Intelligent Agent - Revision history

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 ==References==
+* See also wiki on [[Agent]]
 [[Category: Artificial Intelligence]]
 [[Category: User Experience]]

← Older revision		Revision as of 23:22, 14 November 2025
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	"If every tool, when ordered, or even of its own accord, could do the work that befits it... then there would be no need either of apprentices for the master workers or of slaves for the lords" - Aristotle Politics		"If every tool, when ordered, or even of its own accord, could do the work that befits it... then there would be no need either of apprentices for the master workers or of slaves for the lords" - Aristotle Politics
		+
		+	An autonomous agent could be one that is in training or seeking current knowledge so it can be up-to-date when it is next called to deal with a prompt.

	==Context==		==Context==

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 One way to increase a human's presence in a digital ecosystem is to create a always present agent with a persistent web connection that is intelligent enough to carry out interactions with others on the web that may, or may not, interact by way of their own Intelligent Agent. Here we discussed a single agent, but there are reasons for a human to have more than one [[Persona]] (qv.), each with strikingly different behaviors, for example work and home.
-Since the Intelligent Agent will need to represent your position when you are not present, or perhaps no longer alive, it will need to acquire some level of permission to act on your behalf. One reason to limit yourself to one [[Persona]] at one Agent would be to avoid competing with yourself for some asset.
+Since the Intelligent Agent will need to represent your position when you are not present, or perhaps no longer alive, it will need to acquire some level of permission to act on your behalf. One reason to limit yourself to one [[Persona]] at one Agent would be to avoid competing with yourself for some asset. On the other hand using a work persona versus a home persona would bring up different past context for continuity.
 While there are use cases where a [[Delegate]] is a natural human, as in the case of an EMT or a caregiver, that case will not be further developed on this page.

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 ==Context==
-One way to increase a human's presence in a digital ecosystem is to create a always present agent with a persistent web connection that is intelligent enough to carry out interactions with others on the web that may, or may not, interact by way of their own Intelligent Agent. Here we discussed a single agent, but there are reasons for a human to have more than one persona; each with strikingly different behaviors, for example work and home.
+One way to increase a human's presence in a digital ecosystem is to create a always present agent with a persistent web connection that is intelligent enough to carry out interactions with others on the web that may, or may not, interact by way of their own Intelligent Agent. Here we discussed a single agent, but there are reasons for a human to have more than one [[Persona]] (qv.), each with strikingly different behaviors, for example work and home.
-Since the Intelligent Agent will need to represent your position when you are not present, or perhaps no longer alive, it will need to acquire some level of permission to act on your behalf. One reason to limit yourself to on persona would be to avoid competing with yourself for some asset.
+Since the Intelligent Agent will need to represent your position when you are not present, or perhaps no longer alive, it will need to acquire some level of permission to act on your behalf. One reason to limit yourself to one [[Persona]] at one Agent would be to avoid competing with yourself for some asset.
 While there are use cases where a [[Delegate]] is a natural human, as in the case of an EMT or a caregiver, that case will not be further developed on this page.

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 https://www.cio.com/article/4003880/how-ai-agents-and-agentic-ai-differ-from-each-other.html
-"If every tool, when ordered, or even of its own accord, could do the work that befits it... then there would be no need either of apprentices for the master workers or of slaves for the lords" - Aristotle
+"If every tool, when ordered, or even of its own accord, could do the work that befits it... then there would be no need either of apprentices for the master workers or of slaves for the lords" - Aristotle Politics
 ==Context==

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 # Enterprise deployed autonomous [[Intelligent Agent]].
 # Deploying swarms of [[Intelligent Agent]]s.
 https://www.cio.com/article/4003880/how-ai-agents-and-agentic-ai-differ-from-each-other.html

