödel Machine layer introduces something unprecedented: AI that rewrites its own source code to become fundamentally better at being AI.

Let’s understand how this might cascade back into the full AI tech stack we’ve developed so far.

How Darwin Gödel Machines Transform Each Layer

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