Results from a survey of 1,260 social scientists about AI and coding agent use.

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

New research on how we've reduced agentic misalignment

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

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 br

Google has introduced Middleware for Genkit, its open-source framework for building AI-powered and agentic applications. The update adds a programmable interception layer around model calls, tool execution, and generation loops, giving developers more control over reliability, safety, and orchestration inside productio

Like other AI wearables, Amazon's Bee offers an odd combination of convenience and privacy anxiety.

We're in the transition period -- all of us.

Merrin Kurian shares the architectural blueprints and organizational processes behind Intuit’s AI transformation. She explains the "fixed, flexible, free" framework used to scale GenOS across 8,000 developers, enabling 3,500+ production experiments. She discusses critical agent failure modes, the "LLM-as-a-judge" evalu

Anthropic has expanded its Claude Managed Agents platform with two enterprise-focused capabilities: self-hosted sandboxes and MCP tunnels. The release aims to address a recurring challenge in enterprise AI deployments, where organizations want to use autonomous agents but cannot allow execution environments or internal

Meryem Arik discusses why modern engineering teams face "inference chaos" and how AI model gateways provide a critical control layer. She explains the balance between empowering decentralized teams to choose the best models and maintaining centralized oversight for security, RBAC, and cost control. Explore open-source

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

J. Paul Reed discusses the "ironies of automation" - a 40 years-old concept now amplified by AI. He explains how advanced systems often make the human operator more crucial, not less, while simultaneously degrading the skills needed to intervene. Sharing real-world stories of "AI-fueled" incidents, he shares why over-r

QCon AI Boston 2026 is close to selling out. Six sessions where speakers engage directly with the gap between AI working in a demo and AI working in production. By Artenisa Chatziou

Ian Thomas shares a case study on embracing AI-native engineering within Meta’s Reality Labs. He explains the "Assess and Grow" framework, a maturity model designed to move teams from manual toil to AI-integrated innovation. He discusses real-world wins - including hitting 90% code coverage in record time - while addre

Cloudflare rebuilt Browser Run on its own Containers platform, delivering 4x higher concurrency and 50% faster response times. The upgrade completes a six-layer agent infrastructure stack: compute (Dynamic Workers + Sandboxes), orchestration (Dynamic Workflows), memory (Agent Memory), browsing (Browser Run), and commer

InfoQ has launched a five-week online AI Engineering certification for senior practitioners working on production AI systems, covering RAG, agents, AI platforms, evals, reliability, and operational trade-offs. By Artenisa Chatziou

Uber updates its Uber Eats Home Feed recommendation system using near real-time user sequence features and a Generative Recommender model. The system evolves from hand-crafted features to transformer-based sequence modeling, reduces feature freshness from 24 hours to seconds, and shifts from pointwise scoring to listwi

The next big thing for Nvidia will be CPUs for AI agents, $200 billion worth, CEO Jensen Huang predicts.

Recycling startups are using AI to improve the recovery of critical minerals like aluminum, aiming to build a massive source of the metal.