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- ***Agentic AI***: Systems that can *plan*, *reason*, and *take action* to *accomplish tasks* with  *minimal human intervention*.
	- Certainly! Here's the revised text with grammatical corrections:
	- ***Agentic AI***: Systems that can *plan*, *reason*, and *take action* to *accomplish tasks* with *minimal human intervention*.
		- - AI agents extend the capabilities of LLMs in the following dimensions:
		- - *Integrating memory* to retain and recall information across interactions
		- - *Tool use* to utilize external tools, APIs, and databases
		- - *Decision-making* to plan and execute multi-step workflows
		- - AI agents will continue to refine their ability to *reason*, *plan*, and *act*.
- The **development of agentic-based AI** is a natural progression from *statistical modeling* to *deep learning* and now to *reasoning-based systems*
	- This evolution marks a shift from predictive models to autonomous systems capable of dynamic decision-making.
- The **main challenges with raw LLMs** are the following:
	- *Context window limitations*: The context window typically range from 2,000 to 128,000 tokens and this create the following challenges:
		- *Document processing*: long documents must be chunked to deal with context limits
		- *Conversation history*: A proper memory management is required to maintain infromation across extended conversations.
		- *Cost management*: It is necessary to make efficient token use, because most providers charge based on token count.
	- *Limited tool orchestration:* to execute complex workflows a proper infrastructure is needed to discover tools and manage tool interactions across multiple turns.
	- *Task coordination challenges*: structured control mechanisms are require to manage with LLMs multi-step workflows
- **LangChain**
	- Open-source framework and venture-backed company based in San Francisco
	- Main features:
		- *Composable workflows*: the LCEL - LangChain Expression Language permits to break down complex tasks into modulare components that can be assembled. This enable the orchestration of multiple processing steps.
		- *Integration ecosystem:* it provides interfaces for all generative components i.e., LLMs, embeddings, vector databases, document loaders, search engines. This will permit to switch between providers without rewriting core logic.
		- *Unified model access:* interfaces to different language and embedding models
	- Application development concepts:
		- *Memory and state management*
		- *Agent architecture*
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