Coding Agents Landscape

AI coding agents comparison, Claude Code vs Cursor, OpenAI Codex vs Claude Code, best AI coding agent 2026, GitHub Copilot vs Cursor, Gemini CLI, how to choose a coding agent, coding agent for engineering teams, terminal coding agent, AI pair programming tools

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• Compare Claude Code, OpenAI Codex, Gemini CLI, GitHub Copilot, and Cursor across architecture, context window, permissions, and cost
• Explain how terminal-native, async-cloud, and IDE-native coding agents differ
• Assess each agent's permissions model and sandboxed execution before rollout
• Estimate and compare the cost structure of each coding agent
• Apply a decision framework to match a coding agent to a team archetype
• Plan a multi-agent strategy and a team rollout playbook
• Account for vendor shifts like the Gemini CLI sunset when choosing a stack

• Url: https://aiacademy.anthropos.work/chapters/coding-agents-landscape-intro/ · Coding Agents Landscape: Start Here · Position: 1 · A 12-minute orientation to five coding agents whose feature lists have converged near 1M context — so the real decision is fit, not capability.
• Url: https://aiacademy.anthropos.work/chapters/claude-code-overview/ · Claude Code Overview · Position: 2 · Anthropic's terminal-native coding agent — architecture, 1M-token context, permissions, cost model, and honest trade-offs for engineering managers evaluating their options.
• Url: https://aiacademy.anthropos.work/chapters/openai-codex-overview/ · OpenAI Codex Overview · Position: 3 · OpenAI's async-first coding agent — CLI and cloud task architecture, sandboxed execution, permissions model, cost structure, and honest trade-offs for engineering managers evaluating their options.
• Url: https://aiacademy.anthropos.work/chapters/gemini-cli-overview/ · Gemini CLI Overview · Position: 4 · Google's open-source terminal agent — being sunset for consumer, Pro, and Ultra users on 18 June 2026 in favor of the closed-source Antigravity CLI.
• Url: https://aiacademy.anthropos.work/chapters/github-copilot-overview/ · GitHub Copilot Overview · Position: 5 · Microsoft/GitHub's IDE-native coding assistant ecosystem — surfaces, architecture, context handling, permissions, cost model, and honest trade-offs for engineering managers evaluating their options.
• Url: https://aiacademy.anthropos.work/chapters/cursor-overview/ · Cursor Overview · Position: 6 · The AI-native IDE that forks VS Code and weaves multiple models into every editing surface — architecture, context handling, permissions, cost model, and honest trade-offs for engineering managers evaluating their options.
• Url: https://aiacademy.anthropos.work/chapters/picking-the-right-agent/ · Picking the Right Agent · Position: 7 · A decision framework for engineering managers evaluating coding agents — dimensions that matter, team archetypes, multi-agent strategies, and rollout playbook.

• Compare Claude Code, OpenAI Codex, Gemini CLI, GitHub Copilot, and Cursor across architecture, context window, permissions, and cost
• Explain how terminal-native, async-cloud, and IDE-native coding agents differ
• Assess each agent's permissions model and sandboxed execution before rollout
• Estimate and compare the cost structure of each coding agent
• Apply a decision framework to match a coding agent to a team archetype
• Plan a multi-agent strategy and a team rollout playbook
• Account for vendor shifts like the Gemini CLI sunset when choosing a stack

Course Mode: online · Course Workload: PT140M · Mode: online