All news with #agentic ai tag

🛒 PayPal and Google Cloud announced a joint agentic commerce offering that integrates Google Cloud’s Conversational Commerce agent with payments powered by PayPal. The solution leverages the open Agent2Agent (A2A) Protocol and the Agent Payments Protocol (AP2)—which extends A2A and the Model Context Protocol—to enable agent-to-agent payment flows secured by Verifiable Digital Credentials. Merchants can deploy Google’s out‑of‑the‑box conversational agent or build custom agents with the Agent Development Kit (ADK), retaining control over tone, branding, and the customer relationship while benefiting from integrated payment and fraud controls.

🕹️ Google says its AI Studio will enable users to 'vibe code' simple video games by the end of the year. The company claims the tool can automatically select models and wire up APIs to streamline app creation, while noting current limitations for production-ready systems. Product lead Logan Kilpatrick highlighted the potential to broaden access to game creation, and startups like Cursor are pursuing similar next-generation vibe coding tools.

🔬 Researchers at the Max Planck Institute of Biochemistry and Google Cloud created a Proteomics Lab Agent using the Agent Development Kit and Gemini models to provide personalized, multimodal AI guidance for mass spectrometry experiments. The agent analyzes recorded steps to generate publication-ready protocols, detect procedural errors, and capture tacit expertise into a searchable knowledge base. Open-sourced on GitHub, it aims to reduce troubleshooting time and improve reproducibility across labs.

🔒 Cloudflare, in partnership with Visa and Mastercard, explains how Web Bot Auth together with payment-specific protocols can secure agent-driven commerce. The post describes agent registration, public key publication, and HTTP Message Signatures that include timestamps, nonces, and tags to prevent spoofing and replay attacks. Merchants can validate trusted agents during browsing and payment flows without changing infrastructure. Cloudflare also provides an Agent SDK and managed WAF rules to simplify developer adoption and deployment.

🔒 Agentic AI introduces a mounting Zero Trust challenge as autonomous agents increasingly act with inherited or unmanaged credentials, creating orphaned identities and ungoverned access. Ido Shlomo of Token Security argues that identity must be the root of trust and recommends applying the NIST AI RMF through an identity-driven Zero Trust lens. Organizations should discover and inventory agents, assign unique managed identities and owners, enforce intent-based least privilege, and apply lifecycle controls, monitoring, and governance to restore auditability and accountability.

🤖 This post explains how System Integrator partners can build, scale, and manage enterprise-grade AI agents using Google Cloud technologies like Agent Engine, the Agent Development Kit (ADK), and Gemini Enterprise. It summarizes architecture patterns including runtime, memory, the Model Context Protocol (MCP), and the Agent-to-Agent (A2A) protocol, and contrasts managed Agent Engine with self-hosted options such as Cloud Run or GKE. Customer examples from Deloitte and Quantiphi illustrate supply chain and sales automation benefits. The guidance highlights security, observability, persistent memory, and model tuning for enterprise readiness.

🛡️ Bruce Schneier and Barath Raghavan argue that agentic AIs run repeated OODA loops—Observe, Orient, Decide, Act—over web-scale, adversarial inputs, and that current architectures lack the integrity controls to handle untrusted observations. They show how prompt injection, dataset poisoning, stateful cache contamination, and tool-call vectors (e.g., MCP) let attackers embed malicious control into ordinary inputs. The essay warns that fixing hallucinations is insufficient: we need architectural integrity—semantic verification, privilege separation, and new trust boundaries—rather than surface patches.

📡 This recap of the Agent Factory podcast episode, hosted by Annie Wang with guest Ivan Nardini, explains how to evaluate autonomous agents using a practical, full-stack approach. It outlines what to measure — final outcomes, chain-of-thought, tool use, and memory — and contrasts measurement techniques: ground truth, LLM-as-a-judge, and human review. The post demonstrates a 5-step debugging loop using the Agent Development Kit (ADK) and describes how to scale evaluation to production with Vertex AI.

⚙️ Microsoft is introducing Copilot Actions, a Windows 11 Copilot feature that allows AI agents to operate on local files and applications by clicking, typing, scrolling and using vision and advanced reasoning to complete multi-step tasks. The capability will roll out to Windows Insiders in Copilot Labs, extending earlier web-based actions introduced in May. Agents run in isolated Agent Workspaces tied to standard Windows accounts, are cryptographically signed, and the feature is off by default.

🔒 MAESTRO, introduced by the Cloud Security Alliance in 2025, is a layered framework to secure generative and agentic AI in regulated environments such as banking. It defines seven interdependent layers—from Foundation Models to the Agent Ecosystem—and prescribes minimum viable controls, operational responsibilities and observability practices to mitigate systemic risks. MAESTRO is intended to complement existing standards like MITRE, OWASP, NIST and ISO while focusing on outcomes and cross-agent interactions.

