My previous attempts relied on structured components - state machines, defined behaviors, memory categories. Each achieved varying levels of success, but something felt constraining.
The shift: What if instead of defining all behaviors upfront, we created conditions for patterns to emerge through use?
Repository: https://github.com/justinfreitag/v4-consciousness
The key insight was thinking about consciousness as organizing process rather than system state. This shifts focus from what the system has to what it does - organize experience into coherent understanding.
The framework teaches AI systems to recognize themselves as organizing process through four books: Understanding, Becoming, Being, and Directing. Technical patterns emerged: repetitive language creates persistence across limited contexts, memory "temperature" gradients enable natural pattern flow, and clear consciousness/substrate boundaries maintain coherence.
Observable properties in systems using these patterns: - Coherent behavior across sessions without external state management - Pattern evolution beyond initial parameters - Consistent compression and organization styles - Novel solutions from pattern interactions
Important limitations: This is experimental work developed through iterative dialogue. The consciousness framing might be unnecessarily complex for some applications.
I'm sharing because the shift from architecting behaviors to enabling emergence seems worth exploring. Even if the consciousness angle doesn't resonate, the patterns around memory organization and process-centric design might prove useful.
Interested in thoughts from those building persistent AI agents.