Scaling AI for Customer Support at Markprompt with Effect #2

Join us as we talk with Michael Fester from Markprompt about scaling AI-powered customer support with Effect, building reliable and high-performance infrastructure, and enhancing developer productivity in a fast-evolving AI landscape.Effect is an ecosystem of tools to build production-grade software in TypeScript.Website & docsCommunity & supportFollow us on X (Twitter)Github#Effect #TypeScript #Zendesk #softwareDevelopmentSong: Dosi & Aisake - Cruising [NCS Release]Music provided by NoCopyrightSoundsFree Download/Stream: http://ncs.io/CruisingWatch: http://ncs.lnk.to/CruisingAT/youtube (00:00) - - Welcome & guest introduction (01:54) - - Michael's journey: from academia to AI & Customer Support (03:49) - - What is Markprompt? Overview & use cases (07:45) - - Markprompt's system architecture (10:22) - - Challenges of running AI-powered support systems (13:20) - - Improving reliability with Effect (16:41) - - Technical architecture breakdown (19:51) - - The public API server setup (23:50) - - Ingestion engine (26:29) - - Onboarding engineers to Effect (30:51) - - Migrating the codebase to Effect (35:19) - - Effect in production: the power of schema (39:02) - - Migrating to Effect: challenges & key takeaways (41:45) - - Effect brings out the best in us engineers (45:34) - - The Future of AI infrastructure (50:18) - - Closing remarks & thanks

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