Spec Driven Development, Workflows, and the Recent Coding Agent Conference

Spec Driven Development, Workflows, and the Recent Coding Agent Conference

Author: Demetrios April 1, 2026 Duration: 59:12

Jens Bodal is a Senior Software Engineer II working independently, focusing on backend systems, software architecture, and building scalable solutions across client projects.


This One Shift Makes Developers Obsolete // MLOps Podcast #366 with Jens Bodal, Senior Software Engineer II, Independent


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// Abstract

AI agents are shifting the role of developers from writing code to defining intent. This conversation explores why specs are becoming more important than implementation, what breaks in real-world systems, and how engineering teams need to rethink workflows in an agent-driven world.


// Bio

Jens Bodal is a senior software engineer based in Edmonds, Washington, with nine years of experience building developer tooling, internal platforms, and web infrastructure. He spent seven years as an SDE II at Amazon, working on teams including Amazon Games Studio and the AWS Events Management Platform. His work has focused on developer tooling, CI/CD systems, testing infrastructure, and improving the developer experience for teams operating production services. He is particularly interested in developer experience and the growing ecosystem of local tools that help engineers build and run AI systems on infrastructure they control.


// Related Links

Website: https://bodal.devhttps://github.com/jensbodal

https://www.youtube.com/watch?v=Yp7LYdbOuwE


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Timestamps:

[00:00] Specification vs Code

[00:25] Conference Realizations and Insights

[09:01] Agents and Orchestration Insights

[10:39] Coding Agents and Talent

[18:10] Sub-agent Design Concepts

[25:18] Evaling on Vibes

[33:23] Walled Garden and Proxies

[41:48] Spec-Driven Development Limitations

[46:56] Code Ownership vs Authorship

[50:49] Engineering Ownership and PMs

[53:47] Skill Creation and Iteration

[58:40] Wrap up


Hosted by Demetrios, MLOps.community is a space for honest, meandering talks about the real work of making artificial intelligence systems actually work. This isn't about hype or theoretical papers; it's about the messy, practical, and often surprising journey of taking models from a notebook into a live environment. You'll hear from engineers and practitioners who are in the trenches, discussing the tools, the frustrations, and the occasional breakthroughs that define the day-to-day. The conversations are deliberately relaxed, covering everything from traditional machine learning pipelines to the new world of large language models and even the intangible "vibes" of team culture and process. Each episode peels back a layer on what "production" really means, whether that involves deploying a predictive service, managing an agentic system, or maintaining reliability as everything scales. Tuning into this podcast feels like grabbing a coffee with colleagues who aren't afraid to dig into the technical nitty-gritty while keeping the tone conversational and accessible. It's for anyone who builds, manages, or is just curious about the operational backbone that allows AI to deliver value, offering a grounded perspective often missing from the broader conversation.
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