InfoQ

Evaluating AI Agents in Practice: Benchmarks, Frameworks, and Lessons Learned

This article introduces practical methods for evaluating AI agents operating in real-world environments. It explains how to combine benchmarks, automated evaluation pipelines, and human review to ...

Cracking the code: How a 'prediction machine' is resurrecting the Singapore Stone

Several years ago, my linguistic research team and I began developing a computational tool we call "Read-y Grammarian." Our ...
InfoQ

Webpack Publishes 2026 Roadmap with Native CSS Support, Universal Target, and Path to Version 6

Webpack's 2026 roadmap, led by Even Stensberg, unveils substantial enhancements aimed at modernizing the bundler. Key ...

Inside OpenAI’s Race to Catch Up to Claude Code

Anthropic, a smaller rival started by OpenAI defectors, has found runaway success with its programming agent, Claude Code.

Dark Sky Technology Announces Air-Gapped SBOM Generation for Mixed-Code Development Environments with Bulletproof Trust™

New capability delivers compliant, rich, analysis-ready SBOMs from a single folder-based workflow—even for mixed and ...

AI is getting scary good at finding hidden software bugs - even in decades-old code

Researchers have found that LLM-driven bug finding is not a drop-in replacement for mature static analysis pipelines. Studies comparing AI coding agents to human developers show that while AI can be ...

Andrej Karpathy's new open source 'autoresearch' lets you run hundreds of AI experiments a night — with revolutionary implications

An AI agent reads its own source code, forms a hypothesis for improvement (such as changing a learning rate or an architecture depth), modifies the code, runs the experiment, and evaluates the results ...