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HyperAgents: Self-referential self-improving agents

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Re: HyperAgents: Self-referential self-improving agents

#51

I think even code bases will have self improving agents. Software is moving from just the product code, to the agent code that maintains the product. Engineering teams/companies that move in this direction will vastly out produce others. I've had to really shift how I think about building code bases, alot of logic can go into claude skills and sub agents. Requires essentially relearning software engineering

We do this already but I bet this is not how people imagine it to be. There is still a review process to accept contributions.

Re: HyperAgents: Self-referential self-improving agents

#53
post #50

Earlier quoted context omitted.

Awareness would be any form of agency, goal seeking, or loss minimizing. As Briggs–Rauscher reactions can eventually lead to Belousov–Zhabotinsky reactions, the system can maintain homeostasis with its environment (and continuing to oscillate) by varying reactants in a loss minimizing fashion. This loss minimizing would be done during scarcity to limp towards an abundance phase. This is the mechanism that hypothetica…

I'm not sure what your argument is here, except stating an opinion that loss minimization is equivalent to agency. But even if that was accepted, which is a huge stretch, it doesn't stretch all the way to awareness.

It is, in context of its place in the cosmic scale.

Loss minimizing to a few problems will generalize into abstraction, and a few solutions will develop.

These systems with more generalizable resilency traits will encounter increasingly varied selective sieves.

Systems that survive this seive will exhibit increasingly sophisticated, generalizable solutions to prevent loss of needed dependent reactions/resources.

These solutions must exert influence to be effective; influencing the environment for its own benefit.

As systems influence their environment, delineation of "self" and "environment" becomes a fundamental barrier.

The system would prefer itself, or be outcompeted by a similar system that does.

This layer of semi-life like material would form between sunlight and the oscillating reaction, and eventually envelope it, minimizing surface tension by means of a spherical cell like structure.

Small stuff runs off of loss minimizing at a force level for its mechanistic affect; from covalent bonds to cellular ion transport, the path of lesser resistance is the fundamental forces.

As systems become more complex, the minimizing is less directly attributable to the fundamental forces and becomes more of a Byzantine dependency/feedback network.

This byzantine labyrinth of interactions is called biology.

The delineation of self, the ego.

At the highest levels, geopolitics. At the human level, mate suppression. Lowest level, energy conservation.

All loss minimizing

Re: HyperAgents: Self-referential self-improving agents

#54

Pi is self modifying, self aware. https://lucumr.pocoo.org/2026/1/31/pi/ But this idea of having a task agent & meta agent maybe has wings. Neat submission.

I asked Pi to implement a skill. It was written in TS. Then I ask it to use the skill in two different sessions, none of them can get it working. One has to wrap it with JS and call it. The other has to take the curl commands out of the skill and call them directly. Which is quite smart BTW. But what is the point of making a convoluted TS skill at all?

https://gist.github.com/ontouchstart/40db1244c0ff523f830df1c...

Re: HyperAgents: Self-referential self-improving agents

#55
post #24

Earlier quoted context omitted.

What are the differences wrt Recursive Language Models

Completely unrelated. Recursive Language Models are just "what if we replaced putting all the long text into the context window with a REPL which lets you read parts of the context through tool calls and launch partitioned subagents", ie divide-and-conquer applied to attention space.

They also tend to imply symbolic recursion which seems to be the biggest deal out of everything by a wide margin.

When you can nest 10+ agents deep and guarantee you will get back home without losing any data in any of the stack frames, the ability to chunk through complex problems goes up dramatically.

Re: HyperAgents: Self-referential self-improving agents

#56
I found that running an agent in ralph loop, showing it the agent text and saying "run this, if it fails - identify the reason, and modify the agent instructions to avoid this, acceptance criteria are this and that" worked surprisingly well. Not sure if it qualifies as a self-referential self improving, but it was something.

Re: HyperAgents: Self-referential self-improving agents

#59

The loop on this is basically tweak your prompt until you score better on a contrived test.

Yeah if it was truly capable of self-improving, why did it not take over the world yet?

Gemini itself says AGI will be here in 2029, with human level intelligence and self-improvement capabilities. But then it will take until 2045 before the singularity. I don’t understand what they are going to do in all those years.

Re: HyperAgents: Self-referential self-improving agents

#60

The paper is here - https://arxiv.org/pdf/2603.19461 This, IMO is the biggest insight into where we're at and where we're going: > Because both evaluation and self-modification are coding tasks, gains in coding ability can translate into gains in self-improvement ability. There's a thing that I've noticed early into LLMs: once they unlock one capability, you can use that capability to compose stuff and improve on oth…

Agents need the ability to code but also to objectively and accurately evaluate whether changes resulted in real improvements. This requires skills with metrics and statistics. If they can make those reliable then self-improvement is basically assured, on a long enough timeline.
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