Architecting for the Speed of Vibe Coding: Building Apps on the Cribl Platform

AI-assisted development has collapsed the time from idea to working app from weeks to minutes — but the platforms your team depends on still take weeks to ship a feature, and for good reason. Reliability at scale demands rigor. So how do you give your teams AI-speed iteration without sacrificing the stability you've built your critical workflows on? This session goes inside the architectural decisions behind Cribl's extensibility layer: how we separated AI velocity from platform stability using a strict trust boundary, sandboxed execution, and a controlled set of managed backend primitives (state, webhooks, secure proxies). We'll cover what we chose to build, what we deliberately deferred, and how the same model applies to any platform facing the AI-speed shift. You'll leave with: - A framework for thinking about the trade-off between customization velocity and platform rigor - The three architectural principles that make AI-assisted extensibility safe: trust boundaries, sandboxed execution, and managed backend primitives - Guidance on when to build a custom app, when to extend with a pack, and when to push for first-party capability - Intended for architects, platform engineers, and technical leaders thinking about extensibility in the AI era. ## Follow Cribl LinkedIn: https://www.linkedin.com/company/cribl/ Twitter: https://www.twitter.com/cribl_io Sign up for a Cribl.Cloud account: https://cribl.cloud/signup/ Learn more about Cribl: https://cribl.io