AWS Unveils Bedrock AgentCore: A Game-Changer for Enterprise AI Agents

AI agents will change work and society in internet-sized ways, says AWS VP

Forget the old Apple slogan, "Think different." For Deepak Singh, VP of developer agents and experiences at AWS, the mantra of the future is "work differently," and the way he wants to do that is through agentic AI. "I think people get too hung up on the automation and efficiency, part of which are outcomes," said Singh. "We are working differently, but the way we are working different is making us more effective because [agents are] solving harder problems or more problems than you could do before." Also: AWS aims to be your one-stop-shop for AI agents from Anthropic, IBM, Perplexity, and others Singh sat down with ZDNET on Wednesday, shortly after AWS introduced a bevy of new tools and features centered around agentic AI solutions. Among the biggest announcements were Amazon Bedrock AgentCore, a new enterprise-grade platform designed to facilitate the implementation process for new agents, and a new virtual store within AWS Marketplace, which allows customers to choose agents from Anthropic, IBM, Perplexity, Salesforce, and other vendors. At the core of the announcements is the ability to make organizations more easily adopt, customize, and deploy AI agents in their organization. This ease of access to AI agents inherently means the technology will be more rapidly deployed, and that the way people work will be transformed rapidly -- but Amazon postulates it's for the better. Singh, whose work focuses on building experiences that optimize how developers build software, told ZDNET that agentic AI offers workers of all levels the opportunity to build more efficiently. For example, Singh said a software developer intern could spend more time learning how the system works instead of learning the intricacies of a new programming language. Ultimately, a better understanding of the system, facilitated through interactions with AI agents, can help the intern develop the project they are working on. This type of shift, however, will only occur if employees shift their mindset and learn to work smarter. "On an individual level, you want to figure out if what I'm doing is higher quality. Am I able to do more things? Am I able to take on more? Because I have the capacity?" said Singh. "If you don't work differently, you're not going to get that benefit." In a blog post timed with the announcements, Amazon shared a similar position, saying that AI is actually augmenting entry-level tech careers, opposing a sentiment that many experts hold, in which early-career roles will actually be the first to go. Furthermore, the post identified five high-growth roles transformed by AI, including software development, data analysis, cloud engineering, cybersecurity, and data engineering. To further illustrate this narrative, Singh gave a more tangible example of a team member who wanted to build a new feature and estimated it would take approximately one week. Using Kiro, a new agentic IDE launched by AWS this week, the individual was able to ship it in a single day. Also: 5 entry-level tech jobs AI is already augmenting, according to Amazon The key here is that the result was a collaborative effort, which allowed them to accomplish more in the same amount of time. "The future of how applications run and how we as people interact with the world around us is going to be through agents," said Singh. "Agentic AI is going to be a change for society and business that is as important as the internet."

AWS previews AgentCore to jumpstart enterprise AI agents

Running on Amazon Bedrock, it aims to pave the path from prototype to production Video Amazon Web Services (AWS) on Wednesday previewed a service called Bedrock AgentCore to help organizations put AI agents into business-ready production. Bedrock is an AWS service for managing AI models and applications; AgentCore provides tools for deploying these agents, which are automated applications that are given access to sets of software tools to augment their functions. At the AWS Summit New York City 2025 on Wednesday, Swami Sivasubramanian, VP of Agentic AI for AWS, said AgentCore enables the deployment and operation of software agents securely, at scale, using any framework or model, as you can see below. Youtube Video AgentCore provides a variety of services that help enable agents to operate and communicate with one another. These include things like a runtime, memory, authentication, and a gateway that enables agents to discover tools, a code interpreter for writing and executing sandboxed code, web browsing, and observability services. However, so far, connecting AI models to various services and tools hasn't been quite as transformative as industry hype has foretold. As we noted last month, IT consultancy Gartner expects around 40 percent of AI agent projects to get cancelled by 2027 for lack of results and agents themselves still fail to complete tasks more often than not. That's to be expected given that generative AI models frequently get things wrong, for example, Amazon Q reportedly misidentified AWS CMO. Even so, such agents are becoming more capable and there appear to be opportunities for business task automation that would be easier to implement using an AI model than a traditional programmatic script. Sivasubramanian during the keynote described an automated loan processing system composed of three software agents that work together: an intake agent based on Amazon Nova Pro, a credit agent based on Anthropic Claude Sonnet 4, and an underwriter agent based on OpenAI's GPT-4.1. The intake agent organizes loan application data, he explained. The credit agent checks the loan applicant's credit score and calculates risk. The underwriting agent then writes a loan recommendation based on the data analysis and passes it off to a human for review. Whether that system makes inappropriately biased recommendations isn't addressed. To help make AI agents more viable, AWS has also added an AI Agents and Tools category in AWS Marketplace, a showcase for third-party vendor software and services. The goal is to provide those exploring automation opportunities with access to pre-built agents, tools from popular vendors, and access to consulting to get agent projects off the ground. AWS is offering Bedrock AgentCore as a preview service in US East (North Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Frankfurt). AgentCore services are available at no charge until September 16, unless they're linked to other AWS services. After that, the cost for AgentCore is spelled out on the pricing page. ®

