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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Eye On A.I. · AI Agents Fixing Your IT Before You Even Know Something Broke | Erhan Giral & Ryan Manning, BMC Helix · 3 Aug 2026 podcast

Like for instance, if you ask our model, what's the weather like in France today?

It will give you an answer, it will do some tool calls and figure out the answer.

But in that prompt, nothing will signal that, oh, they're asking me a question about like a root cause analysis on a mainframe Z system.

So it will detect that and it won't activate that part of its training.

Right.

But if the question is, hey, I'm in big trouble, how do I reinitialize this L part on my mainframe?

Then that activation layer kicks in and says, oh, okay, so it looks like they're talking about this other thing that I was trained on, and it loads those weights and biases that you create during your training.

And then those weights and biases sway the network just enough so that whatever it generates, plan or output, summarization or what have you, is now affected by

affected by that training.

We found, and it's not just us, but also this is throughout academia and now also in the industry, the best way to generalize a data set, a training data set is really to go through these trainings so that the model can reason about the native

in a model native way.

So that's why, you know, we've been pursuing this for some time now.

Yeah.

So when we first started, we just started with a textual recipe that we would hand off to the user and say, okay, so here's what you need to do.

This is the recipe I need you to follow.

And maybe there's like eight to 12 steps in there.

And then

We called it a day, but of course you quickly realize, well, okay, first of all, some of these actions are very automatable.

Like once we break it down to a problem, a problem into little steps, it already automatically suggests automation.

So in that regard, what we first said was, okay, so a lot of these are, first, let's verify the problem.

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