You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Most frameworks store every message or token into memory — but that means agents don’t actually
learn from failures. They repeat mistakes, memory bloats, and debugging stays opaque.
I’ve been experimenting with a lightweight module called Codex that flips this around:
Logs only failure points (contradictions, reasoning gaps, unknowns).
Produces a compact, auditable Reasoning Report (JSON + optional HTML).
Keeps memory lean and makes failures traceable.
Example collapse report for a trivial failure (2+2=5):
{
"collapse_point": "Arithmetic Error",
"claim": "2+2=5",
"evidence": "Contradicts elementary arithmetic",
"status": "collapsed",
"timestamp": "2025-08-29T11:24:00Z"
}
Reasoning Report----------------Collapse Point: Arithmetic ErrorClaim: 2+2=5Status: ❌ CollapsedNotes: Contradiction detected against axiomatic arithmetic rules.👉 If LangGraph (or any agent framework) already produces this kind of failure report, please show me a real example.If not, should we start building this into the ecosystem?Silence = we don’t have it yet.
reacted with thumbs up emoji reacted with thumbs down emoji reacted with laugh emoji reacted with hooray emoji reacted with confused emoji reacted with heart emoji reacted with rocket emoji reacted with eyes emoji
Uh oh!
There was an error while loading. Please reload this page.
-
Most frameworks store every message or token into memory — but that means agents don’t actually
learn from failures. They repeat mistakes, memory bloats, and debugging stays opaque.
I’ve been experimenting with a lightweight module called Codex that flips this around:
Example collapse report for a trivial failure (
2+2=5
):Beta Was this translation helpful? Give feedback.
All reactions