InfoQ Homepage Development Content on InfoQ
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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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Evolutionary Data through Schemaboi: Achieving Forward, Backwards, and Sideways Compatibility
Drawing from the enduring adaptability of HTML and HTTP, Seph Gentle proposes embedding self-contained schemas directly into file headers, ensuring data remains readable without external definitions. His experimental format prioritises forward, backwards, and sideways compatibility, enabling data format evolution without central coordination or data loss
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SwiftData Enhances Queries, Adds Support for External Types and Data Store Observation
The 2027 release of SwiftData introduces support for persisting custom and third-party types via Codable, along with the ability to organize data into SwiftUI list sections. It also adds new capabilities for observing data store changes through ResultsObserver and HistoryObserver.
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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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Java News Roundup: TornadoVM 5, JHipster, Google ADK, OmniFish Build of Payara, Introducing Vidocq
This week's Java roundup for July 6th, 2026, features news highlighting: the GA release of TornadoVM 5.0; point releases of JHipster, Keycloak and Google ADK; maintenance releases of GraalVM Native Build Tools and Micronaut; the OmniFish Build of Payara and introducing Vidocq, a new implementation of the Jakarta EE 11 Core Profile and MicroProfile 7.1.
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How to Build More Resilient Local-First Applications with AT Protocol Infrastructure
Jake Lazaroff discussed the AT Protocol as a framework for distributed applications beyond social networking. He emphasised a local-first architecture where users maintain data in PDSs while leveraging shared infrastructure for synchronisation and updates. The presentation included experiments showcasing collaborative tools and highlighted the benefits of reduced reliance on app-specific backends.
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Cloudflare Identifies Race Condition in hyper’s HTTP/1 Implementation
Cloudflare recently documented how its development team identified and fixed a rare bug in the widely used Rust HTTP library hyper that could silently truncate large HTTP responses while still returning a successful 200 OK status. The issue had existed for years, was triggered only under specific timing conditions, and has now been fixed upstream.
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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.
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GitHub Copilot CLI Gets Tabs and No-Config-File Tool Setup in Redesigned Terminal UI
GitHub has made the redesigned GitHub Copilot CLI terminal interface generally available. It adds a tabbed layout for sessions, gists, issues, and pull requests; an in-session, form-driven setup for MCP servers, skills, and plugins that avoids hand-editing config files; and a cleaner, theme-aware, more accessible UI with screen reader support.
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How Datadog Used Claude and Cursor for Test-Driven Production Migration
In a recent article, Datadog engineer Arnold Wakim shared what worked, what didn't, and the lessons they learned while evolving a critical production system using AI to overcome hard limits in its storage backend and significantly improve performance.
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WordPress 7.0 Ships with AI Foundations in Core, a Modernized Admin, and New Design Tools
WordPress 7.0, released on May 20, 2026, includes new AI infrastructure, a redesigned admin interface, and updated design tools. Key features comprise an AI Client, Abilities API, and Command Palette, alongside increased PHP requirements. Community feedback is mixed, particularly regarding AI integration. Developers are advised to consult the official documentation for upgrade guidance.
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OpenAI Fixes 18-Year-Old GNU libunwind Bug by Treating Crash Debugging Like Epidemiology
OpenAI found two unrelated bugs masquerading as one in ChatGPT's data infrastructure. Silent hardware corruption on one Azure host and an 18-year-old race condition in GNU libunwind's setcontext function with a one-instruction vulnerability window. The breakthrough came from switching to population-level crash analysis rather than examining individual core dumps.
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AlloyDB Ships Proxy Models That Replace LLM Calls with Local Inference inside the Database
Google shipped AlloyDB AI functions GA with a proxy model architecture that trains a lightweight local model from LLM outputs, then runs queries at database speed without external calls. Smart batching delivers 2,400x throughput improvement. The proxy model reaches 100,000 rows per second in preview, but benchmark numbers apply only to ai.if in internal testing.
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The Kubernetes Approach to AI-Assisted Maintainership Prioritises Human Accountability
The Kubernetes community has introduced a framework for integrating AI into open-source maintainership, emphasising human accountability in code quality and oversight. AI tools may streamline workflows, but ultimate responsibility lies with human maintainers. The framework requires disclosure of AI usage in contributions and prohibits AI-generated commit messages.