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What's new in AI agents — verified, no hype.
Autonomous agents let Snowflake scale enterprise AI by automating data pipelines.
Why it matters: Data engineers can deploy TensorStax agents to automate pipeline builds and verification, reducing manual effort from days to minutes after integration.
Scales a licensed, HIPAA‑compliant AI primary care service that delivers free, 24/7 consultations across the U.S. with human physician oversight.
Why it matters: ML engineers can adopt structured interview flows and evidence synthesis with human-in-the-loop review to realize up to 10x clinician productivity for routine primary care.
Insurers can use their own LLMs — Claude, ChatGPT Enterprise, or Microsoft Copilot — to securely access payments data and speed integrations with PremiumPay and ClaimsPay.
Why it matters: Developers can use their preferred corporate LLMs to generate and test integration code, shortening PremiumPay and ClaimsPay go-live timelines.
Multi-agent Claude systems speed data analysis, annotation, and coordination, compressing months of lab work into hours.
Why it matters: Bioinformatics teams can deploy Claude multi-agent systems to combine multi-omic datasets and cut analysis time from months to hours.
Anthropic's multi-year deal embeds Claude across Williams' race strategy, car development, and operations to speed data-driven decisions for the 2026 F1 season.
Why it matters: ML engineers can apply Claude to analyze terabytes of simulation and telemetry data, reducing time to actionable performance insights for 2026 development cycles.
Open-sourced starter plugins let teams tailor Claude Cowork to department workflows, with 11 starters for productivity, data analysis, marketing, finance, and biology.
Why it matters: ML engineers can deploy department-specific Claude agents using the open-sourced starters, cutting integration time from weeks to hours.
Automates 90% of threat alerts and converts natural-language requests into executable scripts, letting MSPs scale SMB security operations without added complexity.
Why it matters: Automate triage for 90% of alerts to reduce analyst fatigue and free staff for threat hunting and remediation.
Enables banks and merchants to deploy customizable, governed agentic AI for payments and commerce workflows.
Why it matters: IT leaders can deploy governed agentic workflows for payments and commerce using pre-built agents and policy controls, reducing compliance risk.
Open-source Kimi K2.5 enables visual coding and agent swarms of up to 100 sub-agents, matching GPT-5.2 and Claude 4.5 Opus on key benchmarks.
Why it matters: Teams can build visual, agentic workflows with an open-source model that matches closed-source performance on coding and vision benchmarks, enabling in-house multimodal solutions.
Google Cloud delayed billing for Agent Engine Sessions, Memory Bank, and Code Execution to Feb 11, 2026, giving teams extra time to audit usage and optimize costs before charges begin.
Why it matters: Audit Agent Engine resources now: delete unused Sessions and Memory Bank entries to avoid charges when billing starts on Feb 11.
Global AI will deploy its Agentic AI platform to automate regulatory monitoring, compliance reporting, and HR processes with built-in governance and auditability.
Why it matters: Automate regulatory monitoring and compliance reporting with traceable AI agents to reduce manual reporting and audit workload.
Open event-based standard enables framework-agnostic, real-time streaming of agent execution, tool calls, and state to front-end UIs.
Why it matters: Build reusable frontends that work across LangGraph, CrewAI, and MAF backends without custom integrations.
Enables Gemini 3 Flash to execute Python on images for iterative analysis, improving vision benchmark quality by 5–10%.
Why it matters: ML engineers can enable code_execution in the Gemini API to gain 5–10% on vision benchmarks without building custom agents.
Pilots a Claude-powered assistant to deliver personalized employment support while building government AI skills under DSIT's phased 'Scan, Pilot, Scale' rollout.
Why it matters: Public sector IT teams can pilot Claude-based agents to streamline citizen services and reduce navigation time for job seekers.
Embed production-tested Copilot agents into your apps: the Copilot SDK (technical preview) exposes the agent loop that powers Copilot CLI and lets developers add multi-turn, tool-enabled agents programmatically.
Why it matters: Embed a production-tested agent loop instead of building orchestration plumbing — accelerates agent-driven features and reduces custom orchestration work.
ServiceNow and OpenAI add agents to the Now Platform while Mastercard issues rules for agent-driven payments — accelerating agent use in business workflows and commerce.
Why it matters: Plan integration tests for the Now Platform and equivalent workflow systems to validate agent behavior in real processes.
Graph-backed RAG and meta-cognitive control give agents structured long-term state, multi-hop evidence paths, and cost-aware reasoning for complex, auditable workflows.
Why it matters: Replace ad-hoc context windows with graph-backed state to preserve entity relationships and enable consistent multi-hop retrieval.
An open standard that lets AI agents handle discovery, payments, and post-purchase flows across retailers, speeding agent-driven shopping.
Why it matters: Standardized endpoints reduce integration overhead: retailers and platforms can support agent-driven carts and payments without bespoke APIs.
Organizations pilot multi-agent orchestration to automate complex workflows, but early deployments reveal gaps in measurable ROI, security, governance, and testing.
Why it matters: Run narrow, KPI-driven proofs of concept to measure impact before expanding agent fleets.
Multiple vendors released MCP implementations this week, accelerating interoperability for agents to access enterprise data, tools, and commerce flows.
Why it matters: Inventory APIs and schemas now — MCP requires consistent context payloads and entity mapping to work across agents.