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Agents2026-07-10 · source-backed
Loom (github.com/awslabs/loom) is a reference implementation: "paved path" blueprints baking in least-privilege IAM, abstracted configuration, and strict deployment guardrails for agents built on Strands Agents running on Bedrock AgentCore Runtime. The repo ships the specs used to build it plus a deployment guide. This is the first major cloud vendor publishing its opinionated agent security and governance scaffolding as open source rather than locking it behind a managed service. Steal the blueprints even if you never touch Bedrock.
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AWS shipped per-user, per-target rate limiting August 6 covering MCP targets, inference targets and HTTP passthrough across three metrics: requests (RPS/RPM), tokens (TPM, inference only), connections (CPS). Limits scope by JWT claims ($.context.jwt.sub, .role, .azp) or IAM id...
The walkthrough covers implementing MCP tools, wiring authentication, and deploying with AWS CDK against Bedrock AgentCore and Mistral AI Studio. Steal the two-layer JWT pattern: agent identity and end-user identity as separate token layers. Most MCP server tutorials hand-wave...
AWS shipped Policy in Amazon Bedrock AgentCore to general availability across 13 regions. The breakthrough: security teams can write agent-to-tool access rules in plain English, which auto-convert to Cedar policies with automated reasoning that catches overly permissive or uns...
Each tenant gets a dedicated Bedrock AgentCore runtime, every user session runs in its own microVM that's terminated and memory-sanitized on completion, paired with Knowledge Bases metadata filtering, Guardrails on responses, VPC Lattice for private connectivity and per-tenant...
The full family, Sol, Terra, and Luna, is generally available on Amazon Bedrock with IAM and VPC controls (LLM Boss, AWS). Sol targets coding, biology, and cybersecurity agentic work. Terra runs everyday tasks at about half GPT-5.5's cost, and Luna optimizes for speed. The thr...
AWS made the managed AgentCore harness generally available on June 18. You define model, tools, skills, and memory with CreateHarness, then run it with InvokeHarness. It ships multi-model support (Bedrock, OpenAI, Gemini, LiteLLM), mid-session context preservation, built-in br...
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