A Few Learnings from Building a Bootstrapped MLOps Services Startup //Soumanta Das// Coffee Sessions #56

Soumanta wouldn't claim they've reached where they want to and they're still learning, so he's happy sharing successes as well as failures at Yugen.ai.Join the Community: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://go.mlops.community/YTJoinIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Get the newsletter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://go.mlops.community/YTNewsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠// AbstractDetermining Minimum Achievable Goals helps Yugen.ai ensure a significant amount of focus on value-added and impact before diving deep into solutions & building ML Systems. In this episode, Soumanta discusses Balancing ML Development vs Ops and Monitoring efforts while scaling, plus their focus on improvements in small sprints.Soumanta wouldn't claim they've reached where they want to and they're still learning, so he's happy sharing successes as well as failures at Yugen.ai.// BioSoumanta is a Co-founder at Yugen.ai, an early-stage startup in the Data Science and MLOps space.We imagine the future to be shaped by the convergence and simultaneous adoption of Algorithms, Engineering, and Ops, and Responsible AI. Our mission is to help effectuate and expedite the same for our client partners by creating large-scale, reliable, and personalized ML Systems.// Relevant LinksA blog Soumanta wrote when Yugen turned one https://medium.com/swlh/yugen-ai-turns-one-1089f3bf169Presentation, ML REPA 2021 Title of the Talk - Reducing the distance between Prototyping and Production, Why obsessing over experimentation and iteration compounds ROIsSlides - https://drive.google.com/file/d/1J9Cv6IPPkGpOTq8Xl_AQCKaR0-pKMUmA/view?usp=sharing  Video - https://youtu.be/4PEbgQTw1W0--------------- ✌️Connect With Us ✌️ -------------Join our Slack community: https://go.mlops.community/slackFollow us on Twitter: @mlopscommunitySign up for the next meetup: https://go.mlops.community/registerConnect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/Connect with Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/Connect with Soumanta on LinkedIn: www.linkedin.com/in/soumanta-das/Timestamps: [00:00] Introduction to Soumanta Das [00:24] What's Yugen.ai's name all about? [02:02] Starting during the pandemic [05:13] Determination to continue during the pandemic [08:02] State of the art in Yugen.ai and its future [11:32] Time to value defining ML for a business [13:01] Building a strong ML engineering culture [19:06] Data scientists' patterns  [20:00] Helper functions  [22:45] Code review [25:32] Repeatable use cases [27:48] Minimum achievable goals [30:30] Production management goals [34:30] Use cases and System design document [36:20] Practices that helped Yugen.ai build ML systems  [40:05] Growing pains in the scaling process [43:54] Yugen.ai war stories [46:50] Unrealizing there's something wrong and there's actually something wrong [48:10] Data observability tools [49:42] Hands-on deck