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High Throughput Agentic Engineering with ex-Meta L8 Principal

Kun ChenSeptember 13, 202653m
In a Nutshell

Kun runs First Mate as a single orchestrator that dispatches work to dozens of specialized crewmates across 36 projects, with each crewmate using model-specific rules (Fable for UI, Opus for planning, Luna/Sonnet for simple fixes) and quota-aware selection. Second mates scale capacity by owning entire domains on remote machines while Herder provides unified navigation and Lavish delivers interactive prototype reviews. The workflow routes bug reports from Discord/X directly into the same session, lets automatic compaction handle context limits, and applies "direct PR plus yolo" or "no mistakes" policies based on project risk.

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Kun, previously an L8 principal engineer at Meta, Microsoft, and Atlassian, is sharing an advanced workflow focused on high throughput multitasking through a large number of agents. The approach builds on previous videos about agentic engineering basics.

Herder is a multiplexer that manages all agent sessions and enables easy navigation between sessions. First Mate is an open source project created by Kun that serves as the core workflow where the user only interacts with one agent, and First Mate orchestrates all other agents to minimize context switching.

Setup requires cloning the repository and launching an agent within it. The user utilizes Pi for most models and Claude Code when needing Anthropic models like Opus and Fable. Currently using Grok 4.5 because it is faster, more efficient, and more direct compared to Grok 4.6, which has a non-human personality.

When the new model comes out, don't assume the new model is always better than the last. Use it for a bit and get a sense for how the model behaves by yourself and look at how other people have summarized their learnings as well.

Voice input is used by default because it is faster than typing for natural language prompts. Typing is only used for URLs or specific text. First Mate manages 36 projects total, including both open source and private projects, with all tasks handled through a single agent session.

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