InfoQ Homepage Agents Content on InfoQ
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Sarang Kulkarni on Lessons from Building Deep Research Agents in Production
Deep Research Agentic Systems are AI Agents designed to conduct multi-step research for complex tasks using dynamic reasoning, multi-hop information retrieval, and generate structured analytical reports. Sarang Kulkarni from Thoughtworks spoke at Arc of AI Conference 2026 on how to deploy multi-agent research systems for deep reasoning, and the lessons learned from developing Deep Research Agents.
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Gemma 4 Multi-Token Prediction Delivers up to ~3x Faster Token Generation
Gemma 4 can be paired with multi-token prediction (MTP) drafters that use speculative decoding to generate multiple tokens in parallel, allowing the model to verify them in a single pass and achieve up to ~3× faster inference without quality loss.
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AWS MCP Server Reaches GA with Full API Coverage and IAM-Based Governance
AWS has recently made its managed Model Context Protocol (MCP) server generally available, giving AI coding agents controlled access to AWS APIs, documentation, and operational workflows through a standard interface. It provides a safer and more auditable way to connect AI agents to AWS services without handing over broad credentials.
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xAI Releases Grok Skills and Updates Tool Calling Responses API
xAI has released Grok Skills together with enhancements to the Responses API for Grok 4.3, enabling persistent custom expertise that the model retains across all conversations.
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With Android CLI, Google is Making the Android Toolchain Agent-Friendly
Google introduced new Android development tools that enable building apps up to 3x faster by using AI agents, including a redesigned Android command-line interface (CLI), structured skills", and an integrated knowledge base. These tools are designed to support agent-driven workflows and are compatible with third-party agents such as Claude Code and Codex, in addition to Google Gemini.
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Designing a Multi-Agent System for Engineering Support at Scale: a Case Study from Grab
Grab’s Central Data Team built a multi-agent AI system to automate repetitive engineering support tasks across its data warehouse platform. The system separates investigation and enhancement workflows using specialized agents coordinated via an orchestration layer. It reduces operational load, improves resolution speed, and shifts engineering effort from firefighting to platform engineering work.
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Cloudflare and Stripe Let AI Agents Create Accounts, Buy Domains, and Deploy to Production
Cloudflare and Stripe launched a protocol that lets AI agents autonomously create cloud accounts, register domains, start subscriptions, and deploy to production. Stripe handles identity and payment with a $100/month default cap. No other major cloud provider offers comparable agent-driven account provisioning.
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OpenAI Open-Sources Symphony, a SPEC.md for Autonomous Coding Agent Orchestration
OpenAI Symphony is an agent orchestrator that uses project-management tools, like issue trackers, as a control plan to coordinate multiple coding agents. Instead of developers managing interactive coding sessions, Symphony manages "tasks" by assigning each one to a dedicated agent that works autonomously to completion. Once a task is finished, a human is in charge to review the resulting output.
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Ubuntu Embraces Local AI instead of Cloud-First OS Integration
Ubuntu has outlined its AI strategy, describing it as a deliberate departure from industry trends towards cloud-centric, AI-first operating systems. Instead, the company says, Ubuntu will focus future releases on local intelligence, modular design, and strict user control.
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Cloudflare Introduces Workflows V2 with Deterministic Execution and 50K Concurrent Workflows
Cloudflare introduces Workflows V2, a redesigned distributed workflow orchestration system with deterministic replayable execution, improved observability, and major scaling upgrades, including 50,000 concurrent instances and 2M queued workflows. It supports AI agents, data pipelines, and background processing with improved reliability across distributed systems.
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Benchmarking AI Agents on Kubernetes
Brandon Foley published a benchmarking study on the CNCF blog showing that AI coding agents can find and fix isolated bugs. However, they often struggle to understand system-wide impacts. This challenges the idea that improved code retrieval is the main way to enhance automated bug fixing.
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AWS WorkSpaces Now Lets AI Agents Operate Legacy Desktop Applications without APIs
AWS announced that Amazon WorkSpaces can now serve as managed virtual desktops for AI agents in public preview. Agents authenticate through IAM and operate legacy applications via computer vision and input simulation without APIs. Reflex benchmarks show vision agents consume 45x more tokens than API agents.
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Coder Agents Enable Running AI Coding Workflows on Self-Hosted Infrastructure
Coder Agents is a model-agnostic platform designed to let organizations run AI coding agents on their own infrastructure, rather than relying on cloud-based services. This allows teams to maintain full control over code, data, and execution environments.
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How GitHub Is Securing Agentic Workflows in Modern CI CD Systems
GitHub detailed a defense-in-depth security architecture for agentic workflows in CI/CD pipelines, focusing on isolation, constrained execution, and auditability. The design aims to safely integrate autonomous AI agents while mitigating risks like prompt injection, privilege escalation, and unintended actions, using sandboxed environments, restricted permissions, and full execution traceability.
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Cloudflare Launches “Artifacts” Beta, Introducing Git-Like Versioning for AI Agents
Cloudflare has announced the beta release of Artifacts, a new system designed to bring Git-style version control to AI agents, enabling developers to track, manage, and evolve agent-generated outputs with the same rigor as traditional code.