Amazon's big bet on AI agents comes into focus at AWS Summit

Serving tech enthusiasts for over 25 years. TechSpot means tech analysis and advice you can trust. Editor's take: AI agents have unquestionably become a hot topic among the largest tech vendors, as Amazon's recent event in New York City once again demonstrated. However, as awareness of the complexities involved in creating and widely deploying agents has grown, so too has the number of questions about how to make it all work. At AWS Summit, Amazon's cloud computing division addressed these challenges head-on, unveiling a broad range of offerings that include development and deployment tools for agents, as well as a new marketplace where customers can purchase ready-made agent products. Taken together, these announcements represent a comprehensive vision that AWS hopes will position it as a compelling platform for companies looking to integrate agents into their environments, regardless of their level of IT sophistication. One of the key offerings AWS introduced was Amazon Bedrock AgentCore, a suite of services for building custom agents that can leverage a wide variety of models and agent-building platforms, including open-source options such as Langchain, CrewAI, and LlamaIndex. In addition, AWS launched its own open-source agent-building tool called Strands Agents. As AWS Vice President Swami Sivasubramanian noted in his keynote, agents are more than just the latest AI buzzword - they represent a fundamental rethinking of how software applications are built, distributed, and used. That makes tools like Strands Agents critical to the future of software and the platforms it runs on. Key components of Bedrock AgentCore include a runtime environment for agents that integrates security, reliability, and scalability. One of the major questions surrounding agents is the potential impact - both positive and negative - they can have in a given environment due to their autonomous nature. To help establish trust, Amazon has integrated a series of guardrails and relies on its more than ten-year-old Lambda serverless architecture to run these agents. Additionally, AgentCore Identity provides identity verification capabilities, allowing integration with popular commercial and open-source authentication platforms such as OAuth. Another key service is AgentCore Observability, which helps organizations track agent performance, review data access, and more. Data access is another crucial factor in optimizing agent performance. AgentCore Gateway offers tools to connect to various APIs and systems to enable these workflows. Amazon is also supporting the MCP (Model Context Protocol) and A2A (Agent to Agent) standards through Gateway, giving companies greater flexibility in the types of data sources, applications, and services they can connect to. Another core expectation for agents is the ability to build on prior interactions by using both short-term and long-term memory. Another core expectation for agents is the ability to build on prior interactions by using both short-term and long-term memory. The AgentCore Memory service simplifies the creation of these often complex memory structures, enabling developers to deliver more compelling and effective agentic experiences. Additionally, Amazon introduced AgentCore Code Interpreter, which allows companies to visualize how agent code processes data and handles more complex interactions. Beyond agent-building capabilities, AWS announced several tools to assist with the creation and fine-tuning of AI models used in agentic applications. For its Nova family of foundation models, Amazon introduced Nova Act, which supports autonomous actions within browsers. Given the central role that browser-based applications and search play in many workflows, this functionality is likely to be widely used in agentic AI applications. The AgentCore Browser service provides this capability within the AgentCore platform. Furthermore, because AgentCore supports multiple models across an agentic workflow, organizations can use Nova Act for certain tasks while employing other large language models for more reasoning-focused actions. For companies working to train or fine-tune their models, AWS made two key announcements. First, it introduced new capabilities in SageMaker that make it easier for organizations to customize Nova models using their own data sources. Second, Amazon revealed a new storage service called Amazon S3 Vectors, which is optimized for cost-effective storage of large volumes of vector data commonly used in model training and fine-tuning. These offerings should help enterprises build more customized and effective models. While they can be used independently of any agentic AI efforts, they also fit seamlessly into the broader agent development process. For organizations that prefer to buy rather than build agents, AWS launched a new Agent Marketplace for commercially available agents. At launch, the marketplace already featured more than 800 offerings, ranging from general-purpose tools to industry-specific and workflow-specific solutions - highlighting just how quickly this market is growing. For context, an AWS Marketplace executive noted that the company's SaaS Marketplace debuted with only about 50 partners. The goal of this new marketplace is to provide a storefront for software partners and make it easier for enterprises to find solutions tailored to their specific needs. Taken together, the announcements from AWS Summit reflect a focused effort by the company to position itself at the forefront of emerging tech. As with many major announcements, much of the news arrives before large-scale real-world deployments of agentic AI have begun. But as companies begin experimenting with these technologies, it is critical to provide tools that support those early efforts. By launching the Agent Marketplace, AWS also offers a low-barrier entry point for companies just beginning to explore the agentic AI space. As with generative AI overall, the agentic AI era is still in its early stages, but as these latest announcements confirm, the pace of development continues to be blistering. Bob O'Donnell is the founder and chief analyst of TECHnalysis Research, LLC a technology consulting firm that provides strategic consulting and market research services to the technology industry and professional financial community. You can follow him on X @bobodtech

AWS unveils Bedrock AgentCore, a new platform for building enterprise AI agents with open source frameworks and tools