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 ==Random Notes==
-Dazza Greenwood
+Stefan Eder  AI and Law - Law and AI, Legal Informatics, Insolvenzverwaltung, Restrukturierung, Immobilientransaktionen do ut des
-This is why I don’t use any frameworks anymore. I’ve gone back to just hand, rolling all my agents, and the orchestration, and the memory, among other capabilities manually by (vibe-enhanced) hand mostly in python. But when I do feel like using a framework, I always reach first for the OpenAI Agent SDK and, curiously, frequently use it mostly with the Anthropic and Google API’s. It has a lot of design patterns that are handy but pretty agnostic to how I need to flow and componentize any given agent system, and I like that it’s not opinionated about my architecture or system capabilities.
+Kenny Vaneetvelde  Check out Atomic Agents, the result of all my effort to bring order to the chaos: https://github.com/BrainBlend-AI/atomic-agents
 ==References==

← Older revision		Revision as of 19:58, 15 July 2025
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	In order to understand why an [[Intelligent Agent]] it is likely that an audit trail be maintained for users to review the decisions that have been made on their behalf and at lease some information on why that decision was reached.		In order to understand why an [[Intelligent Agent]] it is likely that an audit trail be maintained for users to review the decisions that have been made on their behalf and at lease some information on why that decision was reached.

		+	==Random Notes==
		+
		+
		+	Dazza Greenwood
		+
		+	This is why I don’t use any frameworks anymore. I’ve gone back to just hand, rolling all my agents, and the orchestration, and the memory, among other capabilities manually by (vibe-enhanced) hand mostly in python. But when I do feel like using a framework, I always reach first for the OpenAI Agent SDK and, curiously, frequently use it mostly with the Anthropic and Google API’s. It has a lot of design patterns that are handy but pretty agnostic to how I need to flow and componentize any given agent system, and I like that it’s not opinionated about my architecture or system capabilities.
		+
		+
		+	Stefan Eder
		+
		+	AI and Law - Law and AI, Legal Informatics, Insolvenzverwaltung, Restrukturierung, Immobilientransaktionen do ut des
		+
		+
		+	Kenny Vaneetvelde
		+
		+	Check out Atomic Agents, the result of all my effort to bring order to the chaos: https://github.com/BrainBlend-AI/atomic-agents
		+
		+	No catch, no SaaS, just a desire to spread the love for quality, well thought-out code. Though feel free to reach out to us at BrainBlend AI: Where AI Meets Strategy if you ever need help with any of your projects, want an (agentic) AI project done for you end-to-end, need extra people in your team, etc...
	==References==		==References==

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 *Fouad Bousetouane Agentic Systems: A Guide to Transforming Industries with Vertical AI Agents https://arxiv.org/abs/2501.00881v1
-The evolution of agentic systems represents a significant milestone in artificial intelligence and modern software systems, driven by the demand for vertical intelligence tailored to diverse industries. These systems enhance business outcomes through adaptability, learning, and interaction with dynamic environments. At the forefront of this [[Revolution]] are Large Language Model (LLM) agents, which serve as the cognitive backbone of these intelligent systems. In response to the need for consistency and scalability, this work attempts to define a level of standardization for Vertical AI agent design patterns by identifying core building blocks and proposing a \textbf{Cognitive Skills } Module, which incorporates domain-specific, purpose-built inference capabilities. Building on these foundational concepts, this paper offers a comprehensive introduction to agentic systems, detailing their core components, operational patterns, and implementation strategies. It further explores practical use cases and examples across various industries, highlighting the transformative potential of LLM agents in driving industry-specific applications.
+The evolution of agentic systems represents a significant milestone in artificial intelligence and modern software systems, driven by the demand for vertical intelligence tailored to diverse industries. These systems enhance business outcomes through adaptability, learning, and interaction with dynamic environments. At the forefront of this [[Revolution]] are Large Language Model (LLM) agents, which serve as the cognitive backbone of these intelligent systems. In response to the need for consistency and scalability, this work attempts to define a level of standardization for Vertical AI agent design patterns by identifying core building blocks and proposing a {Cognitive Skills} Module, which incorporates domain-specific, purpose-built inference capabilities. Building on these foundational concepts, this paper offers a comprehensive introduction to agentic systems, detailing their core components, operational patterns, and implementation strategies. It further explores practical use cases and examples across various industries, highlighting the transformative potential of LLM agents in driving industry-specific applications.
 ===[[KWAAI]]===