2 posts tagged with "multi-agent"

When your product is an AI assistant, using AI to build it feels natural — but doing it well is harder than it sounds. The AI-Assisted Development section describes these patterns in the abstract. This post is what they look like after a year in production on a real Aliz frontend: a React + TypeScript chat-based AI assistant with theming, 18-language internationalization, MCP integrations, and multi-environment deploys. The codebase is large enough that no single prompt can reason about it coherently, which is the whole reason the team stopped reaching for a tool and started building a system — the same shape described in Multi-Agent Orchestration. Three layers of AI setup, a team of specialist agents, and a workflow called QRSPI hold it together.

GitHub just shipped an experimental feature in Copilot CLI (announced April 6) that does something no mainstream coding agent has done before: it uses a second model from a different AI family to review the primary agent's work before it executes. The feature is called Rubber Duck, and it's one of the first real-world implementations of cross-model review built into a tool developers actually use daily. If you care about multi-agent workflows or code quality, this one is directly relevant.