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Cloud giant Amazon Web Services (AWS) believes AI agents will change how we all work and interact with information, and that enterprises need a platform that allows them to build and deploy agents at scale -- all in one place. Today at its New York Summit, AWS unveiled Amazon Bedrock AgentCore, a new enterprise-grade platform designed to build, deploy, and operate AI agents securely and at scale. Swami Sivasubramanian, AWS Vice President of Agentic AI, said during the keynote that AgentCore "helps organizations move beyond experiments to production-ready agent systems that can be trusted with your most critical business processes." AgentCore is a modular stack of services -- available in preview -- that gives developers the core infrastructure needed to move AI agents from prototype to production, including runtime, memory, identity, observability, API integration, and tools for web browsing and code execution. "We believe that agents are going to fundamentally change how we use tools and the internet," said Deepak Singh, AWS Vice President of Databases and AI. "The line between an agent and an application is getting blurrier." AgentCore builds on the existing Bedrock Agents framework, launched in late 2024, but dramatically expands capabilities by supporting any agent framework or foundation model -- not just those hosted within Bedrock. That includes compatibility with open-source toolkits like CrewAI, LangChain, LlamaIndex, LangGraph, and AWS's own Strands Agents SDK. What AWS Bedrock AgentCore includes * AgentCore Runtime: A serverless, low-latency execution environment that supports multimodal workloads and long-running sessions with session isolation. * AgentCore Memory: Long- and short-term memory services that let agents learn from past interactions and persist contextual knowledge across sessions. * AgentCore Identity: OAuth-based identity and access management, allowing agents to act on behalf of users across systems like GitHub, Slack, or Salesforce. * AgentCore Observability: Built-in dashboards, debugging, and telemetry tools with support for OpenTelemetry, LangSmith, and Datadog. * AgentCore Gateway: Converts internal APIs, Lambda functions, and third-party services into agent-compatible tools using the Model Context Protocol (MCP). * AgentCore Browser: Provides headless browser access for agents to autonomously interact with websites. * AgentCore Code Interpreter: A secure environment for executing code generated by agents for analysis and visualization. AgentCore also integrates with the AWS Marketplace, enabling teams to discover and deploy pre-built agents and tools. According to Singh, AgentCore has been designed with interoperability in mind. It supports emerging industry standards like MCP and Google's Agent-2-Agent (A2A) protocol. Features such as AgentCore Identity and Gateway ensure agents have clear permissioning and can interact securely with internal systems and third-party APIs. AWS's launch puts it squarely into the center of what's quickly becoming one of the most competitive segments in enterprise AI. OpenAI's Agents SDK and Google's Gemini-based Agents SDK are both pushing similar visions of end-to-end agent development platforms. Writer's AI HQ and startups like Cognition (maker of Devin) are also building tools for managing autonomous software agents. "Agents are the most impactful change we've seen in ages," Sivasubramanian said. "With agents comes a shift to service as a software. This is a tectonic change in how software is built, deployed and operated." Customer adoption and early use cases Several companies granted early access to AgentCore are already building production-grade agentic applications across industries including finance, healthcare, marketing, and content management. Cloud document and file storage company Box is exploring ways to extend its content management tools using Strands Agents and Bedrock AgentCore Runtime. CTO Ben Kus said the integration gives Box customers "top tier security and compliance" while scaling AI capabilities across enterprise environments. Brazil's Itaú Unibanco is using AgentCore to support its development of hyper-personalized, secure digital banking experiences. Chief Technology Officer Carlos Eduardo Mazzei said the new platform "will help us deliver an intuitive banking experience with the efficiency of automation and personalization customers expect." In the healthcare space, Innovaccer has built a new protocol -- HMCP (Healthcare Model Context Protocol) -- on top of AgentCore Gateway. CEO and co-founder Abhinav Shashank called Gateway a "game-changer" that allows the company to convert existing APIs into agent-compatible tools at scale while maintaining trust, compliance, and operational efficiency. Marketing firm Epsilon is leveraging AgentCore to accelerate campaign build times and improve engagement. Prashanth Athota, SVP of Software Engineering, said the company expects to reduce build times by up to 30% and enhance customer journey personalization. Availability and pricing AgentCore is now available in preview in select AWS regions including US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Frankfurt). It's free to try until September 16, 2025, with pricing to begin thereafter. Pricing for AgentCore is entirely consumption-based, with no upfront commitments or minimum fees. Each module -- Runtime, Memory, Identity, Observability, Gateway, Browser, and Code Interpreter -- is billed independently and can be used a la carte or together. Runtime, Browser, and Code Interpreter services are priced per second, based on CPU and memory usage, with rates set at $0.0895 per vCPU-hour and $0.00945 per GB-hour. Gateway charges $0.005 per 1,000 tool API invocations, $0.025 per 1,000 search queries, and $0.02 per 100 tools indexed per month. Memory costs are based on data volume: $0.25 per 1,000 short-term memory events, $0.75 per 1,000 long-term memories stored (or $0.25 with custom strategies), and $0.50 per 1,000 retrievals. AgentCore Identity costs $0.010 per 1,000 token or API key requests, though it's included at no extra charge when used via Runtime or Gateway. Observability is billed via Amazon CloudWatch rates. To learn more or get started, AWS directs developers to its AgentCore documentation, GitHub samples, and a dedicated Discord server.

AWS looks to super-charge AI agents with Amazon Bedrock AgentCore

Includes a selection of tools and services to help build and deploy agents AWS has revealed a new agentic AI development platform as it looks to make building and deploying agents easier than ever. The new Amazon Bedrock AgentCore platform looks to give developers everything they need to create and deploy advanced AI agents. Speaking at its AWS Summit New York 2025 event, the company said the launch marks a "step change" in helping developers move agents from fun toys to something effective and into production. Set to be available soon, AgentCore includes the following services: AgentCore Runtime - secure serverless runtime purpose-built for deploying and scaling AI agents and tools AgentCore Memory - build context-aware agents by eliminating complex memory infrastructure management while providing full control over what the AI agent remembers AgentCore Identity - securely access AWS services and third-party tools on behalf of users or acting with pre-authorization AgentCore Gateway - build, deploy and discover agents across millions of connections - automatically convert into MCP-compatible tools without managing integrations AgentCore Code Interpreter - enable AI agents to write and execute code securely, enhancing accuracy for solving complex end to end tasks - including JavaScript and Python AgentCore Browser Tool - fast, secure cloud-based browser runtime to enable AI agents to interact with websites at scale - including live viewing for troubleshooting and auditing AgentCore Observability - trace, debug and monitor AI agents' performance in production environments

Amazon's AWS has joined the AI agent craze. Now the real work of showing Fortune 500 companies how to actually use them begins

