Ashfaqbs opened a new issue, #1066:
URL: https://github.com/apache/flink-agents/issues/1066

   ### Search before asking
   
   - [x] I searched in the 
[issues](https://github.com/apache/flink-agents/issues) and found nothing 
similar.
   
   ### Description
   
   What problem does it solve: today, validating a behavior change to an agent 
(a new prompt, a changed tool set, an updated routing strategy) against 
realistic state generally means either testing against synthetic fixtures or 
deploying the change and watching production. Flink Agents already carries 
durable per-key state through Flink's own checkpoint/savepoint mechanism (the 
recovery model #1016 is about aligning), which is exactly the ingredient a 
safer middle option needs.
   
   What value does it bring: a dry-run mode that takes a savepoint from a 
running (or previously run) agent job, replays a defined set of keys/events 
against a *candidate* agent definition (the new prompt, tool set, or routing 
strategy under evaluation), and reports the resulting decisions/outputs 
side-by-side with what the current definition would produce for the same input 
— without those replayed actions taking effect against any real external tool, 
model call side effect that isn't idempotent, or downstream sink. It's the same 
idea as a Flink savepoint-based canary, specialized to "did my agent's behavior 
actually change the way I expect, on data shaped like production."
   
   Do you already have a solution in mind: no PR yet — the open design question 
is how much of the replay path can reuse existing durable-state and 
event-recording machinery (the same Event Log format #970's Phase 1 OTel work 
already consumes) versus needing a genuinely new replay-only execution mode, so 
I'd like input on which direction the maintainers would actually want to carry 
before proposing a concrete shape.
   
   ### Are you willing to submit a PR?
   
   - [ ] I'm willing to submit a PR!


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