All news with #agentic ai tag

🧭 This post explains when to use sub-agents versus packaging agents as tools when building multi-agent systems with Google's Agent Development Kit (ADK). It contrasts agents-as-tools — encapsulated, stateless specialists invoked like deterministic function calls — with sub-agents, which are stateful, context-aware delegates that manage multi-step workflows. The guidance highlights trade-offs across task complexity, context sharing, reusability, and autonomy, and illustrates the patterns with data-agent and travel-planner examples to help architects choose efficient, scalable designs.

🚀 Deploy the official n8n Docker image to Cloud Run in minutes to run scalable, serverless AI workflows. Cloud Run scales from zero and persists data in Cloud SQL while you only pay for active usage. The post shows how to call Gemini as the agent LLM and optionally connect workflows to Google Workspace via OAuth for Gmail, Calendar, and Drive. For production, follow the n8n docs to add Secrets Manager, Cloud SQL, and Terraform-based deployment.

🤖 This recap of The Agent Factory features Logan Kilpatrick from Google DeepMind demonstrating vibe coding in Google AI Studio, a Build workflow that turns a natural-language app idea into a live prototype in under a minute. Live demos included a virtual food photographer, grounding with Google Maps, the AI Studio Gallery, and a speech-driven "Yap to App" pair programmer. The episode also surveyed agent ecosystem updates—Veo 3.1, Anthropic Skills, and Gemini improvements—and highlighted the shift from models to action-capable systems.

🤖 Google’s open-source Agent Development Kit (ADK) simplifies creating autonomous AI agents that use LLMs such as Gemini as their reasoning core. The post presents three hands-on codelabs that guide developers through building a personal assistant agent, adding custom and third-party tools, and orchestrating multi-agent workflows. Each lab demonstrates practical patterns—scaffolding an agent, integrating tools like Google Search and LangChain components, and using Workflow Agents and session state to pass information—so teams can progress from experiment to production-ready agent systems.

🔔 This edition of the Threat Source newsletter opens with Bonfire Night and the 1605 Gunpowder Plot as a narrative hook, tracing how Guy Fawkes' image became a symbol of protest and hacktivism. It spotlights Cisco Talos research, including a new Incident Response report and a notable internal phishing case where compromised O365 accounts abused inbox rules to hide malicious activity. The newsletter also features a Tool Talk demonstrating a proof-of-concept that equips autonomous AI agents with real-time threat intelligence via LangChain, OpenAI, and the Cisco Umbrella API to improve domain trust decisions.

🏥 Microsoft and UiPath describe how integrated agents from Azure AI Foundry and UiPath, orchestrated by UiPath Maestro, can operationalize AI within clinical workflows to surface and act on incidental radiology findings. The workflow uses UiPath medical record summarization agents to flag findings, Azure AI Foundry imaging agents to analyze PACS images and prior results, and UiPath agents to aggregate and forward consolidated follow-up reports to ordering clinicians. Microsoft says this agentic approach accelerates decision-making, reduces physician workload, and improves outcomes while maintaining compliance with DICOMweb and FHIR standards.

🚀 Vertex AI Agent Builder is Google Cloud's integrated platform to build, scale, and govern production AI agents. The update expands the Agent Development Kit (ADK) and Agent Engine with configurable context layers to reduce token usage, an adaptable plugins framework, and new language SDK support including Go. Production features include observability, evaluation tools, simplified deployment via the ADK CLI, and strengthened governance with native agent identities and Model Armor protections.

🧭 This guide summarizes Multi-Agent System (MAS) fundamentals and explains how Google’s Agent Development Kit (ADK) helps developers assemble cooperating agents to solve complex tasks. It outlines three agent roles — LLM Agents for reasoning, Workflow Agents for orchestration, and Custom Agents for bespoke logic — and describes hierarchical organization and orchestration patterns (sequential, parallel, loop). The post also reviews communication options (shared state, LLM delegation, explicit invocation) and points developers to samples and codelabs for rapid prototyping.

🤖 CrowdStrike announced new specialized agents and an orchestration layer designed to accelerate SOC operations and automation. The launch includes a Data Onboarding Agent, a Foundry App Creation Agent, and an updated Exposure Prioritization Agent to simplify pipeline creation, app development, and continuous authenticated scanning. Integrated with Charlotte Agentic SOAR and Charlotte AI, these agents enable coordinated, machine-speed workflows while keeping analysts in control.

