AWS Summit NYC: AgentCore Goes GA as Agentic AI Hits Enterprise Scale

30-Second Summary

Amazon announced at AWS Summit New York 2026 that Amazon Bedrock AgentCore is generally available, removing the last preview-stage barrier to deploying production AI agents on AWS. Two new services launched alongside it: AWS Context, which builds a knowledge graph of your organisational data for agent access, and AWS Continuum, an AI-native security service. Agent tasks on AgentCore have grown 15 times in six months. Nasdaq, Visa, Experian, and the PGA Tour are among the named enterprises running agents in production today.

At a Glance

• Topic: Agent Systems
• Company: AWS (Amazon Web Services)
• Date: 17-18 June 2026 (AWS Summit New York City)
• Announcement: AgentCore Harness reaches general availability; AWS Context and AWS Continuum launch; AgentCore Managed Knowledge Base and Web Search capabilities ship
• What Changed: The core infrastructure for deploying, governing, and securing enterprise AI agents is now a set of managed AWS services rather than a custom engineering problem
• Why It Matters: 15x growth in six-month agent task volume confirms enterprise adoption is not speculative. The services that make agents safe and useful in production are now generally available to any AWS customer.
• Who Should Care: Any business running on AWS that is considering or already deploying AI agents across customer service, operations, sales, or internal workflows

Key Facts

• AgentCore Harness is now generally available. It allows deployment of a working agent, declared by model, tools, and instructions, in minutes.
• Agent task volume on AgentCore has grown 15 times in the past six months.
• AWS Context is a new managed service that maps relationships across existing organisational data into a knowledge graph and provides agentic search at runtime.
• AWS Continuum is a new AI-native security service offering code vulnerability detection, business impact prioritisation, and guided remediation.
• AgentCore Managed Knowledge Base ships with native connectors to S3, SharePoint, Confluence, and Google Drive, plus Smart Parsing for automatic multi-format data preparation.
• Web Search on AgentCore grounds agents in current web data without data egress from the customer's AWS environment.
• Amazon Quick gained autonomous background agents that can be scoped to specific business functions, such as processing orders or monitoring CRM interactions.
• Named enterprise deployments include Nasdaq, Visa, Experian, and the PGA Tour (10 times faster tournament coverage).
• Check Point, Zscaler, Rubrik, Netskope, and SentinelOne are integrating security signals into AgentCore.

What Happened

AWS held its annual Summit in New York City on 17 and 18 June 2026, with agentic AI as the centrepiece of the event. The headline announcement was the general availability of AgentCore Harness, the declarative agent deployment layer that was previously in preview. GA status means full production support, SLA commitments, and removal of the preview-stage access controls that had slowed adoption.

Alongside AgentCore GA, AWS introduced two new services. AWS Context automatically maps relationships across an organisation's existing data sources into a knowledge graph, making that context available to agents at runtime through agentic search. The service addresses a consistent pain point in enterprise agent deployments: agents that cannot navigate the implicit relationships inside an organisation's data end up being less useful than a skilled employee with good search habits. AWS Continuum takes a complementary approach on the security side, ingesting findings across an environment, prioritising them by business impact, confirming exploitability, and driving remediation through existing processes.

New capabilities on AgentCore Managed Knowledge Base added native connectors for the data sources that most enterprises already use, together with an Agentic Retriever that handles complex multi-step queries without custom retrieval engineering. Web Search on AgentCore completes the picture by grounding agents in current information, using the same search infrastructure that powers Amazon Quick, Kiro, and Alexa+, entirely within the customer's AWS environment.

The summit was also the venue for broader validation of enterprise agent adoption. The 15x growth figure in agent task volume on AgentCore over six months is the kind of compound growth rate that signals a technology shifting from experimentation to core workflow dependency. Nasdaq, Visa, and Experian are scaling agents across their enterprises, and the PGA Tour reported a 10x improvement in the speed of tournament coverage production.

Why It Matters

The infrastructure gap is closing. The question enterprises have been asking is not "can AI agents do useful work?" but "can we run them at scale without building the infrastructure ourselves?" AgentCore GA, AWS Context, and AgentCore Managed Knowledge Base together answer that question for AWS customers. The managed layer now covers deployment, retrieval, web grounding, and security.

Security is now infrastructure, not application code. AWS Continuum and the AgentCore Guardrails integration with providers like Check Point and Zscaler represent a shift in where AI security controls sit. Moving prompt injection protection and sensitive data filtering to the infrastructure layer means security is consistent across every agent, not dependent on each development team implementing it correctly.