These agents, to many in the tech industry, are the next evolution in our new AI-powered future, where artificial intelligence not only acts as an assistant, but can autonomously complete complex multi-step actions with just some human intervention in sensitive sectors like healthcare, and no human intervention in lower-risk areas. But at least in the short term, the real battle between AWS and agentic AI competitors may depend less on technology differentiation, and more on who employs the most quality talent to help guide large corporations on where to even begin with AI agents. Businesses "are frustrated because they want someone to tell them what to do and how to do it," Dave Nicholson, chief technology advisor at The Futurum Group, told Fortune. "There isn't enough [talent] to go around. Humans are the bottleneck." Nicholson added that AWS and other cloud and large tech companies will need to heavily lean on partner companies to assist with customer education and implementation too. The business case for agents was pushed into the forefront last year by Salesforce, with the announcement of a new division it calls Agentforce. Google, OpenAI and other cloud and technology players have since rushed to announce AI agent tools and services geared toward corporations. On Thursday, a day after AWS's showed off its agent tools, OpenAI announced a new, general purpose agent for users of its ChatGPT product. With just about every CEO these days under pressure to craft an AI strategy, the incoming AI agents may be poised to capitalize on the situation. In an interview with Fortune after his keynote presentation announcing a new in-house collection of agent-building services dubbed AgentCore as well as a marketplace for agents, AWS VP of agentic AI, Swami Sivasubramanian said that Fortune 500 execs whose companies don't start experimenting with the technology risk missing out on a transformational moment as pivotal as the creation of the internet. "Agents are fundamentally going to change how we work and how we live," Sivasubramanian said when asked how execs at Fortune 500 companies can be sure that their investments in building or deploying AI agents isn't supplanted by a new shiny technology of the moment next year. The executive provided an example of how AI technologies will make it feasible for an agent to, for example, not only plan an itinerary for a trip, but do all of the bookings too. "You can give it a high level objective, like, 'Hey, create me a 10 day itinerary in December to visit Australia,'" he said. "It actually understands the objective. Breaks it down into...I need a flight, I need activities to go see in these cities, and then, based on my preferences, it creates a customized itinerary, and actually also secures reservations by calling APIs." That's the type of personal, tangible, example that gives this AWS executive and other proponents of AI agents, the belief that many customer experiences can be overhauled, or created from scratch, with this technology -- in ways that might even be hard to envision now. Slick as some of these scenarios may sound however, the reality is that there are currently few examples of corporations using agents at massive scale. The green field of opportunity is sure to be attractive for some, but it's also a big challenge for the companies selling agentic products and tools since there are not many real-world examples to guide or inspire. Amazon Web Services' market leadership in cloud computing should serve as some advantage, providing a large existing customer base to sell to. And because those companies' operations are already dependent on AWS, they have more patience for any bumps Amazon experiences as it refines its AI agent business. "They're more likely to get two or three strikes," Nicholson said of AWS and its AI agent rollout. But it's an open question whether AWS' initial focus on heavily marketing its new agentic tools to software developers versus the executives with the purse strings will prove problematic. "They have disjointed messaging," Mark Beccue, an analyst at the research firm Omdia, told TechTarget. "When talking about agents, you must have the complete story." AWS' Sivasubramanian said that most C-suite customers that he meets with naturally look inward to how their own organization runs when considering where and how to deploy AI agents first to help automate, or reduce the time to complete, boring, repetitive tasks. This, of course, raises the question of when and how AI agents will disrupt or displace jobs and in which areas. Amazon CEO Andy Jassy recently weighed in on the overall AI boom in an employee memo, saying that while these technologies will both eliminate current roles while creating new ones, "we expect that this will reduce our total corporate workforce [over the next few years] as we get efficiency gains from using AI extensively across the company." On Thursday, a day after AWS' agent-focused summit, the company carried out layoffs of at least hundreds of employees. A day earlier, Sivasubramanian, perhaps not surprisingly, struck an optimistic tone when discussing a new world full of AI agents that now Amazon -- and many rivals -- are rushing to bring to fruition. "Yes, in the short term, if you look at [past] transformations, there were actually changes on the specific job categories [in which people worked], "but then we as humans have really adapted to these changes and then started working on different things. You don't find people who are doing Y2K engineering anymore." "This is the highest level of 'fear of missing out' ever among behemoths in the IT industry right now," Nicholson said. "These are existential decisions being made at Microsoft, Google, and Amazon."

AWS debuts new AI development tools, vector-optimized object store - SiliconANGLE

