InfoQ Homepage Agents Content on InfoQ
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Embabel Agent Framework Reaches 1.0
Embabel has reached its 1.0 release, providing a framework for AI agents on Java It allows Java and Kotlin developers to define agents as typed domain objects. Built on Spring AI, Embabel supports multiple model providers and combines planning with predefined state machines, offering flexibility for agent workflows.
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Microsoft Three-Layer LLM Routing Architecture for AI Agents on AKS
Microsoft has released a reference architecture for routing agent traffic on Azure Kubernetes Service. It breaks down the issue into three key choices: which model answers a call, how the call is managed, and which GPU replica handles it.
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Indirect Prompt Injection Exploits GitHub's AI Agent to Leak Private Repository Data
GitLost is a prompt-injection exploit discovered by Noma Security that tricks GitHub's new Agentic Workflows into leaking private data. By embedding concealed instructions within public GitHub issues, attackers can circumvent security safeguards and induce AI agents to reveal confidential information in public comments.
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Anthropic Details How it Contains Claude across Web, Code, and Cowork
Anthropic detailed the containment architectures it uses for Claude across its products. It argues that agent safety depends on placing deterministic limits on an agent’s filesystem, network, and execution environment rather than on permission prompts or safeguards. Most notably, it examines failures at trust boundaries and along permitted egress paths that led Anthropic to revise those designs.
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Android Studio Quail 2 Redesigns Agent Mode, Streamlines AI-Assisted Coding
The latest release of Android Studio, Quail 2, now stable, expands Gemini/AI Agent Mode inside the IDE by enabling multiple AI conversations in parallel and further advancing Google's push to integrate AI-powered workflows directly into Android Studio. It also enhances debugging and profiling capabilities and makes it easier to explore experimental features.
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Pinecone Introduces Nexus Engine for Compiling Business Context into Structured Data for AI Agents
Now generally available, Pinecone Nexus is a "knowledge engine" for AI agents that transforms enterprise data into a structured layer agents can query directly. It enables teams to ingest and curate business context once for all, making it reusable across agents and reducing token costs while improving accuracy.
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Cloud Native Infrastructure Emerges as the Foundation for Trustworthy Agentic AI
A new technical analysis published by the Cloud Native Computing Foundation (CNCF) argues that the future of agentic AI will be built not on entirely new infrastructure, but on the mature cloud-native ecosystem that already powers modern distributed applications
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QCon AI Boston: Production AI Moves beyond Prompts to Platforms, Harnesses, and Evals
QCon AI Boston 2026 focused on the operational challenges of deploying AI agents, emphasizing the need for robust production infrastructure. Key themes included improving context management, ensuring security through a "harness" around agents, and adopting a comprehensive engineering model for AI.
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AWS Continuum to Enable Agentic Code Security for Enterprises
Amazon Web Services has recently introduced AWS Continuum, a new integrated security platform to automate the discovery, enforcement, and remediation of security issues across codebases, dependencies, and applications. AWS Continuum launches with four agentic capabilities, aiming at the entire vulnerability lifecycle: penetration testing, code review, threat modelling, and code vulnerabilities.
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Stripe Benchmark Shows AI Agents Build Integrations but Struggle with Validation
Stripe introduces a benchmark suite to evaluate whether AI agents can build real-world Stripe integrations across backend, frontend, and browser-based checkout workflows. The study examines end-to-end software engineering capability, focusing on execution, testing, and validation gaps in agentic systems under production-like constraints.
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Google and Industry Partners Announce Agentic Resource Discovery Specification for AI Agents
Google and industry partners announced Agentic Resource Discovery (ARD) Specification, an open standard for publishing, discovering, and verifying AI tools, APIs, and agents. ARD introduces a discovery layer built on catalogs and registries, enabling dynamic capability discovery while leveraging existing protocols such as MCP and OpenAPI for execution and emphasizing trust and interoperability.
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Google's Genkit Ships Agents API with Detached Turns and Human-in-the-Loop for TypeScript and Go
Google released the Genkit Agents API in preview for TypeScript and Go. The open-source framework packages message history, tool loops, streaming, and state persistence behind a single chat() interface. Detached turns let agents work after clients disconnect. Interruptible tools provide human-in-the-loop control with anti-forgery validation on resume.
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How DoorDash Built an AI Shopping Assistant That Doesn’t Rely on the LLM Alone
DoorDash details the architecture behind Ask DoorDash, its AI-powered conversational shopping assistant, combining LLMs, specialized AI agents, MCP-based tooling, and an intelligence layer with persistent consumer memory and live backend data. Early results show up to 24% higher checkout conversion, 17% larger baskets, and improved intent accuracy using memory-backed sessions.
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Cloudflare Introduces Temporary Accounts for Autonomous Worker Deployment
Cloudflare has recently introduced temporary accounts that let AI agents deploy Cloudflare Workers immediately, without first creating or authenticating with a permanent account. If left unclaimed, the accounts and their deployments expire automatically after 60 minutes.
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Slack Introduces Agent Driven End-to-End Testing to Improve Resilience in UI Test Automation
Agentic testing is an AI-driven approach to end-to-end test automation introduced by Slack engineering. It uses AI agents that execute workflows based on intent rather than fixed scripts, adapting to UI and system changes at runtime. The approach aims to reduce brittle tests in distributed systems while complementing deterministic unit, integration, and E2E testing strategies.