Agentic AI
Hello! Welcome to the latest edition of Fin AI Briefings. This time, we’ll delve into what is happening in the world of Agentic AI.
Everyone is talking about Agentic AI, and enterprises are exploring ways to integrate it. In the previous edition, we listed Agentic AI as one of the main trends of 2025. You can read it here.
Agentic AI elevates automation to systems with the ability to independently identify objectives, strategize solutions, and carry out tasks from start to finish.
When end-users interact with Gen AI chatbots, prompting is an important part of the interaction to get the best outcome. Agentic AI, however, acts on behalf of the user.
For enterprises, it works across complex workflows. It does so by using advanced reasoning to perform complex, multi-step workflows.
Agentic AI will bring a lot of benefits. Let’s learn how it is the next frontier of autonomous intelligence.
Why Memory Matters for AI Agents: Insights from Nikolay Penkov [Arya.ai + Nikolay Penkov]
Penkov identifies three primary types of memory essential for AI agents: Procedural Memory, Semantic Memory, and Episodic Memory. He also emphasizes balancing functionality with ethical considerations, ensuring that AI agents safeguard personal information, avoid bias, and prevent echo chambers from past user prompts.
Autonomous Finance: Guide to Intelligent Automation [Arya.ai]
The post explores intelligent financial systems that operate with minimal human intervention. It highlights the distinction between autonomous finance and agentic AI—while both enhance efficiency and decision-making in financial operations, autonomous finance focuses on self-governing financial processes, whereas agentic AI involves intelligent agents that can independently perform tasks within financial ecosystems.
Multiagent Planning in AI [Geeks for Geeks]
Multi-agent planning in AI involves the coordination of multiple autonomous agents to achieve shared objectives. Each agent operates independently, yet their actions are interdependent, necessitating collaboration to ensure coherent and efficient outcomes.
AI Agents in Finance [Arya.ai]
AI agents are transforming the finance industry by autonomously performing a range of tasks. These agents can think critically in challenging situations and adapt. The integration of LLMs further enhances AI agents' capabilities, which allows them to understand context and generate coherent responses.
The Anatomy of Agentic AI [Ali Arsanjani]
This post delves into the structure and functioning of agentic AI systems, emphasizing their core components and interactions. He identifies agents and the environments they engage with as the foundational elements of agentic AI architectures. Understanding these interactions is crucial for developing systems capable of autonomous decision-making and adaptation in complex scenarios.
Long-term Memory for AI Agents [Debmalya Biswas]
This post examines the limitations of vector databases in managing memory for agentic AI systems. While vector databases are efficient for handling unstructured data in generative AI applications, they fall short in supporting the complex, structured memory requirements of agentic AI.
From SLMs to Superpowers? Decoding the Agentic AI Hype [Finextra Research]
Erica Andersen discusses the evolution from SLMs to Agentic AI, and how Agentic AI enhances these models by granting them autonomy to perform actions like summarizing documents or controlling devices. The rebranding to "Agentic AI" emphasizes this shift towards more active systems.
What are AI APIs, and How Do They Work? [Arya.ai]
The article explains that AI APIs are programming interfaces that enable developers to incorporate artificial intelligence capabilities into their applications without building complex AI models from scratch. These APIs accept various data inputs and return outputs like translations, analyses, or forecasts.
Agentic AI: Opportunities for Indian Tech [Debjani Ghosh]
For India's IT services and SaaS companies, Agentic AI presents opportunities to offer higher-value services, such as predictive analytics and real-time decision support. Indian tech, by embracing Agentic AI, can position itself at the forefront of technological innovation.
👉🏼 Video: What is The Difference Between Generative AI And Agentic AI? [Bernard Marr]
👉🏼 Article: AI-Powered Agents in Action: How We’re Embracing This New ‘Agentic’ Moment at Microsoft [Microsoft]
👉🏼 Podcast: Building Agentic AI for the Enterprise [Seedtoscale]
👉🏼 Article: Banking Automation - How Artificial Intelligence is Shaping Modern Banking? [Arya.ai]
👉🏼 Video: Vertical AI Agents Could Be 10X Bigger Than SaaS [Y Combinator]
👉🏼 Article: Is Now the Right Time to Invest in Implementing Agentic AI? [CIO]
👉🏼 Video: The Future of AI Agents With Dharmesh Shah [Inbound]
👉🏼 Podcast: Agents and the State of AI [Today in Tech]
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