> The engine decomposes the traces to understand common failure modes across harness executions and produces a report with its findings.
What are some examples of these common failure modes?
Show HN: RLM-based local debugger for AI agent traces
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Re: Show HN: RLM-based local debugger for AI agent traces
#12Nice work What sort of systematic issues would teams typically uncover using HALO? I guess there's some sort of built-in checklist you include in the RLM prompt
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Re: Show HN: RLM-based local debugger for AI agent traces
#13> The engine decomposes the traces to understand common failure modes across harness executions and produces a report with its findings. What are some examples of these common failure modes?
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Re: Show HN: RLM-based local debugger for AI agent traces
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Re: Show HN: RLM-based local debugger for AI agent traces
#15neat. when you say production-scale traces don't fit in context — does halo cluster failures first or just stream-summarize each trace?
Re: Show HN: RLM-based local debugger for AI agent traces
#16neat. when you say production-scale traces don't fit in context — does halo cluster failures first or just stream-summarize each trace?
It's more-so recursive decomposition rather than clustering failures or stream summarizing. You can look at this repo if you want to learn more about how RLM's work: https://github.com/alexzhang13/rlm
Re: Show HN: RLM-based local debugger for AI agent traces
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