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Debugging in the Age of Agents

The article explores how debugging practices must evolve with the rise of AI agents and autonomous systems. It discusses the unique challenges of debugging agentic workflows, including non-deterministic behavior, opaque decision-making, and the need for new tools and mental models to trace, monitor, and fix issues in systems that act independently.

Background

- This is a speculative essay set in June 2026, envisioning how software engineering will change once AI coding agents (like Claude, Cursor, or Copilot) reliably write and ship code autonomously. - The title references "debugging" not as fixing bugs in human-written code, but as the new core skill for programmers: reading and correcting code that AI agents write — often incorrectly or with subtle flaws. - The author, Akash Tandon, is a software engineer known for writing about AI-assisted development and the future of programming practice. - Key background: AI coding assistants have rapidly advanced from autocomplete tools (2023–2024) to "agents" that can plan, write, test, and deploy code across multiple files. This has sparked debate about whether human coders will become prompt engineers, code reviewers, or something else entirely. - The piece matters because it argues that "debugging" — traditionally a tedious late-stage task — will become the primary, highest-leverage skill for engineers, reshaping education, workflows, and job definitions.

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