AWS debuts new AI development tools, vector-optimized object store Amazon Web Services Inc. is rolling out a new set of tools designed to help customers build artificial intelligence agents. Swami Sivasubramanian (pictured), the cloud giant's vice president of agentic AI, detailed the offerings today at the AWS Summit in New York. The first new offering that Sivasubramanian detailed during his keynote is called Amazon Bedrock AgentCore. It comprises a half dozen services designed to ease the task of building and maintaining AI agents. AgentCore's first component, AgentCore Runtime, provides cloud-based sandboxes for hosting AI agents. It allows agents to operate for up to eight hours per run, which makes it possible to automate time-consuming tasks such as analyzing large datasets. Each AgentCore sandbox can be configured with different security settings tailored to the workload it hosts. If completing a task requires an agent to use an external system, developers can activate a service called AgentCore Gateway. It allows agents to access application programming interfaces, code snippets deployed on AWS Lambda and other external workloads. If some of those workloads require an agent to authenticate itself, a module called AgentCore Gateway makes it possible to do so using access management services such as Okta. A code interpreter built into AgentCore allows AI agents to run the code they generate. Another tool, a cloud-based browser, enables agents to perform tasks that require interacting with websites. Developers can check that their AgentCore workloads run reliably using a service called AgentCore Observability. "AgentCore provides a secure, serverless runtime with complete session isolation and the longest running workload available today, tools and capabilities to help agents execute workflows with the right permissions and context, and controls to operate trustworthy agents," Sivasubramanian wrote in a blog post. AgentCore-powered agents and other AI applications can keep their data in Amazon S3 Vectors, a new storage offering that also debuted at AWS Summit today. It's optimized to store vectors, the mathematical structures in which neural networks encode their data. AWS says that the offering costs 90% less than alternative services. S3 Vectors stores information in repositories called vector buckets. A vector bucket can hold up to 10,000 data structures called vector indexes. Each vector index, in turn, may contain tens of millions of vectors. Customers can optionally enrich their records with metadata such as the date when a given vector was created. Such contextual information makes it easier for AI models to find relevant records in large datasets. According to AWS, S3 Vectors processes queries with sub-second latency. "As you write, update, and delete vectors over time, S3 Vectors automatically optimizes the vector data to achieve the best possible price-performance for vector storage, even as the datasets scale and evolve," AWS principal developer advocate Channy Yun explained in a blog post. S3 Vectors integrates with multiple AWS services including Amazon Bedrock, which offers access to a set of cloud-hosted foundation models. Some of the algorithms are developed by third-party providers such as Anthropic, while others are built by AWS itself. Companies can use the models to power their AI agents. Going forward, the cloud giant will enable users to customize the Amazon Nova series of models that it offers through Bedrock. The series comprises more than a half dozen algorithms including several large language models. The other neural networks in the lineup, meanwhile, are geared towards tasks such as image generation. AWS will enable customers to customize Nova models during both the pre- and post-training phases of the development workflow. The pre-training phase produces the base version of an AI model. Post-training, in term, is the umbrella term for the optimizations that engineers make to an AI model after initial development is complete. AWS will support several AI customization methods. One of them is RLHF, a particularly widely-used technique whereby humans provide an LLM with feedback on the quality of prompt responses. This feedback helps the model refine its output. After customizing a model, customers can deploy it on Bedrock. "Customers can now customize Nova Micro, Nova Lite, and Nova Pro across the model training lifecycle, including pre-training, supervised fine-tuning, and alignment," AWS senior developer advocate Betty Zheng detailed in a blog post. AWS announced the new offerings alongside a number of other AI-related updates. The AWS Marketplace now has a section dedicated to AI agents, tools and related offerings from the cloud giant's partners. Nova Act, a Bedrock model that can perform actions in a browser, is receiving an enhanced software development kit with expanded cybersecurity features. AWS is also releasing two new MCP servers. The first offers access to data about its APIs, while the other contains knowledge from its developer documentation. AI agents can use the MCP servers to incorporate that information into their prompt responses. AWS will invest $100 million in its AWS Generative AI Innovation Center to help customers with their AI projects. The business unit, which was formed in 2023, provides customers with access to AI researchers, engineers and other technical experts. AWS disclosed on occasion of the investment that the unit has completed AI projects for thousands of customers since launching.

AgentCore powers scalable AI agent deployment - SiliconANGLE

AWS debuts Bedrock AgentCore to move AI agents from pilot to production Amazon Web Services Inc. is accelerating the shift from artificial intelligence pilots to production with the launch of AWS Bedrock AgentCore, a new runtime built to deploy AI agents at scale with memory, orchestration and enterprise-grade security. As enterprises move past proof-of-concept phases, the need for stronger agent infrastructure is becoming urgent. AgentCore is designed to meet that demand, enabling developers to move faster while maintaining control over data, access and trust boundaries. By embedding memory and tool-use capabilities into a managed runtime, AgentCore gives teams the framework they need to operationalize AI agents across complex workflows -- without sacrificing governance or performance, according to Ben Schreiner (pictured), head of AI and modern data strategy at AWS. "Big news with AgentCore coming out and really demonstrating our innovation ahead of the problems you could foresee that agents could create if they weren't governed, if they weren't observed, if they didn't have a secure runtime," Schreiner said. "You can really see the innovation coming out of our engineering teams to help enterprises not only develop these agents, but also make sure that they're deploying them in a secure, reliable way." Schreiner spoke with theCUBE's John Furrier at AWS Summit NYC, during an exclusive broadcast on theCUBE, SiliconANGLE Media's livestreaming studio. They discussed how AWS Bedrock AgentCore is enabling enterprises to move AI agents from pilot projects to scalable, secure production environments while also reshaping development practices and data strategies to support real-world deployment. AgentCore arrives as companies reimagine how AI agents fit into their business logic and workflows. Rather than being a one-size-fits-all solution, AWS emphasizes flexibility and alignment with actual customer needs, driven by its "working backwards" development ethos, according to Schreiner. "That's at the root of how we approach all customers; they're all unique and there may be some themes and trends that transcend customer segments or industries," he said. "We want to take each customer's challenge and what they're trying to do and work backwards from that." That mindset extends to the agent development lifecycle. Early enthusiasm for "vibe coding" -- where non-technical users sketch out intent -- is now meeting enterprise rigor. AWS' Kiro platform helps bridge this gap, enabling better collaboration between business users and technical teams to get agents from prototype to production, Schreiner explained. "Kiro brings those two things together for the first time, where you're seeing the requirements and the documentation and all the things that need to go into creating a production-ready solution," he said. "So many customers got stuck in POC land and it's unfortunate, but if you don't get into production, then you didn't really solve the problem that you had identified ... production and scale is the goal, and we drive toward that with our customers." Another critical factor in deploying agents at scale is data readiness. Organizations are rediscovering the importance of strong, well-governed datasets as they realize that AI effectiveness is tightly coupled to data quality. That's prompting many to rethink legacy architectures in favor of more modern, flexible designs. "We need executives to understand that the machines and the agents that you create are only as good as the data they have access to," Schreiner added. "If you want good answers from your agentic workflows or anything you do with AI, then you've got to make sure the data it has access to is strong. That gets to governance, it gets to security, it gets to all the things that we've been professing for decades now." Here's the complete video interview, part of SiliconANGLE's and theCUBE's coverage of AWS Summit NYC:

