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Agentic Coding Live with Chelsea Troy

Published by O'Reilly Media, Inc.

Intermediate content levelIntermediate

Claude Code content, driven by conversation

What you’ll learn and how you can apply it

  • Learn strategies for advanced agentic coding

Course description

Join Chelsea Troy, machine learning team lead at Mozilla, for a live session on agentic coding that will be driven entirely by your questions and conversation. You’ll explore advanced agentic coding situations and problems O’Reilly members are facing, and solve them with Chelsea in real time using Claude Code.

To get the most out of this session, you should understand the basics of agentic coding: That means you’ve worked with coding assistants before and you know how LLMs work. (If you’re still a beginner, complete O’Reilly’s Agentic Coding skill plan before this course takes place to get up to speed.)

Save your seat to learn what real-world agentic coding looks like beyond the AI equivalent of “Hello, World” and explore what’s actually possible. And be sure to come with your questions.

Topics may include:

  • A deep dive into Python internals
  • Deconstructing the compiler and parser
  • High-stakes performance engineering
  • The future of concurrency and objects

This live event is for you because...

  • You’re a software engineer working with Claude Code and you want to go beyond basics to explore advanced use cases.
  • You work with software engineers and you want to see an example of what they’re doing with AI tooling.
  • You want to become an engineer and you’re curious to see what agentic coding is all about.

Prerequisites

  • Knowledge of agentic coding (beginners can complete O’Reilly’s Agentic Coding skill plan to gain appropriate experience)
  • Python programming experience

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Welcome and introduction (10 minutes)

Scoping the problem we plan to solve (10 minutes)

Discussion of context management for investigation (20 minutes)

Execution of initial investigation (20 minutes)

Break

Refinement and specification (20 minutes)

Execution (20 minutes)

Identifying gaps and next steps (10 minutes)

Wrap-up

Your Instructor

  • Chelsea Troy

    Chelsea Troy leads the machine learning operations team at Mozilla. She also teaches in the Master’s Program in Computer Science at the University of Chicago. Her online workshop, Fundamentals of Technical Debt, is available On Demand through the O’Reilly platform, and she also gives live courses about machine learning, large language models, and product thinking.

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Skill covered

Coding Practices