We’ve all seen what large language models do with a single-shot prompt: they guess. Sometimes insightfully, sometimes not. But what if AI cognition wasn’t a dice roll, but a debate? What if reasoning could loop over itself, accumulating memory, refining positions, and escalating its own standards of agreement until convergence wasn’t just probable, it was inevitable?
That’s what the LoopNode in OrKa unlocks.
🧩 The Missing Piece in AI Reasoning: Cognitive Recursion
Most AI frameworks (LangChain, Autogen, CrewAI) optimize task decomposition and execution. But they suck at deliberation. There's no cognitive memory across passes, no historical synthesis, no ability to say, “We’re not ready to answer that yet.”
OrKa’s LoopNode introduces a new primitive: recursive reasoning with memory, conflict, and synthesis. Not a retry. Not a rerun. A negotiation among agents.
🔁 How It Works: Fork → Read → Join → Loop
Each LoopNode iteration launches a fork group of specialized agents — logic, empathy, historian, skeptic, moderator — who access prior reasoning memories scoped by loop count and role. They respond independently.
Then OrKa’s JoinNode merges these replies into a shared memory state. The moderator_agent evaluates if there's enough agreement to exit. If not, the LoopNode reruns the entire sequence.
Loop continues until:
- A consensus threshold is met (
AGREEMENT_SCORE >= x) - Or maximum iteration count is hit
The output isn’t a single model’s guess. It’s the resolved, memory-enriched output of a cognitive society.
🧠 Real Example: “Who is Marco Somma?”
In trace file orka_trace_20250710_090911.json, the system runs a LoopNode over the prompt:
“Who is Marco Somma, the author of orka-reasoning?”
The first loop returns weak replies:
- Logic: uncertain, low confidence
- Skeptic: flags obscurity
- Historian: names the context but no strong commitment
But LoopNode doesn’t stop. It loops again.
By loop 3:
- Logic confidently outlines the ORKA-Reasoning framework
- Historian connects it to the history of object-based reasoning
- Skeptic still challenges the public recognition, but accepts internal coherence
- Moderator reports ~0.75 agreement score and chooses to continue
By loop 5:
- All agents align on the conceptual framing of Marco Somma as a contributor to a reasoning architecture
- Differences narrow to tone and epistemic humility
- LoopNode exits with confidence
What you get is a nuanced, historically grounded, critically moderated synthesis — not a hallucinated LinkedIn bio.
🧩 Why LoopNode Matters
This isn't retry logic. This is structured epistemology.
LoopNode encodes something missing from all current LLM stacks: the ability to say “We’re not sure, let’s think again.” Not in a hand-wavy CoT prompt way. But via:
- Agentic roles (skeptic vs empathy vs historian)
- Scoped memory per loop and per role
- Forked reasoning and real-time joining
- Moderator arbitration
LoopNode isn’t about looping forever. It’s about looping until alignment emerges or the system declares, “this topic remains unresolved.”
🧠 What Emerges: Cognitive Simulated Society
Each LoopNode run is a tiny simulated epistemic society:
- Citizens: agents with different reasoning values
- Laws: agreement thresholds
- Archives: scoped memory across loops
- Courts: moderators that decide if a verdict is ready
You’re not querying a model — you’re orchestrating a microculture of thought.
🧨 So What?
With LoopNode:
- You don’t guess, you converge
- You don’t prompt, you negotiate
- You don’t retry, you refine
This is how cognition should work: as iterated, memory-bound, self-critical simulation — not as a single forward pass.
If you're building agents that think, you need LoopNode. Full stop.
And if you're not building agents that think, then why are you building at all?
Top comments (0)