Summary
This video demonstrates a multi-agent AI development workflow using two simultaneously running instances of Kimi K2.6 — Moonshot AI’s latest open-weight mixture-of-experts model — integrated with OpenClaw, the open-source autonomous agent harness. The setup divides a long-horizon coding project across two independent terminal sessions: one agent acts as the architect, generating a full technical specification including component breakdown, data models, workout tracking logic, progress charts, streak tracking, and calorie goals; the second agent acts as the implementer, watching for the spec file to land and immediately beginning to build the complete React and Vite application.
Fahd Mirza walks through the full OpenClaw configuration process for Kimi K2.6, including how to manually specify the new model version via CLI (changing K2.5 to K2.6 in the model selection), enter a Moonshot API key from platform.moonshot.ai, and restart the gateway. Both agents are prompted to work autonomously without pausing or asking questions — the result is a scaffolded, functional fitness tracker dashboard with a working UI, calendar view, progress charts, goals panel, and activity feed, produced entirely without human-written code.
The workflow illustrates a practical pattern for splitting agentic coding tasks by role, reducing the risk of context overload in a single session. For developers looking to experiment with Kimi K2.6’s strong agentic benchmark performance in a real build context, this video provides a step-by-step template that can be adapted to other projects.
📺 Source: Fahd Mirza · Published April 21, 2026
🏷️ Format: Hands On Build
