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Google made agentic AI governance a product. Enterprises still have to catch up.

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Two weeks ago at Google Cloud Next ’26 in Las Vegas, Google did something the enterprise AI industry has been dancing around for the better part of two years: it made agentic AI governance a native product feature, not an afterthought. The centrepiece announcement was the Gemini Enterprise Agent Platform, pitched as the successor to Vertex AI […]

Google made agentic AI governance a product. Enterprises still have to catch up. Read More »

Poolside AI Introduces Laguna XS.2 and M.1: Agentic Coding Models Reaching 68.2% and 72.5% on SWE-bench Verified

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Poolside AI released the first two models in its Laguna family: Laguna M.1 and Laguna XS.2. Alongside these, the company is releasing pool — a lightweight terminal-based coding agent and a dual Agent Client Protocol (ACP) client-server — the same environment Poolside uses internally for agent RL training and evaluation, now available as a research

Poolside AI Introduces Laguna XS.2 and M.1: Agentic Coding Models Reaching 68.2% and 72.5% on SWE-bench Verified Read More »

A Coding Implementation on kvcached for Elastic KV Cache Memory, Bursty LLM Serving, and Multi-Model GPU Sharing

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In this tutorial, we explore kvcached, a dynamic KV-cache implementation on top of vLLM, to understand how dynamic KV-cache allocation transforms GPU memory usage for large language models. We begin by setting up the environment and deploying lightweight Qwen2.5 models through an OpenAI-compatible API, ensuring a realistic inference workflow. We then design controlled experiments where

A Coding Implementation on kvcached for Elastic KV Cache Memory, Bursty LLM Serving, and Multi-Model GPU Sharing Read More »

Meet GitNexus: An Open-Source MCP-Native Knowledge Graph Engine That Gives Claude Code and Cursor Full Codebase Structural Awareness

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There is a quiet failure mode that lives at the center of every AI-assisted coding workflow. You ask Claude Code, Cursor, or Windsurf to modify a function. The agent does it confidently, cleanly, and incorrectly — because it had no idea that 47 other functions depended on the return type it just changed. Breaking changes

Meet GitNexus: An Open-Source MCP-Native Knowledge Graph Engine That Gives Claude Code and Cursor Full Codebase Structural Awareness Read More »

DeepSeek AI Releases DeepSeek-V4: Compressed Sparse Attention and Heavily Compressed Attention Enable One-Million-Token Contexts

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DeepSeek-AI has released a preview version of the DeepSeek-V4 series: two Mixture-of-Experts (MoE) language models built around one core challenge making one-million-token context windows practical and affordable at inference time. The series consists of DeepSeek-V4-Pro, with 1.6T total parameters and 49B activated per token, and DeepSeek-V4-Flash, with 284B total parameters and 13B activated per token.

DeepSeek AI Releases DeepSeek-V4: Compressed Sparse Attention and Heavily Compressed Attention Enable One-Million-Token Contexts Read More »

Google DeepMind Introduces Decoupled DiLoCo: An Asynchronous Training Architecture Achieving 88% Goodput Under High Hardware Failure Rates

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Training frontier AI models is, at its core, a coordination problem. Thousands of chips must communicate with each other continuously, synchronizing every gradient update across the network. When one chip fails or even slows down, the entire training run can stall. As models scale toward hundreds of billions of parameters, that fragility becomes increasingly untenable.

Google DeepMind Introduces Decoupled DiLoCo: An Asynchronous Training Architecture Achieving 88% Goodput Under High Hardware Failure Rates Read More »

Mend Releases AI Security Governance Framework: Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model

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There’s a pattern playing out inside almost every engineering organization right now. A developer installs GitHub Copilot to ship code faster. A data analyst starts querying a new LLM tool for reporting. A product team quietly embeds a third-party model into a feature branch. By the time the security team hears about any of it,

Mend Releases AI Security Governance Framework: Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model Read More »

Mend.io Releases AI Security Governance Framework Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model

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There’s a pattern playing out inside almost every engineering organization right now. A developer installs GitHub Copilot to ship code faster. A data analyst starts querying a new LLM tool for reporting. A product team quietly embeds a third-party model into a feature branch. By the time the security team hears about any of it,

Mend.io Releases AI Security Governance Framework Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model Read More »

Google Cloud AI Research Introduces ReasoningBank: A Memory Framework that Distills Reasoning Strategies from Agent Successes and Failures

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Most AI agents today have a fundamental amnesia problem. Deploy one to browse the web, resolve GitHub issues, or navigate a shopping platform, and it approaches every single task as if it has never seen anything like it before. No matter how many times it has stumbled on the same type of problem, it repeats

Google Cloud AI Research Introduces ReasoningBank: A Memory Framework that Distills Reasoning Strategies from Agent Successes and Failures Read More »

The Integration Bottleneck: Why Agentic AI Is a Legacy Modernization Problem

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Walk into any boardroom reviewing a stalled AI program and you’ll hear the same diagnosis: better models, better governance, more change management. Each has a kernel of truth. None of them is what’s actually in the way. The numbers are everywhere at this point. Deloitte’s 2026 study puts agentic AI at 14 percent production-ready and

The Integration Bottleneck: Why Agentic AI Is a Legacy Modernization Problem Read More »