Gemini 3.5 Flash is shockingly fast at generating code and spinning up agents, but that speed comes at a cost: sloppy ...

Microsoft's Build 2026 security news centers on an agentic AI vulnerability system designed to find real exploitable flaws, ...

GitHub Copilot multi-agent support for VS Code launched at Microsoft Build 2026 alongside Project Polaris, an in-house AI ...

Gemini 3.5 Flash, Gemini Spark and a reimagined Antigravity are designed to use AI to actually do things. Jon covers artificial intelligence. He previously led CNET's home energy and utilities ...

. ├── TS-Bench/ # Benchmark datasets for guardrail model evaluation ├── benchmark/ # Evaluation benchmark of agent safety&security ├── scripts/ # Shell scripts for training/inference ├── src/ # Source ...

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. Amazon Web Services has introduced a managed agent harness in Amazon Bedrock AgentCore that ...

If you were one of the users complaining that Claude Code has sucked lately, Anthropic just confirmed it wasn't all in your head. The company wrote in a lengthy blog post that after reviewing user ...

Where does reasoning live? Model reasons; harness enforces. ~1.6% AI, 98.4% infrastructure. How many execution engines? One queryLoop for all interfaces (CLI, SDK, IDE). Default safety posture?

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

One major challenge in deploying autonomous agents is building systems that can adapt to changes in their environments without the need to retrain the underlying large language models (LLMs).

Six months ago, our team tripled from one engineer to three. But our output didn't triple—it exploded. Each of us was running five agents in parallel, opening pull requests faster than we'd ever seen.