I Run a Fleet of AI Agents Across Three Machines. Here's What Broke. - Kyle Jaejun Lee, KRAFTON
Jul 8, 2026 · 9:11
Kyle Jaejun Lee runs a fleet of AI coding agents across three machines daily and reveals the scaling failures that emerged from a hierarchy of CEO, VP, manager, and worker agents. To overcome his own attention bottleneck, he separated context into entity-specific workspaces on disk and replaced context compaction with full resets that read handoff files. When moving beyond one machine, five things broke: agents doing work instead of delegating, TMUX panes too crowded to read, out-of-memory crashes from stacked Claude Code processes, colliding Git credentials across workspaces, and the MacBook dying mid-task. He offloaded long-running work to always-on Linux boxes, used Git commits and SSH to move context between machines, and consolidated review gateways onto a single always-on machine with Discord as a unified router. Unsolved challenges include consistent credentials, local-only tools, and resource scheduling—he plans to layer his orchestration on top of Kubernetes to handle compute, secrets, and tools.
