When to Use Agent vs Ask Mode

Agent vs Ask mode describes the spectrum every AI coding tool offers between read-only analysis and autonomous execution: Cursor’s Ask and Agent modes, Claude Code’s Plan and Normal modes, and Codex’s read-only and workspace-write sandboxes. Read-only mode answers questions without editing files; guided execution reads, edits, and runs commands with permission checks; full autonomy runs unattended. Picking the wrong point on that spectrum wastes context or risks unreviewed changes.

You need to understand how your payment processing module works before refactoring it. You open the AI in its default agent mode, ask “how does payment processing work in this codebase?” and the AI immediately starts reading files, running grep commands, and consuming 40,000 tokens of context before giving you a three-sentence answer. You could have gotten the same answer with a fraction of the context usage if you had used the right mode.

Every tool — Cursor, Claude Code, and Codex — provides modes that control how much autonomy the AI has. The spectrum ranges from “read and analyze only” to “execute everything autonomously.” Understanding this spectrum and when to use each setting is fundamental to working efficiently.

What This Mode-Spectrum Guide Gives You

• A clear mapping of modes across all three tools
• Decision criteria for choosing the right mode for each task type
• Prompts optimized for each mode
• Strategies for transitioning between modes during a single workflow

The Mode Spectrum

All three tools share the same fundamental spectrum, even though they use different terminology:

Capability	Cursor	Claude Code	Codex
Read-only analysis	Ask mode (or Plan mode to draft a plan)	Plan Mode (Shift+Tab)	--sandbox read-only -c approval_policy=on-request
Guided execution	Agent mode (default)	Normal Mode (default)	--sandbox workspace-write -c approval_policy=on-request
Unattended, sandboxed execution	Auto-Run “Run Everything” / Cloud Agent	--dangerously-skip-permissions / Sandbox	--sandbox workspace-write -c approval_policy=never (trusted runs only)

Read-Only / Analysis Mode

Use this when you want to understand code without modifying it. The AI reads files and answers questions but cannot make changes.

Cursor

Switch to Ask mode in the mode selector. The AI will analyze code and answer questions without making changes. For investigations that should end in a written plan rather than edits, Plan mode is the sibling to reach for:

How does the authentication flow work? Trace the request from
the login endpoint through middleware to the session store.
Show me the key files and functions involved.

Ask mode is token-efficient because the AI focuses on answering your question rather than exploring broadly. It uses the codebase index for retrieval rather than reading files one by one.

Claude Code

Toggle Plan Mode with Shift+Tab. Claude will read files and explore the codebase but cannot write to any file or run destructive commands:

Explain the authentication flow. Start from the login endpoint
and trace through middleware, session management, and token
refresh. Identify the key files and any potential issues.

Plan Mode is particularly useful for code reviews and architecture analysis. Claude can read as many files as needed without risk of accidental modification.

Codex

Use a read-only sandbox so Codex can browse and reason but cannot edit files. Keep approval_policy=on-request explicit; approval policy controls escalation prompts, while the sandbox enforces the filesystem boundary:

codex --sandbox read-only -c approval_policy=on-request \
  "Explain the authentication flow in this codebase. Trace the request \
   lifecycle from login to session creation. Identify key files and \
   potential security concerns."

In the Codex IDE extension, choose a read-only planning workflow when you want analysis without edits.

Best for: Code review, architecture analysis, onboarding to a new codebase, understanding unfamiliar code, investigating bugs before fixing them.

Guided Execution Mode

The default mode for all three tools. The AI can read files, make changes, and run commands, but asks for permission at key points. This is the workhorse mode for most development tasks.

Cursor

Agent mode is the default. Cursor’s agent reads files, proposes edits, and runs terminal commands. You can review changes in the diff view before accepting:

Implement the rate limiter middleware following the pattern in
@src/middleware/auth.ts. Write tests in @src/middleware/__tests__/.
Run the tests after implementation.

Configure which tools the agent can use in Cursor Settings. You can allow file edits but require approval for terminal commands, or vice versa.

Claude Code

Normal Mode is the default. Claude asks permission for file writes and potentially destructive commands, but reads files freely:

Implement the rate limiter middleware following the pattern in
src/middleware/auth.ts. Write tests and run them. Fix any
failures before finishing.

Tune the permission level with /permissions. Allow specific safe commands (like npm test) to reduce interruptions while keeping approval for destructive operations.

Codex

Run with workspace-write and on-request configured explicitly. Routine reads, edits, and commands allowed by the workspace sandbox can proceed without a prompt; Codex asks when it needs to cross the sandbox boundary:

codex --sandbox workspace-write -c approval_policy=on-request \
  "Implement the rate limiter middleware following existing patterns. \
   Write tests and run them. Fix any failures."

In the IDE extension, Codex shows inline diffs for each proposed change. Accept or reject individual hunks rather than whole files.

Best for: Feature implementation, bug fixes, refactoring, test writing, most day-to-day development work.

Full Autonomy Mode

The AI runs without interruption. Powerful for well-defined, low-risk tasks. Dangerous for anything touching sensitive code.

