Modern teams are racing to move from “playing with prompts” to shipping real AI features in production. But stitching together models, tools, and data sources is still slow, brittle, and hard to govern. This webinar shows how to use Vibe Coding tools together with MongoDB Agent Skills and Model Context Protocol (MCP) to go from an idea in a prompt to a production-ready, governed AI workflow.
Across this session, you’ll see how developers and architects can safely expose internal tools and data to AI agents, standardize how agents call those tools, and plug everything into MongoDB as the operational backbone for state, memory, and observability.
- What Vibe Coding tools are and why they matter for building reliable, testable, and collaborative AI workflows—beyond ad‑hoc prompting.
- How MongoDB Agent Skills and MCP work together to let agents securely call tools, query data, and orchestrate multi‑step tasks across your stack.
- Best practices for designing production‑grade AI workflows, including schema design, tool boundaries, observability, and human‑in‑the‑loop controls.
- A reference architecture for a real use case, showing how data, tools, agents, and MongoDB fit together in an end‑to‑end flow.
- A live “prompt to production” demo, walking through building and deploying an AI feature using Vibe Coding tools and MongoDB.
As AI agents become the primary consumers of enterprise data, teams need a way to:
- Safely expose tools and data to agents without rewriting their stack.
- Keep state, memory, and business context close to where data already lives.
- Move from isolated PoCs to repeatable, governed patterns that can scale across use cases and teams.
