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Today at the AWS Summit in New York City, Swami Sivasubramanian, AWS VP of Agentic AI, provided the day’s keynote.

Here’s our roundup of the biggest announcements from the event:

New in Amazon Bedrock AgentCore
We’re introducing new capabilities on Amazon Bedrock AgentCore: connecting AI agents to organizational, web, and paid knowledge, helping teams find and fix what’s going wrong in production, and enforcing controls that scale as agents grow more capable.

Together, these capabilities help you build more capable agents faster, govern those agents with controls that scale, and improve them continuously. To learn more, read our blog post covering all the new features.

• Introducing Amazon Bedrock Managed Knowledge Base for faster, more accurate enterprise AI applications — You can build enterprise RAG pipelines with the managed Knowledge Base on Bedrock. It provides native data connectors, Smart Parsing for automatic multi-format data preparation, and an Agentic Retriever for complex multi-step queries—all integrated with AgentCore Gateway so developers can focus on business outcomes rather than infrastructure management.
• Announcing Web Search on Amazon Bedrock AgentCore: Ground your AI agents in current, accurate web knowledge — You can use a fully managed web search tool that enables agents to ground responses in current, cited web knowledge with zero data egress from customer’ secured AWS environment. You can focus on building agents instead of manually adding web search to agents on Bedrock AgentCore and managing its infrastructure.
• AWS WAF adds AI traffic monetization capability to help content owners charge AI bots for content access — You can use a new Bot Control capability that enables content providers and publishers price, meter, and collect payment from AI bots and agents accessing their content and APIs. AWS WAF now lets you set a price for that access, accept payment through third-party providers, and grant scoped access directly at the edge.
• Amazon Bedrock AgentCore harness in now generally available — You can do building and running production-grade AI agents in minutes—without coding orchestration loops—by defining your agent’s model, tools, skills, and instructions in configuration, with Bedrock AgentCore harness.

New in AI-based security tools

• Introducing AWS Continuum: Security at machine speed — AWS Continuum for code vulnerabilities, available in a gated preview, takes findings from across your environment, prioritizes by business impact, proves which are exploitable, and drives a fix through your own process.
• AWS Security Agent (now part of AWS Continuum) adds threat modeling, Kiro power and Claude Code plugin, and more — You can generate the new threat modeling (preview) to understand the full context of your application and identify threats with recommended mitigations using the STRIDE framework. You can also use pull request code scanning with remediation across major Git platforms, and IDE integrations via Kiro power, Claude Code plugin, and MCP — letting developers run security reviews and fix issues without context switching.

New in building AI-based applications 

• Introducing Kiro for iOS — Kiro introduces a native iOS app, available in a gated preview, built for real engineering work that gives developers a new surface to kick off, monitor, steer, and interact with their Kiro sessions directly from their phone. That means you can now start sessions, check back when they’re done, review diffs, and approve changes all while staying connected to your work with no laptop running.
• AWS DevOps Agent adds release management capabilities to assess code changes before production — You can use a new release readiness review of code changes and autonomous release testing. These new features verify every change against the natural language standards you give to the DevOps Agent and run change-specific tests in production-like environments.
• Proactively reduce tech debt autonomously with AWS Transform – continuous modernization — You can use continuous analysis (preview) to automatically scan your code repositories against configurable baselines and generates findings in hours, not weeks. Once you’ve identified and prioritized findings, you can configure autonomous remediations that generate pull requests for affected repositories automatically.

In addition to the keynote announcements, we have other important launches this week:

• Amazon S3 annotations: attach rich, queryable context directly to your objects — Amazon S3 now lets you attach up to 1 GB of rich, mutable, and queryable context directly to your objects using annotations, purpose-built for AI agents and autonomous workflows that need to discover, understand, and act on data at scale without maintaining separate metadata systems.