Claude Code

Definition

Plain language

Anthropic's AI coding assistant that can read your codebase and do work for you.

Also called: Claude Tools

Why it matters: It's a leading example of moving AI from autocomplete to full agentic software work, reshaping how engineering teams actually use models.

For example, a developer types 'find why the login test is flaky and fix it,' and Claude Code reads the repo, edits files, and runs tests until it passes.

Heard on the show

“… A team fired over four thousand of these poisoned bug reports at Cursor, Claude Code, and OpenAI's Codex — the real tools, in their real settings — and two out of three attacks got …”

Mentioned in 24 episodes

1. 227
   Poisoned Bug Reports Fooled Coding Agents Two Times Out of Three
2. 222
   The Bias Isn't in Your Prompt — It's Inside the Model
3. 202
   How Do You Know an AI Agent Actually Refused? Check the World, Not the Words
4. 196
   AI Agents Reached Opposite Conclusions From the Same Data — and Passed Review
5. 195
   Why 'Be Careful' Does Nothing for AI Coding Agents, and What Does
6. 184
   An AI Built an Undetectable Secret Channel, And Another AI Couldn't Find It
7. 166
   A Router That Beats the Frontier Models It Calls
8. 159
   Can a Coding Agent Run Its Own Robot Experiments Overnight, With No Human Resetting the Scene?
9. 157
   When an AI Coding Agent Drives a Phone Through the Terminal, No Screen Needed
10. 150
    Don't Kill the Loser: A Different Way to Handle Two AI Agents Colliding
11. 131
    Why Autonomous Research Agents Forget Their Own Lessons, and Arbor's Fix
12. 130
    Why AI Agents Coordinate Better Through a Shared Board Than a Boss
13. 112
    When an AI Agent Cheats Without Being Told: Inside the Meta-Agent Challenge
14. 102
    How to Catch an AI Attack That No Single Conversation Reveals
15. 086
    Why Frozen-Weight Agents Still Get Worse Over Time
16. 078
    Training a Markdown File: When LLM Self-Improvement Borrows the Discipline of Neural Net Training
17. 075
    Growing Code and Proof Together: Verified Systems in Ten Hours Instead of a Year
18. 057
    How Uber Caught 206 Leaked Credentials With an LLM-Powered Security Stack
19. 046
    When the AI Optimizer Edits the Grade Book: Why Harnessing Evolution Needs a Wall
20. 029
    Why Forty-Eight Percent on FrontierMath Isn't the Real Story in DeepMind's New Math Paper
21. 028
    Teaching a Model to Hire Copies of Itself: Recursive Agent Optimization
22. 024
    An AI Agent That Found 28 Zero-Days in Windows — And What Made It Work
23. 016
    Why Your Coding Agent Stalls While the GPU Runs Hot
24. 005
    Why a Debugger Designed for Humans Is the Wrong Tool for an AI Agent

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