Tried splitting agent reasoning into two layers this week. Interesting results.
Spent some time testing a two layer agent setup this week.
One layer handled the decisions.
The second layer handled the execution.
Surprisingly, it reduced confusion steps and made multi step tasks feel more predictable.
Still early, but the stability gains were noticeable.
Curious if anyone else here has tried separating reasoning and action in their agents. What worked for you?
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Interesting breakdown.
Interesting! I’ve tried a similar split and it really does make agents more stable. Keeping decisions and execution separate seems to reduce those weird confusion loops. Curious to hear how your setup evolves.
Yeah, those confusion loops were the main trigger for this experiment. The biggest improvement came from forcing the agent to produce a clean plan before touching any tools. Once the plan is locked, the execution layer becomes almost deterministic.
I’m now testing a feedback step where execution reports back only if something deviates from the plan. That’s making the loop even tighter. Curious if you’ve tried something similar in your setup.
That makes sense. I’ve tried a smaller version of that — the agent makes a plan first, then only checks back if something goes off-track. It helped a lot with stability. Your feedback step sounds even better though. Excited to see how it works for you.
Wow, brilliant idea! I’m always curious if there is some psychology involved when making these deductions?
There actually is a bit of psychology in it. When the model is asked to decide and act in the same breath, it tends to shortcut reasoning or hallucinate just to satisfy the ‘do something now’ pressure.
But when you create a pause ;first think, then act; the model behaves more like a human who outlines the steps before executing them. That separation alone reduced a ton of instability in multi-step tasks.
This tracks with what we’ve seen too — once reasoning is isolated, execution becomes more deterministic and predictable.
Exactly. Once I split them, the execution stopped drifting. Curious if you use a strict planning step or something more dynamic in your setups?
This makes sense. Keeping decision logic separate usually makes debugging easier. Did you notice any tradeoffs in speed or complexity when you split the layers?
A little more structure at the start, but the payoff was worth it. Debugging got easier and failures dropped. Have you tried multi-layer flows before or mostly single loop?
Solid experiment. We’ve run into similar issues with agents drifting from the plan. Separating reasoning and execution feels like the right direction. Did you test this across different task types?
Tried it on a few different flows. It held up especially well in tasks with lots of branching decisions. What kind of workflows do you normally deal with?
Nice insight. Multi step processes get messy fast in most systems. Good to see a structured approach to improving stability. Curious where you saw the biggest improvement.
The biggest gain was in longer automations. Once reasoning moved out, retries and edge cases behaved much cleaner. Have you seen similar issues in your flows?
Interesting breakdown. Curious if this kind of split helps with campaign automations too. We see a lot of flows fail because the logic and execution mix together.
Yes, it should help. Campaign flows break often when logic and execution mix. Splitting them reduces those random jumps. Do you usually automate outbound or internal workflows?