Tag
A practitioner shares insights on why multi-agent AI pipelines often fail at handoff points and offers validation, context control, and logging practices to maintain reliability.
A developer questions the claim that 1M-token context windows render scoped handoffs obsolete, arguing against the idea.
A practical guide explaining why naive multi-agent systems fail and how to build coordinated AI agent teams using Builder, Judge, and Manager roles with clear handoffs and verification.
A developer shares lessons from letting a single AI agent handle too many tasks, leading to multiple failure modes. They advocate for splitting roles, enforcing structured outputs, and designing handoffs carefully.
A content marketer shares their experience switching from Paperclip's ticketing system to Alook, an AI agent tool where agents handle handoffs via email and share memory, reducing manual oversight.
Describes a specialized multi-agent system for code review with distinct roles and persistent state, open-sourced as agile-team-skill, which separates reviewer and decision-maker roles to improve code quality and process memory.