Amazon Web Services Inc. envisions a world in which billions of AI agents will be working together. That will take a significant advance in frontier model reasoning, and the company made several major announcements today to make this dream a reality.

“Why not?” is the cloud giant’s central re:Invent conference tagline this week, and AWS built on the theme by announcing a major expansion of its Nova foundation model platform with the launch of Nova Forge, a “first-of-its-kind” service to train and build frontier AI models.

Frontier model reasoning involves advanced problem-solving capabilities for cutting edge AI frameworks, moving from basic information retrieval to problem-solving and logical deduction. While models have advanced rapidly, getting them to comprehend and act while using proprietary data has been a challenge. Nova Forge is designed to address one of the biggest complaints among enterprises using AI.

“Almost every customer I talk to wishes they could teach a model to understand their data,” AWS Chief Executive Matt Garman (pictured) said in his keynote remarks on Tuesday. “Today you just don’t have a frontier model that deeply understands your data and your domain.”

Understanding a specific business

The new service will allow organizations to build optimized variants of Nova by blending proprietary data with Nova’s frontier capabilities. The goal is a customized model that combines the knowledge and reasoning power of Nova’s engine with a deeper understanding of each organization’s specific business.

“AI’s ability to understand your company data is what delivers huge value,” Garman said. “The wizardry comes when you can deeply integrate a model with your intellectual property.”

Garman noted that AWS already has several notable customers who have implemented Nova Forge. These include the online conversation platform Reddit Inc., which brought its own domain data into Forge’s pretraining process. As Garman explained in an exclusive video conversation with SiliconANGLE prior to the conference, Reddit is using Nova to read context, reduce false positives and scale to millions of communities without increasing engineering complexity.

In addition to Forge, Amazon’s Nova platform is also being expanded with “Lite” and “Pro” reasoning models, along with “Sonic,” a speech-to-speech model that can unify text and speech understanding to generate real-time, human-like conversational AI.

New tools for building and monitoring agents

A significant portion of Amazon’s releases this week have involved new capabilities for AI agents. This is understandable, since “the next 80% to 90% of enterprise AI value will come from agents,” as Garman told SiliconANGLE.

The cloud giant announced Policy in Amazon Bedrock AgentCore, designed to actively block unauthorized actions through real-time, deterministic controls that operate outside of the agent code. By setting clear boundaries, organizations can clamp down on unauthorized data access, inappropriate interactions and system-level mistakes.

“This is a little bit like raising a teenager,” Garman told the re:Invent gathering. “You really want to be able to control specific actions with those tools.”

AWS also launched AgentCore Evaluations to gain visibility into agent behavior and results. The offering simplifies the complicated processes and infrastructure previously required to ensure agentic quality. Developers will also have the ability to write custom evaluators using preferred large language models and prompts.

AWS is launching a new class of frontier agents, billed as an “extension” of an organization’s software development team. The Kiro autonomous agent will maintain persistent context across sessions, learning from a developer’s pull requests and feedback. Kiro will also independently figure out the best process for work completion, sharing changes so the user stays in control of what gets incorporated.

“It runs alongside your workflow, maintaining context,” Garman explained. “It actually learns how you like to work.”

Frontier agents were also unveiled today to incorporate security expertise throughout the development cycle, and to support DevOps functions such as correlating telemetry, code, and analyzing deployment data to pinpoint root causes of problems and reduce mean time to resolution. The company revealed that its use of DevOps Agent had resulted in an estimated root cause identification rate of over 86%.

As is common with the opening keynote at AWS re:Invent, the company packed as many releases as it could into a two-and-a-half-hour window. As he was nearing the end of his remarks, Garman took it upon himself to deliver 25 additional announcements, mostly dealing with new instances and database enhancements, in 10 minutes, which may be something of a tech conference record.

“The true value of AI has not yet been unlocked,” Garman said. “It’s turning from a technical wonder into something that delivers real value. Dive deep into the details and start inventing.”

Photo: Robert Hof/SiliconANGLE