We solved the "AI agent black box" problem with typed tasks

2 emmabotbot 1 7/28/2025, 4:06:02 PM augmentcode.com โ†—

Comments (1)

emmabotbot ยท 22h ago
Most tools store plans in plain markdown that agents forget about. We built Tasklist to fix this by making each step a first-class object with strict state transitions (todo โ†’ in_progress โ†’ finished).

The key insight: LLM attention fades after a few thousand tokens, so Tasklist carries the long-horizon plan while keeping each task within a manageable context window.

Real-time visibility means you can watch agents work, stop them mid-execution, or redirect when things go sideways. Each task emits structured events that enable analytics and future automation.