AWS announced general availability of training sessions within Amazon SageMaker AI serverless model customization. Teams can write their own post-training loops — including custom loss functions and reward signals for reinforcement learning — while SageMaker AI handles GPU allocation, distributed execution, fault recovery, and checkpoint storage. Supported techniques include SFT, DPO, RLVR, RLAIF, and multi-turn RL, and users can choose LoRA or full fine-tuning. The feature supports models including gpt-oss-20b, gemma-4-31B-it, Qwen3.6-27B, and Qwen3.8-27B, and billing is based on tokens processed, pausing while a user's reward function scores responses.
Google announced Public Preview of streaming support in API Gateway, covering Server-Sent Events, chunked/NDJSON responses, WebSockets and gRPC streaming. Streaming endpoints can now sit behind the same gateway as regular APIs, keeping existing authentication, logging and monitoring, without any changes to the API spec. Streams can stay open up to one hour, and gateways now get a predictable default hostname instead of a generated hash. The feature also ties into model routing, letting a single gateway stream responses from Gemini, Claude and OpenAI gpt-oss models.
Google Cloud has made Anthropic's Claude Opus 5.5 and Claude Sonnet 5.5 selectable inside its Antigravity agentic coding platform, alongside Gemini 3.8 Flash and Gemini 4 Argon. Developers can switch between model families mid-conversation across Antigravity 2.0, the CLI, and IDE extensions for VS Code, JetBrains and Visual Studio, all under one enterprise billing and security boundary. Google also describes two engineering patterns: using a second model family to independently review code written by the first ('LLM-as-a-judge'), and assigning fast Gemini Flash subagents to handle high-volume mechanical tasks while a stronger model handles deep reasoning.
AWS introduced Agent Registry, a managed catalog service for Model Context Protocol (MCP) servers, agents, and agent skills. Instead of hardcoding every tool into an orchestrator, agents can now search an approved, versioned catalog at runtime and build a client from the returned descriptor. A reference sample demonstrates a Discover → Instantiate → Execute loop using Amazon Bedrock AgentCore Gateway and AgentCore runtime, with Anthropic Claude Sonnet as the foundation model.
Eon, a data protection ISV running on AWS, replaced per-tool credentials and local MCP servers with a single Amazon Bedrock AgentCore MCP Gateway. The gateway uses Cedar-based policies to enforce least-privilege access for both human engineers and an autonomous SRE agent running Claude on Amazon Bedrock, routing calls to MCP servers hosted on AgentCore Runtimes across multiple AWS accounts. Developer onboarding time dropped from about two days to about two minutes after rolling the system out to 100+ developers and roughly 10,000 sessions.
AWS has rolled out structured outputs across every Anthropic Claude model hosted on Amazon Bedrock, reaching both the standard runtime endpoint and the newer Mantle endpoint built for agentic workloads. Instead of hoping the model returns valid JSON, developers can now lock responses to an exact schema through constrained decoding, which blocks the model from generating tokens that would break the format. A companion feature, strict tool use, applies the same guarantee to function-calling arguments so agent workflows don't fail on malformed inputs.