Organisational knowledge is the competitive moat. AWS Context is a significant product because it turns the implicit knowledge inside an organisation's data into something agents can navigate. Two businesses using the same model will produce different results if one has a knowledge graph of its relationships and the other does not. That is the kind of advantage that compounds over time.

The 15x figure reframes urgency. Compound growth of 15 times in six months does not leave much room for multi-year evaluation cycles. Enterprises that are already at scale are building operational expertise, tuning agents, and refining their data infrastructure. The gap between early movers and late movers is widening at a rate that makes "wait and see" a strategy with real costs.

Named deployments shift the conversation. Nasdaq, Visa, and Experian are not experimental deployments. These are regulated financial institutions running agents in production, under compliance and audit requirements that are at least as demanding as most enterprises'. Their adoption provides a strong proof point for regulated-industry operators who have been waiting for peer-group validation.

The David and Goliath View

The AWS Summit story this year is less about individual product features and more about the moment enterprise agentic AI crossed from "interesting pilot" to "production infrastructure." AgentCore Harness going GA, combined with managed knowledge retrieval, security integration, and a knowledge graph service, means the full stack for running agents in an enterprise is now available off the shelf from the provider that already runs most enterprise cloud workloads. That is a significant consolidation of the deployment risk that has kept many organisations cautious.

What stands out in the AWS announcement is the security architecture. Integrating Guardrails at the infrastructure level and wiring in signals from providers like Check Point and Zscaler is a model that other enterprises should study. The organisations that will scale agents fastest are those that solve governance once at the infrastructure layer, rather than re-solving it in every application. AWS has done that work and is making it available as a managed service.

For business operators who have been waiting for enterprise-grade agent infrastructure to exist before committing to a deployment roadmap, the waiting period is over. The infrastructure is here, the enterprise proof points are named, and the growth curve suggests that the cost of delay is no longer theoretical.

Where This Fits in the AI Stack

AgentCore and its companion services sit in the orchestration and deployment layer of the AI stack, above model providers and below end-user applications. AWS Context adds a data layer specifically designed for agent retrieval, distinct from traditional vector search or structured query approaches. AWS Continuum operates at the security layer, connecting to existing security tooling rather than replacing it.

For a D&G client assessment, these services are directly relevant to the AI Growth Engine (agent-powered sales and marketing workflows), Employee Amplification Systems (internal knowledge agents), and Secure AI Brain (governance, audit, and data security).

Questions Operators Are Asking

Do we need to be an AWS customer to benefit from this? Yes, AgentCore, AWS Context, and Continuum are AWS-native services. If your primary cloud is Azure or Google Cloud, the equivalent capability exists but across different products. That said, many enterprises run multi-cloud environments, and standing up a workload on AWS specifically for agent infrastructure is a viable option.

What does "generally available" actually mean for AgentCore? GA means AWS is making production-level SLA commitments, the API surface is stable, and the service is supported under standard AWS enterprise agreements. It also means access is no longer gated by preview sign-up, which was the main friction point for organisations that had been queued to evaluate it.

How does AWS Context differ from standard RAG retrieval? Standard retrieval-augmented generation retrieves documents relevant to a query. AWS Context builds a knowledge graph that represents relationships between entities in your data, such as customers, products, suppliers, and contracts, and lets agents traverse those relationships at runtime. The practical difference is that agents can answer questions that require following a chain of relationships, not just finding the most similar document.

Is AWS Continuum a replacement for existing security tooling? No. Continuum is positioned as an aggregation and prioritisation layer that ingests findings from existing tools (Check Point, Zscaler, Rubrik, and others) and adds business impact scoring and remediation guidance. It works alongside existing security infrastructure rather than replacing it.

What should we do first if we are on AWS and ready to start? Enable AgentCore Harness and connect one existing data source via Managed Knowledge Base. Build a single-purpose agent around a workflow where the time savings are easy to measure, such as internal support, policy lookup, or data summarisation. Establish baseline metrics before you expand, so you have a compounding performance narrative for your second and third agents.

Citable Summary

AWS has announced the general availability of Amazon Bedrock AgentCore Harness at AWS Summit New York 2026, together with two new services: AWS Context, a knowledge graph for organisational data, and AWS Continuum, an AI-native security layer. Agent task volume on AgentCore has grown 15 times in six months. Nasdaq, Visa, Experian, and the PGA Tour are running agents in production today. The managed infrastructure stack for enterprise agentic AI is now generally available to all AWS customers.