{"id":13108,"date":"2026-06-28T12:52:28","date_gmt":"2026-06-28T12:52:28","guid":{"rendered":"https:\/\/sawahsolutions.com\/range\/agentic-ai-tool-aims-to-give-us-commanders-new-target-options-within-seconds\/"},"modified":"2026-06-28T12:52:29","modified_gmt":"2026-06-28T12:52:29","slug":"agentic-ai-tool-aims-to-give-us-commanders-new-target-options-within-seconds","status":"publish","type":"post","link":"https:\/\/sawahsolutions.com\/range\/agentic-ai-tool-aims-to-give-us-commanders-new-target-options-within-seconds\/","title":{"rendered":"Agentic-AI tool aims to give US commanders new target options \u2018within seconds\u2019"},"content":{"rendered":"
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A new agentic-AI tool will continuously scan intelligence feeds and operational networks to provide U.S. military commanders with targeting options \u201cwithin seconds,\u201d the Pentagon announced Thursday.<\/p>\n

Dubbed Agent Network, the new tool will employ \u201cagents\u201d\u2014artificial-intelligence entities that perform tasks on behalf of a user, such as running a scheduled search or executing an email campaign\u2014to \u201ccontinuously scan defense intelligence and operational systems, translating findings into clearly presented options,\u201d said a press release, which added: \u201cAgent Network does not autonomously select or strike targets; it ensures commanders remain in charge of every decision.\u201d<\/p>\n

It is one of seven \u201cpace-setting\u201d projects originally unveiled in January along with a new Pentagon AI strategy. Key contractors in the Agent Network effort include Lumbra and Palantir, which already handles much targeting analysis through its Maven Smart Systems contract.<\/p>\n

But expectations for what agents can currently do may be running ahead of reality. \u201cTasks that AI agents are instructed to perform can clearly have computational complexity beyond\u201d what current large language model architectures can handle, Vishal Sikka\u2014a former CEO of SAP\u2014wrote last July.<\/p>\n

Citing the seminal Time-Hierarchy Theorem, Sikka noted that transformer models approach difficult tasks and simple ones using the same mechanical formula. These models can only perform so many operations per \u201ctoken,\u201d which is the way large language models understand word concepts. Even dealing with seemingly simple concepts can require a large number of tokens. Because of this limitation, there is no way to get a transformer-based model to not hallucinate when the task that you give it is more complex than it has tokens to bring to that task.<\/p>\n

\u201cDespite their obvious power and applicability in various domains, extreme care must be used before applying LLMs to problems or use cases that require accuracy, or solving problems of non-trivial complexity,\u201d Sikka concluded.<\/p>\n

But Illia Pashkov, founder of SINT Labs and editor of The Agent Times<\/em>, cautioned against underestimating agents\u2019 potential.\u00a0<\/p>\n

\u201cAgentic AI quietly stopped being a demo this year,\u201d Pashkov said. \u201cIt’s drafting code, clearing support queues, grinding through back-office work in finance and healthcare, and now it’s reading intelligence. The speed is not hype. I’ve watched these systems compress weeks of analyst work into an afternoon.\u201d<\/p>\n

But their capabilities also bring risks\u2014more than people accustomed to working with common AI chatbots might realize. Private-sector companies that have rushed to put AI agents to work are already seeing problems, Pashkov said, pointing to a company whose agent wiped a live production database. Unless carefully implemented, agents can\u2019t tell when they\u2019re going wrong.<\/p>\n

\u201cThe danger was never a dumb agent; it’s a confident one running without a leash, a logbook, or a human who owns the call,\u201d he said.\u00a0<\/p>\n

A host of Defense Department offices and teams are beginning to deploy agent systems, said one DOD intelligence security official who is not directly affiliated with the Agent Network program. The official described an atmosphere of enthusiasm.\u00a0<\/p>\n

\u201cThere are so many opportunities to leverage the DOD Enterprise capabilities and allow people to build their own agents,\u201d they said.<\/p>\n

But the official allowed that keeping track of how every agent is performing is a major challenge. Governing all of them will be nearly impossible.\n\n<\/svg><\/p>\n<\/div>\n