EP309: AutoRAS builds self-healing AI agent networks

from Learning GenAI via SOTA Papers · host Yun Wu

Title: AutoRAS: Learning Robust Agentic Systems with Primitive RepresentationsSource: http://arxiv.org/abs/2606.21445v1Summary:This paper introduces a foundational framework for the automated design and optimization of agentic systems by representing workflows as sequences of symbolic primitives. By optimizing these configurations using safety signals and flow-based objectives, it shifts multi-agent system design from manual heuristics to automated learning.

Episode metadata supplied by the publisher feed · Published Jul 16, 2026

Embed this episode

Attribution link and audio player

Ready to play

EP309: AutoRAS builds self-healing AI agent networks

0:00 24:56

1×

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

Share this episode

Similar Episodes

No similar episodes found.

Similar Podcasts

CISO Perspectives (public) N2K Networks This season on CISO Perspectives, host Kim Jones explores some of the challenges of leading through uncertainty. We explore the complexity of the changing nature of regulation and working with the federal government, the evolution of privacy and fraud, and how emerging technologies like AI and quantum computing are changing cyber. When you don’t know what questions to ask, you’re afraid to ask, or don’t know who to ask, CISO Perspectives provides the foundation for learning in this brave new world.

Frequently Asked Questions

How long is this episode of Learning GenAI via SOTA Papers?

This episode is 24 minutes long.

When was this Learning GenAI via SOTA Papers episode published?

This episode was published on July 16, 2026.

Can I download this Learning GenAI via SOTA Papers episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.

URL copied to clipboard!