High-Signal AI Code Review: A Multi-Agent Blueprint

January 28th at 12pm ET

In this webinar, we’ll deconstruct the architecture of multi-agent systems for code reviews.

We are moving from the era of the AI assistant to the era of agentic workflows, but most AI code reviews today force a single agent to act as a single reviewer—blending priorities, hallucinating context, and optimizing for breadth rather than depth. The result? A wall of low-impact noise that developers learn to ignore.

In this webinar, you’ll learn why high-quality review is a set of distinct checks, not a single opinion, and how a multi-agent workflow maps to how strong teams review code: correctness, security, performance, maintainability, and tests.

Join to learn:

• The Single-Agent Bottleneck
  Why asking one model to multitask leads to context switching and ruins performance on complex diffs.
• Architecting the Multi-Agent Swarm
  Breaking down the review process into specialized roles where each agent has exactly one job and one definition of done.
• Reducing False Positives
  Moving from generic, noisy advice to high-signal, context-aware engineering feedback.
• Tools & Context
  Giving agents the specific inputs they need—like ticket requirements and codebase patterns—to avoid generic outputs.
• The Anatomy of a Good Review
  Deconstructing “quality” into five distinct checks: correctness, security, performance, maintainability, and tests.