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Is it reasonable to develop and deploy AI agents without a continuous testing strategy? Consider these test-driven approaches to ensure the release readiness of AI agents.
Distributed app platform also introduces the 'aspire do' command for parallelized builds and deployments and an Aspire MCP server for AI devops.
The long-running Contagious Interview campaign is now hiding BeaverTail and InvisibleFerret payloads inside JSON storage services.
Unlock the power of AI and machine learning without ever leaving the JavaScript sandbox. Big names include TensorFlow.js, LangChain, and Angular, but we’ve found a few smaller gems, too.
How governance diffuses responsibility across owners, reviewers, and committees, and how engineering leaders can fix it.
Goal is to steal Tea tokens by inflating package downloads, possibly for profit when the system can be monetized.
RHEL command-line assistant expands context limit for more effective AI-powered Linux management and troubleshooting, while offline version becomes available in developer preview.
Flaws replicated from Meta’s Llama Stack to Nvidia TensorRT-LLM, vLLM, SGLang, and others, exposing enterprise AI stacks to systemic risk.
Python is taking on all contenders these days, as more languages elbow into Python’s domain of AI, machine learning, and data science. Those stories and more, in this week’s report.
Agent HQ provides a single location for managing both local and remote coding agents and introduces a plan agent that breaks down complex tasks into steps before coding.