AWS unveils Frontier AI agents for software development

Amazon Web Services has unveiled a new class of AI agents, called frontier agents, which the company said can work for hours or days without intervention. The first three agents are focused on software development tasks.

The three agents announced December 2 include the Kiro autonomous agent, AWS Security Agent, and AWS Devops Agent, each focused on a different aspect of the software development life cycle. AWS said these agents represent a step-function change in what can be done with agents, moving from assisting with individual tasks to completing complex projects autonomously like a member of the user’s team. The Kiro autonomous agent is a virtual developer that maintains context and learns over time while working independently, so users can focus on their biggest priorities. The AWS Security Agent serves as virtual security engineer that helps build secure applications by being a security consultant for app design, code reviews, and penetration testing. And the AWS DevOps Agent is a virtual operations team member that helps resolve and proactively prevent incidents while continuously improving an applications’ reliability and performance, AWS said.

All three agents are available in preview. The Kiro agent is a shared resource working alongside the entire team, building a collective understanding of the user’s codebase, products, and standards. It connects to a team’s repos, pipelines, and tools such as Jira and GitHub to maintain context as work progresses. Kiro previously was positioned as an agentic AI-driven IDE. The AWS Security Agent, meanwhile, helps build applications that are secure from the start across AWS, multi-cloud, and hybrid environments. AWS Devops Agent is on call when incidents happen, instantly responding to issues and usings its knowledge of an application and relationship between components to find the root cause of a problem with an application going down, according to AWS.

AWS said the Frontier agents were the result of examining its own development teams building services at Amazon scale and uncovering three critical insights to increase value. First, by learning what agents were and were not good at, the team could switch from babysitting every small task to directing agents toward broad, goal-driven outcomes. Second, the velocity of teams was tied to how many agentic tasks could be run at the same time. Third, the longer agents could operate on their own, the better. The AWS team realized it needed the same capabilities across very aspect of the software development life cycle, such as security and operations, or risk creating new bottlenecks.