A recent Harvard study of 718 firms, using the Jellyfish analytics platform, finds that although AI coding assistants and agents increase code volume, this does […]
Tag: Large language models
AI in Production: Panellists Highlight Silent Failures, Harness Engineering, and Agent Governance
During a recent InfoQ webinar titled “AI in Production: What Breaks, What Works, and Who Approves It?”, a panel of senior engineering practitioners met to […]
Google EnvHarness Enables Self-Evolving Agents to Learn in Dynamics Environments
Google researchers open sourced EnvHarness, a framework that dynamically adapts agent-training environments to an agent’s weaknesses without modifying the agent, environment, or evaluation system. According […]
Google Antigravity SDK Adds Local Model Support for Greater Token Efficiency and Code Privacy
Google has introduced support for local models in the Antigravity SDK, enabling developers to build and execute agentic workflows directly on their own machines, while […]
Android Bench 2 Adds Support for Long-Horizon Tasks, Agentic Evaluation, and Continuous Scoring
Google has released Android Bench 2.0, a major update to its benchmark framework for evaluating AI models and agents on Android development tasks. The update […]