Mastering Agentic Coding & GPUs

Part 1

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— Building Effective Agentic Coding Systems
This section focuses on how to design and operate a production-ready agentic coding environment. We’ll cover how to plan projects for agent collaboration, develop unit tests that guide and constrain agent behavior, and set up CI/CD pipelines with best practices for safety and reliability. You’ll learn strategies for managing versions, overcoming content length limits in agent workflows, and evaluating agentic output for correctness and quality. We’ll also explore how agents interact with Kubernetes for orchestration and how to keep your code, data, and intellectual property secure when agents are writing and executing code.

 

Part 2

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— Compute Foundations for Agentic Systems
This section demystifies how modern compute especially GPUs power agentic systems at scale. We’ll explain how GPUs work, best practices for using them effectively, and practical paths for learning CUDA without getting lost in theory. You’ll see how GPUs integrate with Kubernetes, how to schedule and manage GPU workloads, and how to scale agent-driven workloads efficiently across clusters. The goal is to give you a mental model for matching agentic workloads to the right compute architecture as systems grow from experimentation to production.

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