In agent-based AI, thinking should be fluid, not locked in a recursive chokehold.
🚦 Problem: Blocking Loops Kill Parallelism
LangGraph's looping structure is elegant on paper simple retry branches, conditional checks, and reruns. But there's a catch.
Loops in LangGraph block execution. When an agent hits a loop, the entire workflow must wait. Nothing else runs until that loop finishes its retry-check cycle. That might be fine for scripts. But for cognition, it’s deadly.
🧬 OrKa's Breakthrough: Coroutine Loops
OrKa introduces a dedicated LoopNode. It doesn't hijack the orchestrator’s timeline it spins up a scoped cognitive subprocess.
- Forks memory context
- Runs multiple agents in parallel
- Evaluates AGREEMENT_SCORE
- Decides to exit or re-run
- Writes back memory
This loop isn’t a trap! It's a thought capsule. You can have three loops resolving internal decisions while the main graph continues reacting, branching, moving.
Because thinking needs freedom, not cascade evolution.
Modular. Explainable. Runnable anywhere.
đź’» Orka: https://orkacore.com
🧪 Docs + install: pip install orka-reasoning
Follow if you’re serious about traceable AI reasoning. No black boxes.
“I didn’t build OrKa because I thought the world needed another SDK.
I built it because I was sick of watching agents play ping-pong with prompts while pretending to think.”
Top comments (2)
Quoting:
Love this! That’s exactly what it feels like half the time - I throw a prompt in, the agent stares off into the existential abyss for a while, and then: 🕳️ ...crickets.
Exactly. We keep calling it “reasoning,” but most frameworks are just duct-taped I/O pipes in a trench coat. They wait. They loop. They bluff.
Real cognition moves, it branches, remembers, questions, restarts itself.
OrKa's whole point is: stop babysitting the prompt. Give your agents a structure that lets them actually think.
Appreciate the resonance, Ashley.