InfoQ Homepage Agents Content on InfoQ
-
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.
-
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.
-
Grafana's gcx and MCP Server Reach GA for Telemetry-Driven Agent Development
Grafana Labs has announced general availability for two tools that let AI coding agents query live observability data during development: the gcx CLI and the Grafana MCP server. Both allow agents to pull metrics, logs, traces, SLOs, and Synthetic Monitoring results from Grafana Cloud or a self-hosted stack
-
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.
-
Cloudflare Adds Agent Tracing, with Truncation Limits and Uneven Payload Defaults
Cloudflare launched agent tracing, adding spans for agent invocations, model calls, tool runs, and approvals to existing Workers traces. Sessions replay turn by turn, though the docs warn traces are not lossless and payloads may be truncated. Payload recording defaults differ by framework, and from October 1, 2026 every span counts as a billable event.
-
Vercel Launches v0 API for Headless App Building
Vercel has made the v0 API generally available, enabling developers and AI agents to programmatically generate, iterate on, preview, and deploy applications through API calls.
-
Cloudflare Previews Automatic WebMCP Support for Web Pages
Cloudflare announced a developer preview that lets any website enable a WebMCP (Web Model Context Protocol) interface with a single dashboard switch. This allows browser-based AI agents to interact with unmodified web pages through structured tools instead of scraping or guessing, keeping human traffic and control on the original site.
-
Cloudflare Launches Persistent, Stateful, Computer-Like Environments for Agents
Cloudflare has introduced Cloudflare Computer, a new open-source runtime designed to give AI agents something closer to a real "computer" instead of just ephemeral containers. It leverages Cloudflare isolates for fast serverless execution, making agents cheaper, faster, and more scalable, according to the company.
-
Rootly Drops Small PR Rule as Agentic AI Changes Code Review Economics
Incident management platform provider Rootly has published an account of its decision to drop its long-standing small pull request rule, arguing that the practice no longer serves its purpose now that AI agents generate most of its code. The company describes a shift from measuring PR size to assessing blast radius, with feature flags and rollback capability taking precedence over line counts.
-
Pods as Workers, Not Agents: Rethinking the Deployment Unit for AI Agents on Kubernetes
Running AI agents on Kubernetes raises a key question: should each agent get its own Pod? The kagent project argues no—agents are bursty, short-lived, can spawn subagents, and may wait for human approval, making one Pod per agent wasteful. Agent-substrate adds a control plane to schedule logical “Actors” onto long-lived worker Pods.
-
Vercel Labs Ships Zero: a Graph-First Language Built So Agents Write the Code
Vercel Labs has introduced Zero, an experimental systems programming language aimed at AI rather than human users. It employs unique features like a specific toolchain contract and structured error messages. Reaching version 0.3.4, it compiles to native binaries for major operating systems. The language prioritizes size, speed, and agent usability, though it is still in development.
-
Ponytail Agent Skill Corrects its Own Benchmark after Contributor Challenge
A single-author repo of instruction files, not code, Ponytail passed 44,000 GitHub stars in nine days by making coding agents stop over-building. Its headline claim of 80-94% less code came from a flawed baseline; after a contributor said so, the maintainer rebuilt the benchmark as a real agentic run and published a lower figure of 54%.
-
Azure and Community Guidelines on Choosing between a Skill or a Sub-Agent
In a recent Azure Architecture blog article, Azure lead engineer Kishorekumar Pattabiraman outlines practical criteria for choosing between skills, sub-agents, and other approaches when building AI systems, emphasizing reusability, simplicity, and long-term maintainability.