ibl.ai Agentic AI Blog

Insights on building and deploying agentic AI systems. Our blog covers AI agent architectures, LLM infrastructure, MCP servers, enterprise deployment strategies, and real-world implementation guides. Whether you are a developer building AI agents, a CTO evaluating agentic platforms, or a technical leader driving AI adoption, you will find practical guidance here.

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We analyze key research from leading institutions and labs including Google DeepMind, Anthropic, OpenAI, Meta AI, McKinsey, and the World Economic Forum. Our content includes detailed analysis of reports on AI agents, foundation models, and enterprise AI strategy.

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CTOs, engineering leads, and AI architects turn to our blog for guidance on agent orchestration, model evaluation, infrastructure planning, and building production-ready AI systems. We provide frameworks for responsible AI deployment that balance capability with safety and reliability.

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Google: Agents – Architecture, Tools, and Applications

Jeremy WeaverJanuary 6, 2025
Premium

Generative AI agents extend language models by using external tools and orchestrated reasoning frameworks like ReAct and Chain-of-Thought, with practical implementations shown through examples such as LangChain and Vertex AI.

Google: Agents – Architecture, Tools, and Applications



Summary of Read Full Report

This whitepaper explains Generative AI agents, programs extending the capabilities of language models. Agents achieve goals by using tools (Extensions, Functions, and Data Stores) to access external information and perform actions.

The paper details agent architecture, including the model, tools, and orchestration layer, and explores various reasoning frameworks like ReAct and Chain-of-Thought.

It also discusses methods for enhancing model performance through targeted learning and provides examples using LangChain and Vertex AI. Finally, it summarizes the key components and future directions of agent development.

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Jeremy WeaverApril 4, 2025

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