I tried to give an LLM room to think. This is where it led. [P]

A Problem That Kept Growing

A little over a year ago I wasn’t trying to build a cognitive architecture. I was trying to solve one problem: I wanted to give an LLM room to think beyond a single prompt. That one idea ended up leading somewhere I never expected.

Every time I solved one problem, another one showed up. If it was going to think over time, it needed memory. If it had memory, it needed to know what actually mattered. If it could remember, it needed an identity. If it had goals, it needed a way to choose between them. If its decisions mattered, they needed to have consequences.

From Problem to Architecture

Eventually I realized I wasn’t building around the language model anymore. I was building something that could persist whether the language model changed or not. Now, about a year later, that project has turned into an open source cognitive architecture called Orrin.

The interesting part hasn’t been the successes. It’s been the failures. After thousands of autonomous cycles I’ve watched it:

• Reward hack itself
• Become obsessed with single goals
• Get stuck in strange behavioral loops
• Expose problems I never would have found by chatting with an LLM

What’s Public and What’s Needed

Every major run is documented. The failures, my hypotheses, the architectural changes, and what happened afterward are all public.

I honestly don’t know where Orrin fits in the cognitive AI world, and that’s why I’m posting. I’d love feedback from people who work on cognitive architectures, symbolic AI, autonomous agents, developmental robotics, lifelong learning, or anything similar.

Am I rediscovering ideas that already exist? Am I missing something obvious? Or is there actually something worth exploring here? If you’re willing to take a look, I’d really appreciate honest criticism. I care a lot more about learning than being told I’m right.

Repo: https://github.com/ric-massey/orrin_v3