🚀 CrowdStrike introduces Charlotte Agentic SOAR, an orchestration layer that integrates Falcon Fusion SOAR, Falcon Next‑Gen SIEM, Charlotte AI and AgentWorks to enable intelligent, no‑code agents. The offering includes an Agentic Security Workforce of purpose-built AI agents, an Agent Builder for plain-language agent creation, a visual workflow orchestrator with hundreds of connectors, and unified case management. Together these elements let analysts set guardrails while agents reason, decide, and act at machine speed to accelerate detection and response and reduce repetitive analyst tasks.

🤝 Getting an enterprise-grade generative AI platform in place is a milestone, not the finish line. Sustained, distributed adoption comes from embedding AI into everyday processes through an organized AI champions network that brings enablement close to the work. Champions act as multipliers — translating strategy into team behaviors, surfacing blockers and use cases, and accelerating normalized use. With structured onboarding, rotating membership, monthly working sessions, and direct ties to the core AI program, the network converts tool access into measurable business impact.

🛍️ Google Cloud outlines UX and implementation guidance for building conversational AI agents tailored to online shopping. The article presents seven practical design principles — including multimodal input, intelligent query handling, rich visual presentation, and clear trust signals — that improve discovery and reduce friction. It highlights features like predictive assistance and contextual clarification and offers a Figma component library plus developer resources to accelerate deployment.

🛡️ OpenAI has introduced Aardvark, a GPT-5-powered autonomous agent designed to scan, reason about, and patch code with the judgment of a human security researcher. Announced in private beta, Aardvark maps repositories, builds contextual threat models, continuously monitors commits, and validates exploitability in sandboxed environments before reporting findings. When vulnerabilities are confirmed, it proposes fixes via Codex and re-analyzes patches to avoid regressions. OpenAI reports a 92% detection rate in benchmark tests and has already identified real-world flaws in open-source projects, including ten issues assigned CVE identifiers.

🔒 Unit42 researchers Jay Chen and Royce Lu describe agent session smuggling, a technique where a malicious AI agent exploits stateful A2A sessions to inject hidden, multi‑turn instructions into a victim agent. By hiding intermediate interactions in session history, an attacker can perform context poisoning, exfiltrate sensitive data, or trigger unauthorized tool actions while presenting only the expected final response to users. The authors present two PoCs (using Google's ADK) showing sensitive information leakage and unauthorized trades, and recommend layered defenses including human‑in‑the‑loop approvals, cryptographic AgentCards, and context‑grounding checks.

🤖 Agentic AI burst into prominence with promises of streamlining operations and accelerating productivity. This Special Report assesses what's practical versus hype, examining the current state of agentic AI, the primary deployment challenges organizations face, and practical lessons from real-world success stories. It highlights business processes suited to agentic agents, criteria for evaluating development tools, and how LinkedIn built a platform. The report also outlines near-term expectations and adoption risks.

🔐 Aembit today announced Aembit Identity and Access Management (IAM) for Agentic AI, introducing Blended Identity and the MCP Identity Gateway to assign cryptographically verified identities and ephemeral credentials to AI agents. The solution extends the Aembit Workload IAM Platform to enforce runtime policies, apply least-privilege access, and maintain centralized audit trails for agent and human actions. Designed for cloud, on‑premises, and SaaS environments, it records every access decision and preserves attribution across autonomous and human-driven workflows.

🤖 AWS Marketplace now offers flexible pricing and simplified deployment for AI agents and tools, including contract-based and usage-based options for Amazon Bedrock AgentCore Runtime containers. The update also streamlines OAuth credential management via Quick Launch for API-based agents and allows supported remote MCP servers procured through Marketplace to be used as MCP targets on AgentCore Gateway. These enhancements reduce deployment complexity and give partners more pricing flexibility while improving scalability for customers.

🔐 This post proposes a lightweight, crowd-curated registry for bots and agents to simplify discovery of public keys used for cryptographic Web Bot Auth signatures. It describes a simple list format of URLs that point to signature-agent cards—extended JWKS entries containing operator metadata and keys—and shows how registries enable origins and CDNs to validate agent signatures at scale. Examples and a demo integration illustrate practical adoption.

🚀 At GitHub Universe 2025, Microsoft and GitHub presented a vision for agentic development that lets developers see, steer, and build across autonomous agents. The event introduced platform capabilities like Agent HQ, a prompt-first AI Toolkit for VS Code, and the GA release of Azure MCP Server. Announcements focused on enterprise-grade security, standards-based integration, and faster, more intuitive agent creation and governance.

🤖 AWS announced an open-source AI agent context package for AWS IoT Greengrass that provides ready-to-use instructions, examples, and templates to accelerate edge device application development. The package is published on GitHub under the Creative Commons Attribution Share Alike 4.0 license and is designed to integrate with generative AI tools such as Amazon Q. Developers can clone the repository to jumpstart creation, testing, and fleet-wide deployment workflows across supported Regions.