Erhan Giral

speaker
389 appearances 1 recordings 1 series first heard Aug 2026 last heard 3 Aug

Erhan Giral’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Aug 2026 with 1.

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and can sufficiently confident to say, hey, you know, this is actually something we deal with and here is how we solve these problems.
Then there is a lot of economies there.
So you can imagine that the pressure in the market is always towards, okay, so can we fix these reoccurring problems, which tend to be like 80, 85% of the problem space.
What can we do to automate these as quickly as possible?
That's essentially what, you know, people like Ryan and me do.
Yeah, we absolutely do, which is interesting.
So we have this new agent called Deep Root Cause Analysis Agent.
So this is something that you unleash on big problems in a post-mortem sense.
So meaning problem already happened and
You're trying to understand why that was, and you have a lot of time, so you have a lot of research time.
You don't have to be counting milliseconds necessarily.
So when this thing is launched, it quickly formulates an opinion, a theory about what it is based on all the available data, all the snapshot data that was handed to it.
But it has agency.
So in fact, when you say agentic AI, what that really means is, hey, do you have a system that can take initiative to dig into data and come up with an outcome?
Come up with an outcome that is towards, that is in the trajectory that you think it should do.
So for us, that's root cause analysis, meaning we task our agents to say, hey, here's all the telemetry data that we have.
Here are all the data connectors that you might want to pull in in an agentic manner if you want.
And I need you to get to the bottom of this and do a deep root cause analysis on this.
And when you test this agent, like I said, it formulates a...
a hypothesis, and then this hypothesis is then passed to other sub-agents in the system.
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