Agentic infrastructure drives AI's next leap - SiliconANGLE

On theCUBE Pod: AWS' agentic push, builder-first bet and the cloud wars to come Agentic infrastructure is fast becoming the backbone of artificial intelligences' next leap -- not just enabling intelligence but orchestrating how it works safely, efficiently and at scale. While the spotlight often lands on flashy new models, a quieter revolution is happening underneath. Cloud leaders are rethinking the stack -- building resilient systems designed to support agents that can reason, collaborate and drive action. This shift to agentic infrastructure is changing everything from developer workflows to enterprise adoption, requiring new tools, protocols and messaging that connect AI's potential to real business value. It's less about showing off the latest model and more about making AI work, sustainably and securely. In this week's episode of theCUBE Pod, theCUBE Research's John Furrier (pictured, left) and Dave Vellante (right) dig into this transformation, focusing on Amazon Web Services Inc.'s new tools such as AgentCore and Kiro, the evolving developer experience and the critical role of protocol standards such as MCP. They debate how Amazon's product-led DNA helps -- and sometimes hinders -- its ability to speak to the C-suite, and they unpack the infrastructure arms race driving everything from agent ecosystems to IPO strategy. "This agentic wave, which is essentially service as a software or software that's being done and prompted and built differently ... they definitely are stacking up a run here to not be like, we're catching up. They're definitely transformed," Furrier said. "My takeaway: They're transforming at a pace I've never seen before with the size that they have." AWS' recent product launches marked a strategic deepening of its AI capabilities -- but with a practical, developer-first mindset. AgentCore, introduced at the AWS Summit NYC, is a managed service that simplifies how developers build, deploy and manage autonomous agents. Meanwhile, Kiro, Amazon's IDE-like coding platform, was rolled out as a foundation for co-creating with agents across prototype to production. These tools signal AWS' intent to move beyond generic AI hype and toward the real-world plumbing that makes agentic systems work. "AgentCore clearly was the big news because they're helping builders more simply build and deploy and manage agents," Vellante said. "That's to me, the most consequential announcement at the summit. And it's a big leap in operationalizing AI, so that's good." Despite this progress, AWS still faces communication gaps with the executive tier. Compared to competitors such as Salesforce Inc. and Microsoft Corp., who offer clear messaging around agents and business transformation, Amazon tends to rely on developer-centric language. However, Furrier and Vellante argue this may be intentional -- a bet that delivering real business value will ultimately matter more than polished soundbites. "If you think about the size of Amazon as a company, AWS particularly, it's massive," Furrier said. "To make that bureaucracy work and what they just delivered in the first half of the year, it's pretty significant. Kiro is significantly stronger than any vibe coding platform out there." Underneath the tooling announcements lies a deeper truth: Enterprises don't want more demos -- they want production-grade software that runs efficiently and generates ROI. That's where agentic infrastructure makes the difference. Systems such as Kiro and AgentCore don't just help teams build AI applications -- they enable them to do so with architectural discipline, cost awareness and reliability, according to Furrier. From avoiding wasteful token usage to managing post-training complexity, agentic infrastructure allows builders to design with production in mind. "The models are great to talk to ... but if you have a model and you want to train it again, it is expensive and hard," Furrier added. "You have a new kind of flywheel developing and things like MCP server, AgentCore; this is what Amazon started." The conversation also acknowledged the broader ecosystem implications. As AWS contributes to open protocols such as MCP and A2A, it's positioning itself not just as a platform but as a hub for interoperable, multi-agent systems. This shift also puts pressure on competitors with less open postures, especially as third-party integrations, ISV tools and SaaS marketplaces become vital components of agentic scale, Vellante explained. "AWS' posture is clearly more inclusive in the recognition that not everything is going to go into the AWS cloud," he said. "I think the strong messaging that I heard at the summit was AWS wants to be the best place to build and deploy and manage agents." This week's theCUBE Pod episode also broadened its lens to explore how other tech giants are competing for control of the agentic stack. Oracle Corp., Microsoft, Meta Platforms Inc. and Google LLC are all laying down massive bets -- from sovereign AI strategies to chip innovation and sprawling data center campuses. With funding rounds hitting $2 billion for infra startups, the race is on to create not just the best models but the most efficient, sovereign and intelligent AI backplanes, according to Furrier. "The geopolitical landscape is going to be reset in the next 10 years by power and data center output," he said. "Sovereign cloud will be the first wave ... and once sovereignty gets nailed down, then borderless crypto will come in." Despite all the innovation happening under the hood, one of the biggest opportunities for AWS lies in up-leveling its message. As enterprise buyers look to AI for strategic outcomes, they're not necessarily seeking more APIs -- they want clarity on value. Amazon's insistence on practicality may win the hearts of developers, but as Furrier and Vellante pointed out, connecting with business leaders requires more than great tooling. "Amazon starts with developer speak," Vellante said. "They don't start with wallet speak ... I think they are bringing in more C-level execs to help with that, and I think it just takes time." The tension is clear: While AWS offers some of the most advanced infrastructure in the industry, it still risks being perceived as "just the pipes" in a market hungry for revenue-driving platforms. Companies such as Oracle, Salesforce and Microsoft have built software businesses with broader boardroom resonance. To fully capture its agentic opportunity, AWS must do more to connect the dots between agentic infrastructure, apps and enterprise value, Furrier explained. "Amazon's message to the C-suite is, if you're trying to build applications to serve your customers, we have the best products for you to do it today," he said. "It doesn't cost as much, and it delivers revenue. That's got my attention."

