Daily AI Updates: November 26, 2025

November 26, 2025
Overview

SGLang’s dLLM framework launches in collaboration with Ant Group, NVLabs/Fast‑dLLM, and UIUC—adding Block diffusion, KV cache management, and TP/EP parallelism; integrates LLaDA2.0‑mini/flash with CUDA graphs and dynamic batching coming next week. Unified FP8 for RL reduces quantization mismatch and TIS‑clipfrac on 30B and 235B MoE. LangChain Deep Agents ships a general agent framework with persistence, streaming, and human‑in‑the‑loop. JetBrains extends Kotlin agents with a custom ExecuteShellCommandTool for run‑observe‑iterate loops. GitHub Copilot releases a Chat Cookbook of prompt strategies. Anthropic updates an engineer‑inspired harness for long‑running, multi‑window agent execution.

Main Content

  • SGLang dLLM Framework Release: Launches in collaboration with Ant Group, NVLabs/Fast‑dLLM, and UIUC. Adds Block diffusion, KV cache management, and TP/EP parallelism. Integrates Ant Group’s new LLaDA2.0‑mini and LLaDA2.0‑flash models, with CUDA graphs and dynamic batching slated for next week.

  • SGLang FP8 Training & Inference Optimization: Implements end‑to‑end FP8 for reinforcement learning, unifying FP8 to eliminate quantization mismatch. Reports significantly lower TIS‑clipfrac and improved stability on 30B and 235B MoE architectures.

  • LangChain Deep Agents Update: Ships a general agent framework supporting persistent execution, streaming, and human‑in‑the‑loop cycles—suited for context engineering and deep agent construction.

  • JetBrains AI Agent Tools Extension: Adds a custom ExecuteShellCommandTool for Kotlin coding agents to run code, observe failures, and iterate based on real feedback.

  • GitHub Copilot Chat Cookbook: Releases prompt strategies and best practices to improve AI pair‑programming workflows.

  • Anthropic AI Agent Harness Update: Inspired by human engineer workflows, optimizes long‑running agent execution across multiple context windows to address continuous task challenges.