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۱۳ مقاله
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 to the researchers, this approach can improve both learning effectiveness and efficiency while helping agents…
Andrew Martin discusses why AI security is fundamentally tied to Kubernetes security. He shares insights into the evolving AI threat landscape, covering non deterministic agent behavior, GPU supply chain vulnerabilities, shared compute risks, and practical defense strategies from prompt firewalling to agentic…
AWS has introduced two open source projects for AI agent development: Strands Decider 2B, a small model designed to make decisions within agent workflows, and Strands Box, a sandbox for controlling agent execution. Both projects address different aspects of building agents that use tools, execute code, and interact…
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 retaining the flexibility to mix in cloud based models for higher level tasks. This approach gives developers greater control over data privacy,…
Once AI is in production, code arrives faster than it can be reviewed, token costs rise, evals have to be good enough to act on, and agents need permissions and guardrails. QCon AI New York 2026 (December 15 16) has confirmed sessions from engineers sharing how they handle these constraints. By Artenisa Chatziou
We celebrated our 16th birthday with 46 announcements across open source, post quantum security, AI agents, and developer platform upgrades. Here’s a day by day roundup of everything we shipped.
Docker's WeAreDevelopers keynote shows how Sandboxes, Kits, and Cloud Sandboxes give AI agents strong isolation and reproducible authority.
Run agents on your laptop, in the cloud, and move between them with one command, all safely. Earlier this year we launched Docker Sandboxes: microVM environments where coding agents can work autonomously in a safe way.