AWS expands its Generative AI Innovation Center with $100M investment - SiliconANGLE

AWS expands its Generative AI Innovation Center with $100M investment Since launching its Generative AI Innovation Center in 2023, Amazon Web Services Inc. has had one primary goal: help customers turn the potential of artificial intelligence into real business value. Now, the company has invested an additional $100 million in the center to enable customers to pioneer the new wave of autonomous agentic AI systems. Post-announcement, I talked with Taimur Rashid, managing director of generative AI innovation and delivery, who oversees the center. He told me that education about AI continues to be a big part of the Center's mission. "As new as generative AI is as a technology, one of the things that we can do to help our customers along that journey is educating them, showing them the art of the possible." To make that goal a reality, Rashid said AWS has been steadily expanding its gen AI capabilities. "We've added machine learning capabilities, gen AI capabilities and Bedrock, which is a foundational platform for building gen AI applications," he said. "By also bringing human expertise, we can really help customers with that overall journey." As you would expect, the AWS Generative AI Innovation Center isn't a building or campus. It's a global organization of AWS experts that work closely with customers worldwide to help them successfully navigate, learn what AI can offer, and build AI capabilities at scale. Working with the center, customers can launch deployment-ready solutions in as little as 45 days. It's this combination of collaboration, curated content and expert support that makes the center unique. AWS believes that there is an important role for people to enable gen AI to deliver on its promise to benefit a wide range of customers. "We are a multidisciplinary team of AI strategists, and forward-deployed engineers," Rashid said. "We can really be very intentional about helping customers with how to look at gen AI, and then from there, productionizing systems so that they can ultimately get the business value out of it." He also noted that customers want to educate their teams. "They want to ensure that they can utilize the technology in the best way. What are the learnings? What are the best practices and approaches?" he added. "That's where we help bridge that gap. Our most experienced customers in the enterprise space all the way to medium-size, even emerging startups have reached out to us saying 'we need some unique help with how we look at model customization." One example he pointed out: "RobinAI, with its AI platform for the legal industry, is a great example of that. They specifically wanted to fine tune models to help lawyers and paralegals process hundreds of pages, and they got our expertise around that too." Another customer that's working closely with the AWS team to ensure it gains the full benefits of gen AI is Jabil, a large manufacturing company. Rashid explained that in just three weeks, it deployed an intelligent shop-floor assistant using Amazon Q with more than 1,700 policies and specifications across multiple languages, reducing the average troubleshooting time while improving diagnostic accuracy. There's technical help that AWS offers, but as Jabil started to adopt it, it required some guidance to optimize the cost and make it more efficient. The center can help organizations kickstart their AI plans. Almost every business and information technology leader I have talked with has dozens, even hundreds of proposed AI projects. The technology is so new that most customer teams are not yet fully equipped with gen AI skills. They have literacy around data and experience with classical machine-learning models, but when you look at gen AI, they are dealing with a plethora of large language models. Customers want help to determine which model to use. The AWS Generative AI Innovation Center helps customers better understand how gen AI can be used most effectively. Not surprisingly, Rashid said the gen AI choices available to the typical company can be overwhelming. "A senior executive from a travel and hospitality company told me they had identified 300 use cases and needed help prioritizing them," he said. "There's a whole rubric of things that we help customers with, because either the technology is too new, or their teams have not been upskilled on it. We do it for them, which not only helps the customer navigate the space, but we teach them as we go so, they can be more self-sufficient over time." When AWS opened the center in 2023, customers looked at chatbots as their best AI entry point. "As they gained experience and saw all the things they could accomplish with AI, we saw more use cases around content summarization or generation," Rashid recalled. "It's like how things quickly progressed at the advent of cloud computing." Like gen AI, he added, "cloud was a new emerging technology; a paradigm shift for many people. So, we invested quite heavily in teaching customers, enabling coursework through training and certification. We're making very similar efforts with AI, too. In fact, I think with AI we must be a lot more intentional, because it's not only a technical competency that we have to educate customers on. We have to show it in a more immersive way." Partners are a key part of the Innovation Center's work. Last year AWS started a Partner Innovation Alliance that brings a subset of its gen AI competency partners closer to the center and teaches them the center's methodologies and approaches. As a way of scaling, AWS is taking the best practices it has learned along the way and educating its partners. It currently has 19 partners in this Innovation Alliance, including Deloitte, Booz Allen Hamilton and Capgemini. There are also several boutique partners, these are ones that are born in the cloud or digital-native consulting partners, as well as regional coverage in markets such as Korea and Latin America. AWS also has Innovation Center teams in various geographies around the world. "There's a broad set of things that every region looks at from a gen AI perspective," Rashid said. "In the Middle East and Africa -- and even in Europe -- we see a huge emphasis around sovereign AI. Customers are asking how they could use AI to advance many aspects of their society and their nations from health care and government services to education. What's nice about how we're structured is we have resources within those regions that can respond very quickly and in alignment with our regional sales teams to meet some of the unique needs that we see in different geos." The AWS Generative AI Innovation Center team is also prioritizing working with startups. Though AWS has a long history, it has been more methodical of late. Startups bring unique technology. By bringing this audience into the Innovation Center, AWS can help startups get enterprise-ready so they can jointly service customers. This is an obvious win for the startup but also AWS as it creates some consistency in experience. As in most areas of life, there can be too much of a good thing in the world of agentic AI. Specifically, as agentic AI continues its explosive growth, how can organizations avoid having 100 applications that come with 100 agents all trying to chat at users and give advice on what to do? That's one of the goals of AWS' recently announced preview release of Amazon Bedrock AgentCore, which enables customers to securely deploy and manage a large number of agents. "During a recent trip to New York, every agent conversation I had was about 'how should we think about this world of integration and permissions when it comes to agentic AI?'" said Rashid. "That's why the launch of AgentCore is so timely. The primitives [foundational, reusable building blocks that enable AI systems to act autonomously and achieve complex goals] that are offered through AgentCore help establish not only integration, which is one aspect, but then the data permissions that must go with it." Ultimately, he added, as companies get their agents to learn reason and then act, permissions become very important. "Right now, we have building blocks which are important -- such as MCP [Model Context Protocol] and AgentCore," he said. "It's about how you put them together to integrate them into the existing fabric of the application without having to do a massive overhaul. Over time, companies and teams will get data better integrated. They'll get a more specific application strategy, but I do think you'll see a lot of agents. We're early in that cycle right now, but it's very important for us to guide customers to avoid the problem." There isn't a company I talk to that isn't interested in gen AI, but new landscapes can be confusing and hold customers back. The AWS Generative AI Innovation Center is an excellent resource for AWS customers to understand all the technology, how to deploy and to ensure that as they look to scale up gen AI, they are maximizing benefits while reducing risk.

