Agentic RAG Explained in 3 Levels of Difficulty

June 17, 2026 — Amazon Bedrock Managed Knowledge Base, a fully managed retrieval-augmented generation (RAG) service, is now generally available. With Managed Knowledge Base, developers can build production-ready AI agents grounded […] The post AWS Launches Amazon Bedrock Managed Knowledge Base for Enterprise RAG Applications appeared first on AIwire.

With its latest AI tools and products, the vendor showed it is listening to its customer base even while it fails to offer novelty in the market.

The problem with software development today may no longer be writing code. With AI coding assistants generating code faster than ever, the bigger challenge is reviewing, testing, and safely releasing it. AWS is betting that software teams need help with that part of the process, adding release management features to its DevOps Agent. The new features, currently in preview, automatically assess code changes against organizational standards, identify potential release risks, and generate tests tailored to individual changes before they reach production. The release readiness feature, in particular, runs the code in an AWS-managed isolated environment, executing lightweight user journey tests to verify the software builds, runs, and passes basic functional checks before the change enters the pipeline, the company wrote in a blog post. The findings of these tests can be viewed through the DevOps Agent console, as comments on pull requests in GitHub or GitLab, or can be invoked directly thr

The company’s latest agentic AI tools promise faster enterprise automation, but the more revealing story is the infrastructure AWS is building to monitor and contain them.

AWS introduces Web Search on Amazon Bedrock AgentCore, a fully managed tool that enables agents to ground responses in current, cited web knowledge with zero data egress from customer's secured AWS environment. You can focus on building agents instead of manually adding web search to agents on Bedrock AgentCore and managing its infrastructure.

Coinbase and AWS are pushing x402 as a way for publishers and APIs to charge autonomous AI agents, but hot-key and spend-limit risks remain.

Hot AI companies can’t stop talking about forward-deployed engineers (FDEs), which are now very much in vogue.  FDEs, in case you haven’t heard, are hired by companies looking (hoping?) to successfully deploy AI tools and services. It’s one of the hotter professions in a world still trying to understand the impact of AI on careers. So, what exactly are FDEs — are they techy lone rangers like the ones OpenAI, Google and Microsoft are hiring? Turns out it’s not so much about individual engineers who swoop in to design and roll out AI deployments; it’s more about a team of engineers working together at customer sites. At least, that’s the view at Amazon Web Services (AWS). In fact, according to Taimur Rashid, managing director of the AWS Generative AI Innovation Center, the FDE concept pre-dates the current generative AI (genAI) gold rush. The same kinds of engineering teams were needed for the earlier machine-learning and cloud eras to help companies with deployments. Taimur Rashid, man

State Information Technology Services officials said the enterprise agreement lowers costs, simplifies acquisition and expands access to AI tools and training for more than 130,000 state employees.