Building MCP Before MCP Existed: Inside Despegar's Sofia Agent

Nicolas Alejandro Bogliolo is the AI PM at Despegar, the largest online travel agency in Latin America, and the engineer-product-hybrid behind Sofia, the GenAI travel concierge that beat most of the OTA world to a working multi-agent system. Before MCP was a standard and before LangChain was widely adopted, his team had already shipped their own orchestration layer and tool protocol in production. This conversation is a rare look at what it takes to build an agentic system that actually books trips, runs on WhatsApp, and keeps adding capabilities without falling over. Building MCP Before MCP Existed: Inside Despegar's Sofia Agent // MLOps Podcast #375 with Nicolas Alejandro Bogliolo, AI PM at Despegar What we cover: - Chappi, the brain of Sofia: how Despegar built an internal orchestration layer when there was nothing off the shelf- Building "MCP before MCP": the custom tool-calling protocol that predated the Anthropic standard- Multi-agent architecture by vertical: flights, hotels, activities, and cars each own their own flow - Decentralized agent ownership: how any squad in the company can build a flow with central supervision - Sofia on WhatsApp: making messaging the consumer control center, the way Slack became it for the enterprise - The five-phase travel arc Sofia covers: dreaming, planning, anticipation, in-trip, and post-trip - KPI evolution: why "in-scope conversation rate" topped out near 96 percent and what they measure now - The flight-delay-claim use case and why filing claims through a chatbot is a perfect agent task - Group trip planning in WhatsApp groups: the next frontier for travel agents - Sofia as channel of choice: the WeChat-style vision for an agent that handles your entire trip - Why Despegar held off on giving Sofia the ability to bargain with customers, for now. Whether you are building production agents, running an OTA, or just curious about how an AI travel concierge actually works under the hood, this episode is full of grounded,