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AI Agents News 25 June 2025 - 10 September 2025

Agentic AI Revolution: How Autonomous, Goal-Driven AI Agents Are Reshaping Our World

Agentic AI Revolution: How Autonomous, Goal-Driven AI Agents Are Reshaping Our World

Comprehensive Overview of Agentic AI What Is Agentic AI (and How Is It Different from Traditional AI)? Agentic AI, often described as autonomous, goal-oriented AI, refers to AI systems endowed with a form of “agency.” In practical terms, an agentic AI can make independent decisions and take actions in pursuit of an objective, without needing a human to prompt each step. It’s a step beyond traditional AI models that simply respond to explicit inputs. For example, a classic AI system (say, a chess program or a language model like ChatGPT) generates outputs only when prompted and doesn’t initiate further action
LLMOps Boom: The 2025 AI Agent Platform Landscape Unveiled

LLMOps Boom: The 2025 AI Agent Platform Landscape Unveiled

Key Facts & Takeaways Market Spend by Stack Layer: From Data to Deployment The LLMOps ecosystem can be viewed in stack layers – from the infrastructure and data foundations up through model orchestration and finally evaluation/monitoring. Each layer is attracting significant investment as enterprises build out end-to-end GenAI capabilities: Enterprise Adoption Trends and Use Cases Across Industries Enterprise adoption of large language models and AI agents has accelerated dramatically in the past 18 months, cutting across virtually every sector. Where are companies actually deploying LLMs, and to what end? A few key trends and use cases stand out: Despite these
Everything You Need to Know About Google Gemini CLI: Features, News, and Expert Insights

Google’s Gemini CLI Just Dropped—Here’s Why This Free, Open‑Source AI Agent Could Replace Your Favorite Coding Tool

Gemini CLI is a command‑line AI agent that passes natural-language prompts to Gemini 2.5 Pro and returns structured responses, code, or multimedia within the terminal. Gemini 2.5 Pro supports a 1,000,000-token context window, about 50–100× larger than mainstream LLMs, enabling repository-scale reasoning. The CLI integrates with Veo for video, Imagen for images, and Google Search via the Model Context Protocol (MCP) to handle multimodal tasks. During the preview, individuals can issue 60 requests per minute and 1,000 per day. Google released the entire Gemini CLI codebase under the Apache 2.0 license on GitHub, inviting pull requests and forks. Taylor Mullen,
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