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Why do AI systems silently fail? How can you set up a system that produces results while also reviewing and validating the work? This week on the show, Calvin Hendryx-Parker returns to discuss his recent talk "Orchestrate Agentic AI: Context, Checklists, and No-Miss Reviews."
Test your understanding of Git basics for Python projects, including commits, the staging area, branches, merges, and working with remote repos.
Test your grasp of the CPython source code, from bytecode and memory management to frames and generators. Based on the CPython 3.8 walkthrough.
Learn how to use Claude Code to build and debug Python projects with natural-language commands right from your terminal.
Test your understanding of how to review AI-generated Python code, from automated checks to the bugs that coding agents get wrong most often.
Test your understanding of Claude Code by working through installation, plan mode, diff review, and debugging a Python project.
Learn how to use Python's deque to efficiently append and pop items from both ends, build queues and stacks, and set maxlen for bounded history.
Check your understanding of using Arduino with Python. Practice setting up circuits, using the Firmata protocol, and controlling inputs and outputs.
Test your understanding of Python's deque. Practice fast appends and pops at both ends, building queues and stacks, and setting maxlen.
Learn AI debugging by pairing with an AI coding agent: reproduce the bug with a failing test, give your agent context, then verify the fix.
Test your understanding of debugging Python code with an AI agent, from reproducing a bug with a failing test to verifying the fix.
What bottlenecks were preventing NumPy from scaling on free-threaded Python? Christopher Trudeau is back on the show this week with another batch of PyCoder's Weekly articles and projects.
