Ergün Mercan
speaker
129 appearances
1 recordings
1 series
first heard Jul 2026
last heard 13 Jul
Ergün Mercan’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.
Appearances
It introduces highly variable tokens spent per decision path.
Without strict operational metering, rate limiting and context window optimization, your token costs can easily spiral out of control.
So you have to actively connect the compute cost of every single decision path directly to the business outcome.
In terms of setting the scope, starting small is non-negotiable.
Pick a high-impact, low-complexity use case, for example, like automating FAQs or streamlining a specific customer service workflow.
This lets you prove value quickly and build confidence before scaling.
Operators should introduce autonomy step by step, gradually expanding their capabilities.
So start with assisted workflows, then slowly increase the AI's role as you build trust and refine the system.
The biggest mistake is rushing and aiming for too much too fast.
They should think about evolution and maybe not the revolution, right?
But of course, a smaller operational scope does not mean you can cut corners on core infrastructure.
The quality implementation is paramount.
Yeah.
We do have the guardrail systems for different purposes.
So it requires a bit of preparation and almost like an R&D kind of optimization for data guardrails.
But data quality and runtime governance must be always top-notch.
Your AI agents
are only as good as the data they are trained on so you have to have a clean relevant and well structured data and you cannot rely on you know passive post-run monitoring that's uh that's uh the output is already gone
So automated compliance and security overviews needs to be introduced continuously to audit the live reasoning paths as well.
If an agent deviates from standard operating boundaries, veers excessively in tool usage or risks exposing data,
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