According to AndrewYNg on X, DeepLearning.AI launched a short course on the A2A (Agent2Agent) Protocol, built with Google Cloud and IBM Research and taught by Holt Skinner, Iván Nardini, and Sandi Besen, to standardize communication between AI agents across different frameworks. As reported by AndrewYNg, the course addresses the costly custom integrations typically needed to connect heterogeneous agent systems, offering a repeatable protocol layer for interop and orchestration. According to AndrewYNg, this creates business opportunities for multi‑agent applications—such as enterprise workflows, customer support, and supply chain automations—by reducing integration time, improving reliability, and enabling vendor‑neutral agent ecosystems.

According to DeepLearning.AI on X, Moonshot AI’s Kimi K2.5 is a vision-language model that orchestrates parallel workflows to code, conduct research, browse the web, and fact-check simultaneously, delegating subtasks and merging outputs into a single answer (source: DeepLearning.AI post on Feb 12, 2026). As reported by DeepLearning.AI, this agentic execution speeds time-to-answer and reduces error rates via integrated verification, indicating opportunities for enterprises to automate complex knowledge work, RAG pipelines, and multi-step data validation. According to DeepLearning.AI, the model’s autonomous task routing and result fusion highlight a shift toward multi-agent architectures that can improve developer productivity, accelerate literature reviews, and enable compliant web-sourced insights with traceable citations.

According to DeepLearning.AI, Andrew Ng said AI is reshaping the job market by boosting demand for workers who can operate AI tools rather than causing broad layoffs, highlighting upskilling as a priority for employers and talent pipelines (source: DeepLearning.AI on X). According to DeepLearning.AI, OpenClaw autonomous agents gained viral traction on GitHub, signaling developer interest in multi-agent robotics and tool-using frameworks that could accelerate practical automation use cases. As reported by DeepLearning.AI, Kimi K2.5 launched subagent team orchestration and added video capabilities, pointing to growing multi-modal, multi-agent productization that can improve complex workflow execution for businesses.