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Record, replay, and improve AI agents in production, built on ZenML
197 starsPython
Record, replay, and improve AI agents in production
by htahir111·Jul 6, 2026·2 points·0 comments
AI Analysis
●●SolidSolve My ProblemSlick
Checkpoint replay and what-if experiments compete directly with LangSmith.
Strengths
- •Framework-agnostic recording works with any agent SDK or harness
- •Checkpoint-based replay enables debugging and model comparison experiments
Weaknesses
- •Agent observability space is crowded with LangSmith, Arize, and funded competitors
- •Self-hosted requirement adds operational overhead for teams
Category
Target Audience
AI engineers building production agent systems
Similar To
LangSmith · Arize Phoenix · Helicone
Post Description
At the AI Engineering World's Fair a big part of the conversation was to nail the self improvement loop. Our take on this is to record state of the agent execution with a durable runtime, then allow users to replay from state checkpoints and run 'what-if' experiments.
It's OSS and free to use. Would love some feedback from the community.
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