Arpy Dragffy Guerrero

speaker

627 appearances 7 recordings 1 series first heard May 2026 last heard 6 Aug

Arpy Dragffy Guerrero’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months

Recordings per month over the last 12 months — 7 in all, peaking in Jun 2026 with 3.

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So what you see across organizations right now is a real financial and strategic liability building.

The cost of model calls is growing faster than the value that they're creating.

Half built agents are floating around unmoderated.

VIB-coded experiments are multiplying the security surface and the compounding inconsistency of who is actually getting better results.

So the top adopters, the ones who are running genuinely autonomous workflows, are seeing massive productivity gains.

But mostly everyone else is just still learning to prompt.

And what about when the evidence isn't there, right?

Executives are reaching for blunter instruments.

So C-suite leaders are under more pressure to turn AI investments into ROI than most of their teams actually understand.

The board expects it, investors expect it.

And when you can't show the path, the pressure to make a dramatic move becomes really real.

So layoff or redesign, restructuring around AI native models, it's happening faster than the underlying thinking often warrants.

But it's happening because so few organizations have found a path to incremental AI value creation.

So when you can't demonstrate this path, the blunt instrument comes out.

These executives are not being careless per se.

They are operating in a vacuum of demonstrated ROI with very little time left to produce.

Let's get really concrete for a second about what value creation and on the flip side, value stalling actually look like.

Because these terms are getting thrown around without any grounding or context.

So value creation is increased throughput, increased velocity, more shipped with the same team, and measurable market outcomes.

So a support team that handled 40 cases a day is now handling 200 because the AI handles tier one resolution and the humans handle the judgment.

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