What shipped & dropped across AI labs, today.
Today
Thu · Oct 15 · 5 postsUpcoming deprecation of selected GitHub Copilot models in mid-November
We will deprecate the following models across all GitHub Copilot experiences (including Copilot Chat, inline edits, ask and agent modes, and code completions) on November 16th, 2026: Model Deprecation date…
Announcing DPoP Support for Google OAuth: Securing Refresh Tokens
Google OAuth Platform now supports DPoP (Demonstrating Proof-of-Possession) to sender-constrain refresh tokens, neutralizing Infostealer malware and adversary-in-the-middle attacks. By cryptographically binding long-lived refresh tokens while maintaining short-lived access tokens as standard Bearer tokens, developers achieve robust credential security without incurring high-QPS API performance overhead. Additionally, developers integrating multi-agent or Model Context Protocol (MCP) workloads can use Google Cloud Secure Token Service (STS) to handle secure token delegation across agent chains.
Three layers, one repo: a tour of google/adk-recipes
The google/adk-recipes repository unifies Agent Development Kit (ADK) resources into three structured layers—core/, plugins/, and contrib/—serving as a single source of truth for building AI agents. Developers can leverage reference patterns, install modular vertical skills (such as retail product search and virtual try-on) directly into their coding assistants, and deploy production-ready services across multiple languages. This cohesive structure streamlines the entire workflow from initial scaffolding to full deployment on Google Cloud infrastructure.
Agentic autofix for code scanning alerts general availability
Agentic autofix for code scanning alerts is now generally available. It remediates alerts by working across your codebase the way a developer would: it explores relevant files, proposes a fix,…
Evaluating AI agents: moving past the vibe check
A practical engineering guide and reference architecture for establishing continuous evaluation pipelines for multi-turn AI agents using Gemini Enterprise Agent Platform, Google ADK, and OpenInference standards.
Yesterday
Wed · Oct 14 · 3 postsHydraFusion updates and new Max option
HydraFusion has an updated model pool, improved orchestration workflows, and introduces HydraFusion Max. Both HydraFusion and HydraFusion Max are available across VS Code, the GitHub Copilot app, and GitHub Copilot…
Announcing MCP support in Apigee hybrid: agentic tools that run in your own cluster
Apigee hybrid 1.17.0 introduces native Model Context Protocol (MCP) support, enabling the MCP data plane to run directly within your own Kubernetes cluster. This architecture ensures that AI agent request traffic and tool execution remain entirely inside your infrastructure while pulling configuration updates from the control plane. Developers can expose OpenAPI 3.0.x specifications as discoverable MCP tools, leverage existing security policies and API products, and trace end-to-end requests using W3C trace context headers.
Anthropic opens Singapore office and signs MOU with the Government of Singapore
Tuesday
Tue · Oct 13 · 4 postsGemini 4 Argon in GitHub Copilot
Gemini 4 Argon, Google’s newest frontier model, is now generally available in GitHub Copilot. It is designed for complex coding, agentic, and reasoning tasks. In early testing, Gemini 4 Argon…
Enterprise managed settings enforcement updates
Enterprise administrators can now require supported GitHub Copilot clients to retrieve current server-managed settings at startup instead of relying on a cached policy. We are also adding minimum client version…
Optimizing a 200,000-line Python codebase overnight with Gemini 4 Argon
How our engineering team ran Gemini 4 Argon unattended overnight with .agents/skills and /goal mode to cut in-memory session prep overhead by 40% in long sessions and speed up cold imports by 21% in Google's open-source Python Agent Development Kit (ADK).
Gemini 4 Argon for Robotics
Gemini 4 Argon is a general-purpose physical reasoning model designed to enhance workflows across the robotics stack with advanced capabilities in physical understanding, code generation, and visual-semantic reasoning. Developers can access and integrate Argon across Google's developer platforms—including Google AI Studio, the Gemini API, and Google Antigravity—to build and test sophisticated robotic applications. By leveraging simulation tools like MuJoCo and code-as-policies, engineers can seamlessly transition from real-world data or sketches to physically verified robot control and self-improvement workflows.
Monday
Mon · Oct 12 · 1 postSaturday
Sat · Oct 10 · 1 postFriday
Fri · Oct 9 · 1 postOctober 8
Thu · Oct 8 · 5 postsCopilot code review: New organization billing options and controls
This release adds new billing and license controls for Copilot code review admins: Billing: Organization owners can bill Copilot code reviews from members with a Copilot license to the organization’s…
ML Drift: Next-Gen GPU AI/ML Inference at the Edge
Google AI Edge has introduced ML Drift, a high-performance, universal GPU compute framework designed to accelerate on-device AI and machine learning inference. By abstracting the complexities of hardware and low-level APIs—including OpenGL ES, OpenCL, Metal, and WebGPU—ML Drift enables developers to build real-time, interactive ML experiences, from sophisticated video effects to generative AI, across mobile and desktop platforms.
Introducing the Anthropic Cyber Mission
The Outer Loop, Insights First: An Ambient Quality Agent That Diagnoses Your Production Agent
How do you keep improving an AI agent after the first 80%, once it serves real production traffic and silent quality regressions return HTTP 200 OK? We are open-sourcing AQuA (Ambient Quality Agent), a reference implementation that runs beside your production agent in Google Cloud, sweeps and verifies failure clusters against conversation transcripts, and diagnoses root causes anchored to the exact deployed source snapshot.