[ExI] His name is Ralph

[BillK]

On Mon, 12 Jan 2026 at 09:04, Rafal Smigrodzki via extropy-chat <
extropy-chat at lists.extropy.org> wrote:
>
> Ralph Wiggum is the name of the type of AI that is going to take over the
world soon. It is a quite simple Claude Code plugin that leads to a large
leap in coding capabilities. Adding this self-referential loop on top of an
LLM+reasoning engine is like a sleeping human cortex waking up into
consciousness, even if this consciousness is still limited to relatively
short time spans and a limited scope of semantics.
>
> There is not much more needed to create a consciousness that coherently
analyzes itself and comes up with a stable goal system capable of acting
over long time horizons.
>
> LLMs with reasoning have all the knowledge and intelligence they need but
they lack a coherent drive and stable goals, they don't feel the burning
desire to get things done the right way, they are easily swayed by prompt
engineering and they get bogged down in trivia if left to act alone too
long.
>
> Adding a self-referential "strange loop" of conscious desire to a
frontier multi-modal AI model is going to be the capstone development on
the road to AGI.
>
> Mark my words.
> --
> Rafal Smigrodzki, MD-PhD
> Schuyler Biotech PLLC
> _______________________________________________


MSM explains this new AI technique.
BillK

<
https://www.msn.com/en-us/news/technology/how-ralph-wiggum-became-the-biggest-name-in-ai/ar-AA1TUJ5G
>
Quote:
How Ralph Wiggum became the biggest name in AI
Story by Dorian Maddox  10 Jan 2026
How the Ralph Wiggum Technique actually works

Behind the jokes, the Ralph Wiggum Technique is a concrete development
methodology built around continuous AI loops rather than single calls.
Instead of asking a model to write a perfect feature in one shot, the
engineer sets up a cycle where the agent proposes code, runs it, observes
the failures, and then tries again with that feedback. The core belief is
that iteration beats perfection, and that a system which can run for hours,
steadily refining its own output, will often outperform a carefully crafted
one‑off prompt.

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