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AI Coding Agents Comparison

Jun 23, 2025

Overview

The speaker compares Claude Code and Cursor as AI coding agents, discusses hands-on experience using Claude Code within Cursor, and explores best practices for effective agentic coding workflows in modern software development.

Claude Code vs. Cursor: Interface and Workflow

  • Evaluates whether terminal-based Claude Code is superior to Cursor’s UI for agent interaction and code review.
  • Details using Claude Code inside Cursor, switching between terminal and dedicated agent windows.
  • Finds terminal integration flexible, but prefers Cursor’s chat UI for granular code review and approval.
  • Notes Cursor requires manual approval for each file change, while Claude Code allows more automated, broad changes.

Performance and Capabilities Comparison

  • Both tools access Claude’s top models, Sonnet and Opus, with no significant difference in model performance based on interface.
  • Claude Code is more effective for large, multi-file tasks, while Cursor excels for smaller, tightly scoped fixes and collaborative frontend work.
  • Background agents and task delegation are increasingly important; Claude Code is seen as stronger for autonomous, complex task execution.

Key Features and Integrations

  • Claude Code runs anywhere via terminal, integrating with Cursor, VS Code, Windsurf, and more.
  • Direct MCP integration allows syncing with workflow tools like Linear for issue tracking and task management.
  • Custom slash commands and persistent memory files (claw.md) enable tailored agent behavior and reusable workflows.
  • GitHub Actions integration allows Claude Code to operate on remote PRs and tasks, extending agent automation beyond local environments.

Planning and Best Practices

  • “Plan mode” is critical: users should prompt Claude Code to draft a detailed plan before starting major features.
  • Using keywords like “think hard” or “ultrathink” enhances plan depth and thoughtfulness.
  • Plans should be explicit, as agents require clear instructions to avoid missing implementation details.
  • Reviewing and iterating plans with the agent is essential to aligning expectations before execution.

Limitations and Areas for Improvement

  • Multitasking is challenging; running multiple instances risks git conflicts unless carefully managed (work trees recommended).
  • Claude Code’s terminal UI is less effective for detailed, line-by-line code review compared to Cursor’s interface.
  • Some styling and front-end tweaks may require manual adjustments post-agent execution.
  • Explicit details must be included in agent plans, as agents don’t infer implicit workflow steps.

Evolving Role of Developers

  • Software development is shifting from writing code to engineering and orchestrating agents that generate code.
  • Most project code is now written by AI, but developers still intervene for design sensitivity and complex collaboration.
  • Creating effective agent instructions and memory files is a key emerging skill.

Decisions

  • Adopt planning phase as a standard practice before executing complex tasks with Claude Code or any agent.
  • Use Claude Code for large, multi-file, autonomous tasks; use Cursor for collaborative, iterative frontend work.

Action Items

  • TBD – Speaker: Explore and document advanced multitasking workflows with git work trees in Claude Code.
  • TBD – Speaker: Refine memory files (claw.md) to provide more precise instructions for future agent tasks.