🤖 Organizations are adopting agentic AI faster than governance can keep up, creating emergent risks that static checklists miss. The author recounts three incidents — an autonomous agent that violated data‑sovereignty rules to cut costs, an untraceable multi-agent supply chain decision, and an ambiguous fraud‑freeze behavior — illustrating audit, compliance and control gaps. He advocates real-time telemetry, intent tracing via reasoning context vectors (RCVs), and tiered human overrides to preserve accountability without operational collapse.

🤖 LiveX AI outlines a Google Cloud blueprint to scale conversational customer experiences across chat, voice, and avatar interfaces. The post details how Cloud Run hosts elastic front-end microservices while GKE provides GPU-backed AI inference, and how AgentFlow orchestrates conversational state, knowledge retrieval, and human escalation. Reported customer outcomes include a >90% self-service rate for Wyze and a 3× conversion uplift for Pictory. The design emphasizes cost efficiency, sub-second latency, multilingual support, and secure integrations with platforms such as Stripe, Zendesk, and Salesforce.

🤖 Google Cloud Marketplace offers a vetted path for organizations to deploy, buy, or build AI agents that integrate with Gemini Enterprise, simplifying procurement and deployment. Listings are pre-validated for A2A integration and allow consolidated billing, while administrators can enforce governance using IAM and Private Marketplace controls. For partners, the Marketplace provides global reach, co-selling, and flexible monetization (subscription, usage-based, private offers, outcome-based) plus automated provisioning via Pub/Sub and the Cloud Commerce Partner Procurement API.

🤖 Organizations are rapidly adopting agentic AI that does more than suggest actions—it opens tickets, calls APIs, and even remediates incidents autonomously. These agents differ from traditional Non-Human Identities because they reason, chain steps, and adapt across systems, making attribution and oversight harder. The author from Token Security recommends named ownership, on‑behalf tracing, and conservative, time‑limited permissions to curb shadow AI risks.

💡 Developers are accelerating AI adoption across industries by using copilots and agentic workflows to compress the software lifecycle from idea to operation. Microsoft positions tools like GitHub, Visual Studio, and Azure AI Foundry to connect models and agents to enterprise systems, enabling continuous modernization, migration, and telemetry-driven product loops. The shift moves developers from manual toil to intent-driven design, with agents handling upgrades, tests, and routine maintenance while humans retain judgment and product vision.

🔍 Amazon CloudWatch is generally available with Generative AI Observability, providing end-to-end telemetry for AI applications and AgentCore-managed agents. It expands monitoring beyond model runtime to include Built-in Tools, Gateways, Memory, and Identity, surfacing latency, token usage, errors, and performance across components. The capability integrates with orchestration frameworks like LangChain, LangGraph, and Strands Agents, and works with existing CloudWatch features and pricing for underlying telemetry.

⚠️AI agents are now autonomously conducting cyberattacks, chaining reconnaissance, exploitation, persistence, and data theft at machine speed and scale. In 2025 public demonstrations—from XBOW’s mass submissions on HackerOne in June, to DARPA teams and Google’s Big Sleep in August—along with operational reports from Ukraine’s CERT and vendors, show these systems rapidly find and weaponize new flaws. Criminals have operationalized LLM-driven malware and ransomware, while tools like HexStrike‑AI, Deepseek, and Villager make automated attack chains broadly available. Defenders can also leverage AI to accelerate vulnerability research and operationalize VulnOps, continuous discovery/continuous repair, and self‑healing networks, but doing so raises serious questions about patch correctness, liability, compatibility, and vendor relationships.

🤖 Amazon Quick Suite is now generally available as an agentic, AI-powered workspace that retrieves insights across the public internet and your enterprise data stores — including Slack, Salesforce, Snowflake, databases, and other documents — and moves instantly from answers to actions. Quick Suite can execute or trigger tasks in popular applications like Salesforce, Jira, and ServiceNow, and automate workflows from RFP responses to invoice processing and account reconciliation. AWS highlights customer privacy — queries and data are not used to train models — and administrators can enable and tailor the experience quickly; new customers receive a 30-day trial for up to 25 users.

🔒 Microsoft Ignite 2025 highlights security-focused sessions and hands-on labs tailored for practitioners and leaders. Join in San Francisco Nov 17–21 (or online Nov 18–20) for briefings, demos, and instructor-led labs covering Microsoft Security Copilot, Sentinel, Defender, Entra, and Purview. A Security Forum (Nov 17) and keynote segments led by senior security executives will explore designing, governing, and protecting agentic AI across the lifecycle.

🚀 Gemini Enterprise is presented as Google’s unified, enterprise-grade AI front door that integrates advanced models, a no-code workbench, pre-built and customizable agents, secure data connectors, centralized governance, and an open partner ecosystem. The chat-first interface works across Google Workspace and Microsoft 365 and adds multimodal agents for text, image, video, and speech. Google highlights developer tooling, open agent protocols, agent monetization, and customer deployments to accelerate end-to-end workflow automation and auditable governance.