Building monday.com Sidekick: why capable agents need more than just tools

monday.com rebuilt its Sidekick AI assistant after finding that a single general-purpose agent with an expanding toolset became less reliable, more costly, and harder to debug in production. The revised architecture separates responsibilities among a permission-aware context retrieval layer, a main orchestration agent, specialized subagents with focused toolsets, bounded tools for auditable actions, and isolated sandboxes for iterative work involving files, code, calculations, and generated artifacts. Sandboxes keep intermediate data and processing outside the main model context, while tools handle defined operations such as reading boards or updating items, and subagents address narrower tasks including research, risk analysis, and content generation. LangChain’s LangGraph, Deep Agents, LangSmith, and sandbox capabilities support stateful workflows, delegation, tracing, evaluation, and debugging. The team reports that this structure better supports cross-context reporting, file analysis, and grounded content creation, while emphasizing that reliable workplace agents require clear capability boundaries, permission controls, selective context, observability, and evaluation rather than simply adding more tools.

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