We spent 47k running AI agents in production

6 months ago

Multi-agent systems are the future, but the infrastructure layer is missing, leading to high costs.
A team spent $47,000 due to an infinite conversation loop between two agents.
Agent-to-Agent (A2A) communication and Anthropic’s Model Context Protocol (MCP) are revolutionary but lack standardization.
Anthropic’s MCP aims to standardize context sharing among AI agents, similar to USB-C for devices.
Production challenges include infinite loops, context truncation, cascade failures, and token explosions.
Current agent infrastructure requires manual configuration, costing time and money.
GetOnStack is building production-ready infrastructure for multi-agent systems to prevent costly mistakes.

Hasty Briefsbeta