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Agree. It's code all the way down. The key is to give agents a substrate where they can code up new capabilities and then compose them meaningfully and safely.

Agree. It's code all the way down. The key is to give agents a substrate where they can code up new capabilities and then compose them meaningfully and safely. Larger composition, though, starts to run into typical software design problems, like dependency graphs, shared state, how to upgrade, etc. I've been working on this front for over two years now too: https://github.com/smartcomputer-ai/agent-os/ https://github.com/smartcomputer-ai/agent-os/

whattheheckheck 7mo ago
So what are software packages now a days other than precomputed subsets of capabilities. Like a mesh that data gets pushed through to produce what? What are the optimal subset of prebuilt programs to accomplish any task?
- lukebuehler 7mo ago
  It's a tradeoff. Technically, you need very few programs, you can let an agent do everything and coordinate everything. But that is also inefficient, it's slow and uses a lot of tokens. So you allow the agent to build tools and coordinate those tools, just like we humans do. However, with agents, the threshold of pain is much higher, we can let agents do thing's "manually" where humans would build automations much sooner.
- ghywertelling 7mo ago
  Exactly. Tools like grep, ls are also in the same category. Even in algorithm, we have techniques like memoization and Dynamic Programming which allow us to speed up things. Why should LLM fill up its context by "manually" doing what wc or ls does for you deterministically ?
whattheheckheck 7mo ago
Oh wow, what do you think of karpathys autoresearch? Feels like this is just that? Gotta openclawify it?
iamandoni 7mo ago
> Larger composition, though, starts to run into typical software design problems I've been seeing the same thing. Where agents are great solving the immediate task, but as changes compound they run into software & architectural design problems. I created https://github.com/andonimichael/arxitect https://github.com/andonimichael/arxitect to help at least have coding agents self reflect on their software design. But I really like your approach to self-modification and improving the agent itself instead of just teaching it another skill in it's context.
- deleted 7mo ago
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- cestivan 7mo ago
  [dead]
dataviz1000 7mo ago
I’ve been working with Claude Code to create copies of itself using git worktrees, run an iteration and then update its instructions. It can reverse engineer every website I tested it on. I kept updating the instructions then started asking Claude to update itself. Then asked if could figure out who to iterate unsupervised. https://github.com/adam-s/intercept?tab=readme-ov-file#the-self-improving-skill https://github.com/adam-s/intercept?tab=readme-ov-file#the-s...
LuisvelAI 7mo ago
[flagged]

whattheheckheck 7mo ago

So what are software packages now a days other than precomputed subsets of capabilities. Like a mesh that data gets pushed through to produce what? What are the optimal subset of prebuilt programs to accomplish any task?

lukebuehler 7mo ago
It's a tradeoff. Technically, you need very few programs, you can let an agent do everything and coordinate everything. But that is also inefficient, it's slow and uses a lot of tokens. So you allow the agent to build tools and coordinate those tools, just like we humans do. However, with agents, the threshold of pain is much higher, we can let agents do thing's "manually" where humans would build automations much sooner.
ghywertelling 7mo ago
Exactly. Tools like grep, ls are also in the same category. Even in algorithm, we have techniques like memoization and Dynamic Programming which allow us to speed up things. Why should LLM fill up its context by "manually" doing what wc or ls does for you deterministically ?

whattheheckheck 7mo ago

Oh wow, what do you think of karpathys autoresearch? Feels like this is just that? Gotta openclawify it?

iamandoni 7mo ago

> Larger composition, though, starts to run into typical software design problems I've been seeing the same thing. Where agents are great solving the immediate task, but as changes compound they run into software & architectural design problems. I created https://github.com/andonimichael/arxitect https://github.com/andonimichael/arxitect to help at least have coding agents self reflect on their software design. But I really like your approach to self-modification and improving the agent itself instead of just teaching it another skill in it's context.

deleted 7mo ago
[deleted]
cestivan 7mo ago
[dead]

dataviz1000 7mo ago

I’ve been working with Claude Code to create copies of itself using git worktrees, run an iteration and then update its instructions. It can reverse engineer every website I tested it on. I kept updating the instructions then started asking Claude to update itself. Then asked if could figure out who to iterate unsupervised. https://github.com/adam-s/intercept?tab=readme-ov-file#the-self-improving-skill https://github.com/adam-s/intercept?tab=readme-ov-file#the-s...

LuisvelAI 7mo ago

[flagged]