InfoQ Homepage Agentic AI Architecture Content on InfoQ
News
RSS Feed-
Uber Eats Rebuilds Search Pipeline to Cut End-to-End Latency by 50%
Uber has rebuilt major parts of the Uber Eats search pipeline, reporting a 50% reduction in end-to-end latency. Changes include Above-the-Fold measurement, reduced retrieval work, parallel hydration, advertising data redesign, infrastructure optimizations, and an agentic coding workflow. Uber is also exploring microbatching, product-based retrieval, and HTTP multipart streaming.
-
Google Open-Sources AX a Kubernetes Style Orchestrator for Autonomous AI Agents
Google has open-sourced AX, an orchestrator designed for managing autonomous AI agent workloads. AX operates on a runtime, Agent Substrate, treating agents as stateful actors. It provides resource-efficient task suspension and resumption to optimise performance and reduce latency in idle phases. It features a control plane with Kubernetes-style primitives for managing agent tasks and resources.
-
GitLab Duo Expands Self-Hosted AI Options through Microsoft Foundry
GitLab has expanded GitLab Duo Self-Hosted to support models deployed through Microsoft Foundry, letting organizations run GitLab's AI development capabilities against models hosted in their chosen Azure environment.
-
Alibaba Open Sources OpenCodeReview for AI-Assisted Code Review
Alibaba recently open-sourced OpenCodeReview, an AI-powered code review CLI that combines deterministic pipelines for file selection, bundling, and rule matching with an LLM agent for dynamic code analysis. It supports built-in checks for issues such as null-pointer exceptions, thread safety, XSS, and SQL injection.
-
WSO2 Releases Agent Manager as Enterprises Look to Control Growing AI Agent Sprawl
WSO2 has announced the general availability of WSO2 Agent Manager, an open-source platform designed to provide centralized governance, identity management, security controls, and operational oversight for AI agents running across different models, frameworks, and deployment environments.
-
How LinkedIn Trains AI Job Search 8x Faster with Multi-Teacher Distillation
LinkedIn has published details of the training infrastructure behind its AI-powered job search, describing a multi-teacher distillation pipeline that compresses knowledge from large teacher models into a compact 0.6B-parameter ranking model.
-
The Open-Sourcing of DeepSeek Harness Opens the Door to Modular, Unbundled AI Agent Infrastructure
DeepSeek has released a developer preview of DeepSeek Harness (dsh), an open-source execution runtime for building autonomous AI agents. The software features a micro-kernel architecture with modular plugins for various functional units. The release includes an append-only event logging system for tracking execution activities. Adoption may depend on plugin ecosystem stability and API maintenance.
-
Multi Agent Collaboration Gets Persistent Compute in Bedrock AgentCore
Amazon Web Services has extended Amazon Bedrock AgentCore with runtime instances, a new compute option that gives AI agents persistent infrastructure purpose-built for complex long-running workflows and multi-agent coordination.
-
Cloudflare WriteGuard Brings Fine-Grained Security Controls for MCP Servers
Cloudflare is introducing WriteGuard, now in private beta, to provide fine-grained security controls for MCP (Model Context Protocol) servers. It aims to make AI agents safer by controlling their access to tools that can modify data or perform actions, rather than simply read information.
-
Netflix Open-Sources Agentic Workflow for Causal Inference
Netflix open-sourced an agentic workflow for Observational Causal Inference (OCI) that reduces toil in causal analysis. Given observational data and the human user's analysis plan, the agent uses an actor-critic loop to estimate causality, write a report, and suggest next steps.
-
SpaceXAI Launches Grok Bot for Autonomous AI Agents
SpaceXAI has introduced Grok Bot, a system of persistent AI agents that operate on dedicated cloud computers and can interact with websites, applications, inboxes, and other tools.
-
Grab Cuts Mechanical Analytics Work from 44% to 30% with AI Agents
Grab is using AI agents to automate analytics workflows, cutting mechanical analyst work from 44% in February to 30% in June. Its approach combines agent autonomy, certified data, context management and human oversight, with self service analytics increasingly handling metric, data and SQL requests without analyst intervention.
-
AWS Open-Sources Dogwood, Extending Cedar to Govern Sequences of Agent Tool Calls
AWS has open-sourced Dogwood, a policy language extending Cedar with temporal conditions so rules can reason about an agent's prior tool calls rather than one request in isolation. It covers approvals, rate limits and running totals, ships under Apache 2.0, and is supported in AgentCore Policy, though the reference interpreter is not production-ready.