Amazon Launches AgentCore to Deploy and Operate AI Agents at Scale | AIM

AgentCore addresses the growing demand for infrastructure that supports production-ready AI agents capable of reasoning, planning, acting, and learning with limited human oversight. Amazon has announced the preview launch of AgentCore, a new suite of services designed to help developers deploy and manage AI agents at enterprise scale. Built on Amazon Bedrock and compatible with any model or framework, AgentCore addresses the growing demand for infrastructure that supports production-ready AI agents capable of reasoning, planning, acting, and learning with limited human oversight. The rise of agentic AI has accelerated with the adoption of standardised protocols like Model Context Protocol (MCP) and Agent2Agent (A2A), which simplify how agents interact with tools and systems. While frameworks like CrewAI, LangGraph, LlamaIndex, and Strands Agents have made prototyping easier, moving these agents into production still poses major challenges. Developers often spend months building session management, memory systems, observability layers, and secure identity controls, diverting focus from core functionality. "AgentCore eliminates tedious infrastructure work and operational complexity so development teams can bring agentic solutions to market faster," Amazon said in a blog post. AgentCore offers enterprise-grade services that handle key operational components of agent development. These include a serverless runtime environment with session isolation, long- and short-term memory management, execution observability with metadata and debugging tools, and secure identity integration for accessing AWS and third-party services such as GitHub and Slack. The platform also includes managed browser instances for web-based workflows and a code interpreter to run agent-generated code in an isolated environment. According to Amazon, these services are designed to work either independently or together, and can be integrated with existing agent code through the AgentCore SDK. "AgentCore can work with open source or custom AI agent frameworks, giving teams the flexibility to maintain their preferred tools while gaining enterprise capabilities," the company said. Developers can also discover and run pre-built agents and tools via AWS Marketplace, using AgentCore Runtime to deploy and AgentCore Gateway to connect them to APIs and other services. This unified access model is expected to make it easier for enterprises to scale agent-based applications while maintaining compliance and control. With AgentCore, Amazon is positioning itself at the centre of the agent infrastructure ecosystem, providing a foundational layer for developers to move beyond experimentation and build AI agents that operate reliably at scale.

Amazon's Bedrock AgentCore Platform Hints At Future Of Work: AI Agents That Think, Code And Collaborate - Alphabet (NASDAQ:GOOG), Amazon.com (NASDAQ:AMZN)

Amazon.com Inc. AMZN has introduced a new platform aimed at revolutionizing the workplace with AI technology. What Happened: Amazon Web Services (AWS) on Wednesday unveiled the Amazon Bedrock AgentCore, a customizable service that allows businesses to create a network of interconnected AI agents. These agents can perform tasks such as data analysis and coding, freeing up human employees to focus on more creative and strategic work, reported Semafor. The platform was introduced by Swami Sivasubramanian, the company's vice president of agentic AI, at the AWS Summit in New York. The AI agents can operate in the background for up to eight hours and are compatible with popular MCP and A2A protocols, enabling communication with other agents outside the company. Deepak Singh, vice president of developer agents and experiences, described AgentCore as a significant step towards the widespread adoption of agentic AI, likening its potential to that of the internet. See Also: Nvidia Is 'On A March To $5 Trillion' Market Capitalization, Says Dan Ives As He Predicts Bullish Environment For Tech And Crypto: 'Very Strong Second Half' Amazon's announcement comes on the heels of similar product launches from rivals like Microsoft Corp. MSFT, Alphabet Inc.'s GOOG GOOGL Google, and OpenAI. However, AWS sets itself apart by offering agents that are compatible with any framework or model, not just those within the Bedrock ecosystem. At the New York event, Amazon also introduced a dashboard for employers to monitor agent performance and a marketplace for developers to buy and sell agents. Why It Matters: Amazon's new platform is the latest in a series of moves by the company to solidify its position in the AI space. In June, Amazon launched a new team within its consumer R&D division to focus on agentic artificial intelligence. In July, the company unveiled powerful new AI servers to support Nvidia Corp.'s NVDA most advanced chips. Amazon's commitment to AI is further evidenced by its potential multibillion-dollar investment in Anthropic, a San Francisco-based AI model builder. The company is reportedly considering an additional investment to extend its existing $8 billion commitment. Price Action: Amazon ended Wednesday at $223.19, down 1.40% and gained slightly to $223.95 in pre-market trading, according to Benzinga Pro data. Read Next: XRP Surges 25% In 1 Week: Here's When It Will Hit A New All-Time High Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Photo courtesy: Shutterstock AMZNAmazon.com Inc$223.580.17%Stock Score Locked: Want to See it? Benzinga Rankings give you vital metrics on any stock - anytime. Reveal Full ScoreEdge RankingsMomentum65.75Growth97.12Quality66.79Value49.45Price TrendShortMediumLongOverviewGOOGAlphabet Inc$182.93-0.46%GOOGLAlphabet Inc$182.03-0.51%MSFTMicrosoft Corp$504.97-0.13%NVDANVIDIA Corp$172.500.66%Market News and Data brought to you by Benzinga APIs