--- title: "Video: Zero-Touch Algorithm Handoffs: Shipping ML Algorithms to Prod Without Rewrites (or ML Engineers)" type: post url: "https://robotpaper.ai/video-h-zero-touch-algorithm-handoffs-shipping-ml-algorithms-to-prod-without-rewrites-or-ml-engineers/" canonical: "https://robotpaper.ai/video-h-zero-touch-algorithm-handoffs-shipping-ml-algorithms-to-prod-without-rewrites-or-ml-engineers/" markdown_url: "https://robotpaper.ai/video-h-zero-touch-algorithm-handoffs-shipping-ml-algorithms-to-prod-without-rewrites-or-ml-engineers.md" published: "2025-12-27T16:33:44.000+00:00" updated: "2025-12-27T16:35:41.000+00:00" tags: ["Conferences", "MLOps", "Pattern"] author: "Roy Osherove" author_links: ["https://robotpaper.ai", "https://x.com/royosherove", "https://www.linkedin.com/in/osherove/", "https://forms.gle/jQSx5KoXvrVA1JCK7", "https://robotpaper.ai/about-roy.md"] description: "My BuildStuff talk on zero-touch algorithm handoffs: shipping ML algorithms to production with Temporal workflows, without rewrites or ML engineer handoffs." usage: "Licensed under CC BY 4.0 — reuse, quote and adapt with attribution (Roy Osherove, link to the original post)." license: "https://creativecommons.org/licenses/by/4.0/" --- # Video: Zero-Touch Algorithm Handoffs: Shipping ML Algorithms to Prod Without Rewrites (or ML Engineers) A while ago I wrote about [Zero-Touch Algorithm Handoffs: How We Ship ML Algorithms to Prod Without Rewrites (or ML Engineers)](https://robotpaper.ai/zero-touch-algorithm-handoffs-how-we-ship-ml-algorithms-to-prod-without-rewrites-or-ml-engineers/) and a few weeks ago I got the chance to speak about this topic at the [BuildStuff conference](https://buildstuff.events/pages/agenda). Here's the video: [Zero-Touch Algorithm Handoffs: Shipping ML Algorithms to Prod Without Rewrites (or ML Engineers)](https://www.youtube.com/embed/59-jvqnLReM?feature=oembed) ## Summary In this video I break down how to ship machine learning algorithms to production without rewrites or ML engineers by using a zero-touch deployment pattern built on Temporal workflows. Traditional ML handoffs—where research code is re-implemented in production apps or sits in backlog with ML engineers—are slow, error-prone, and duplicate effort. Instead, we treat algorithms as Temporal activities owned by researchers and let developers own simple workflows that call those activities, giving us automatic production updates, resilience, scale, and decoupled ownership. This zero-touch algorithm deployment pattern eliminates integration friction, accelerates delivery, improves autonomy between teams, and brings MLOps automation to real researcher-to-prod handoffs without manual intervention --- ## About the author **Roy Osherove** - Senior Solutions Architect at AWS working on AI for production and AI-driven development; author of The Art of Unit Testing and Elastic Leadership, with about 20 years of consulting and training on unit testing, TDD, team leadership and continuous delivery. ### Sites - [RobotPaper](https://robotpaper.ai/): This blog: AI patterns and anti-patterns, AI and coding agents, and engineering leadership. - [osherove.com](https://osherove.com): Roy's personal site. Author of The Art of Unit Testing and Elastic Leadership; consulting and training on unit testing, TDD, team leadership and continuous delivery, plus about 20 years of blog posts. - [The Art of Unit Testing](https://www.artofunittesting.com): The Art of Unit Testing, 3rd Edition (Manning): readable, maintainable, trustworthy unit tests, plus TDD workshops in C#, JavaScript, Java and Kotlin. - [5whys.com](https://www.5whys.com): Roy's writing on software team leadership: self-organizing teams, surviving chaos, learning mode and the Elastic Leadership model. - [Pipeline Driven](https://pipelinedriven.org): Continuous delivery and DevOps practices: build patterns, pipeline-friendly testing, DevOps metrics and enterprise DevOps. - [Elastic Leadership](https://www.elasticleadership.com): Elastic Leadership, Roy's framework for software team leaders (survival, learning and self-organizing modes). ### Social - X: [https://x.com/royosherove](https://x.com/royosherove) - LinkedIn: [https://www.linkedin.com/in/osherove/](https://www.linkedin.com/in/osherove/) ### Contact - Contact form: [https://forms.gle/jQSx5KoXvrVA1JCK7](https://forms.gle/jQSx5KoXvrVA1JCK7) ### License Content on robotpaper.ai is licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/): reuse, quote and adapt with attribution (Roy Osherove, link to the original post). More about Roy and his other sites and projects: [https://robotpaper.ai/about-roy.md](https://robotpaper.ai/about-roy.md)