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title: The Agentic SOC – From AI Theater to Real Defense
description: A discussion between Recorded Future co-founders and Accenture&#x27;s Managing Director of Security Operations EMEA covers how SOCs can move past &#x27;AI theater&#x27; and...
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og:description: A discussion between Recorded Future co-founders and Accenture&#x27;s Managing Director of Security Operations EMEA covers how SOCs can move past &#x27;AI theater&#x27; and...
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# The Agentic SOC – From AI Theater to Real Defense

**[Recorded Future Blog](https://daily.dev/sources/recorded-future-blog)** · 6 min read · 4 upvotes · 1 comments

## Summary

A discussion between Recorded Future co-founders and Accenture's Managing Director of Security Operations EMEA covers how SOCs can move past 'AI theater' and toward measurable value from AI. Key themes include defining concrete KPIs (cost, risk, speed) rather than deploying AI for its own sake, new agentic risks like indirect prompt injection and visibility gaps in traditional SIEMs, and a shift from post-event observability to proactive constraints on agent compute and communication. The panel predicts defensive timelines will compress from days to seconds within a few years, changing the analyst's role from alert handling to agent oversight and architecture.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.recordedfuture.com/blog/agentic-soc-real-defense>

## Questions this post answers

### What is indirect prompt injection in the context of AI security agents?

Indirect prompt injection is a threat where AI agents are manipulated through the very instructions or content they read and process, rather than through direct attacker input. It represents a distinct, structural threat vector unique to agentic systems, since traditional SIEM and monitoring platforms are not built to observe the internal state of an LLM or detect this kind of manipulation.

_Teams building agent-based defenses can follow evolving prompt injection research on daily.dev._

### Why can't traditional SIEM platforms fully monitor AI security agents?

Traditional SIEM and monitoring platforms can observe external agent behavior, such as network ports and communications, but cannot see what happens inside an LLM's internal reasoning. This creates a visibility gap for agentic systems, prompting security teams to shift from post-event observability toward proactive controls like compute, communication, and delegation budgets placed on each agent.

_Anyone architecting agent oversight can track observability gaps in AI tooling on daily.dev._

## Community discussion

Top comments from developers on daily.dev.

**@kartiknvj** · 2 upvotes

> The shift from alert handling to agent oversight is the honest version of what "AI in the SOC" actually does to the job. I'd add that oversight only works if you can trace why an agent took an action, otherwise you've swapped alert fatigue for unauditable automation. How are you measuring the risk KPI now that indirect prompt injection is part of the surface?

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---

Tags: [#security](https://daily.dev/tags/security), [#ai-agents](https://daily.dev/tags/ai-agents), [#prompt-injection](https://daily.dev/tags/prompt-injection)

[View this post on daily.dev](https://daily.dev/posts/the-agentic-soc-from-ai-theater-to-real-defense-f2t95kiuh)

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