Cursor

Auto-Run set to Run Everything (informally called YOLO mode) auto-accepts all changes and commands. Cloud Agent runs tasks asynchronously in an isolated cloud environment:

Fix all ESLint warnings in src/components/. Run npm run lint
after each fix to verify. Commit each fix separately with a
descriptive message.

Cloud Agent is the safer option for autonomous work. It runs on a clone of your repo in an isolated cloud environment, so your local working directory stays untouched until you review and merge the changes.

Claude Code

Use --dangerously-skip-permissions for batch operations, or enable sandbox mode (/sandbox) for safer autonomy:

claude --dangerously-skip-permissions -p \
  "Fix all ESLint warnings in src/components/. Commit each fix separately."

Sandbox mode is preferred because it provides autonomy within defined boundaries (filesystem and network restrictions) rather than bypassing all safety checks.

Codex

For a trusted unattended job, approval_policy=never suppresses prompts but does not expand sandbox access. Always keep the sandbox explicit; if Codex needs to cross its boundary, that action fails instead of prompting:

codex exec --sandbox workspace-write -c approval_policy=never \
  "Fix all ESLint warnings in src/components/. Commit each fix \
   with a descriptive message."

Use this only in a trusted CI identity or disposable checkout. Codex Cloud tasks run in a separate hosted environment, so local files remain untouched until you apply or merge the resulting diff.

Best for: Lint fixes, formatting, bulk renames, documentation generation, test boilerplate, migration scripts across many files.

Full autonomy requires strong guardrails

Never use full autonomy mode on security-sensitive code, database migrations, or infrastructure changes. Even with sandbox isolation, the AI can make subtle mistakes that pass tests but break things in production. Reserve autonomous mode for mechanical, low-risk tasks where the definition of “correct” is clear and verifiable.

Decision Framework

Use this flowchart when choosing a mode:

1. Are you trying to understand code, not change it? Use read-only/analysis mode.
2. Is the task well-defined with clear verification? Use guided execution mode and let the AI work through the task with your periodic review.
3. Is the task mechanical and low-risk? Consider full autonomy mode with appropriate isolation (cloud agent, sandbox, cloud thread).
4. Is the task touching sensitive code? Use guided execution with per-file approval.
5. Are you unsure what mode to use? Start with guided execution. You can always loosen permissions mid-session.

Copy-paste prompt: Mode transition during a workflow

Phase 1 (Analysis - use ask/plan mode):
Read the payment processing module in src/payments/. Explain the
current architecture and identify the three riskiest areas for
our planned refactoring.

Phase 2 (Planning - stay in ask/plan mode):
Based on your analysis, create a refactoring plan. Save it to
docs/payment-refactor-plan.md. Include risk assessment for each step.

Phase 3 (Implementation - switch to agent/normal mode):
Implement step 1 from the plan. Write tests first, then implement.
Run tests after each change.

Parallel Mode Usage

Advanced teams use different modes simultaneously across multiple sessions:

Cursor

Run a Cloud Agent on a lint-fix task (autonomous) while you use the main Agent for feature development (guided). Review the Cloud Agent’s changes when they are ready, without interrupting your feature work.

Claude Code

Run a headless Claude session to fix lint warnings in one terminal tab while working interactively on a feature in another. Use --continue to pick up any session later:

# Terminal 1: Autonomous lint fixes
claude -p "Fix all ESLint warnings in src/. Commit each fix." --allowedTools "Edit,Bash(npm run lint)"

# Terminal 2: Interactive feature development
claude

Codex

Launch a cloud thread for the mechanical task and work locally on the feature. Codex runs both in parallel:

Cloud thread: Fix all TypeScript strict mode errors in src/utils/.
Commit each fix with type: "fix(types)" message.

Meanwhile, work on your feature locally in the IDE extension or CLI.

Copy-paste prompt: Scoped autonomous batch operation

Fix all [ISSUE TYPE] in [DIRECTORY]. For each fix:

1. Make the minimal change needed
2. Run [VERIFICATION COMMAND] to confirm the fix
3. Commit with message: [COMMIT FORMAT]
4. Move to the next instance

Only modify files in [DIRECTORY]. Do not change test files.
Do not install new dependencies. Do not modify configuration files.

Where Mode Selection Goes Wrong

You stay in analysis mode too long. If you spend 30 minutes asking the AI about the codebase before writing any code, you have consumed context that could have been used for implementation. Set a time box for analysis (5-10 minutes), then switch to implementation.

You use full autonomy on complex tasks. Autonomous mode works for mechanical tasks with clear verification. For tasks requiring judgment (API design, error handling strategy, performance optimization), guided mode with human review produces better results.

You mix modes within a single prompt. Asking the AI to “analyze the auth module, then refactor it” in a single prompt forces it to switch modes internally, which often leads to it skipping the analysis and jumping straight to refactoring. Separate analysis and implementation into distinct prompts.

You forget to switch back. After using analysis mode for investigation, some developers forget to switch back to execution mode and wonder why the AI is not making changes. Check your current mode if the AI seems unresponsive to implementation requests.

Where to Go Next After Choosing a Mode

Human in the Loop Deeper patterns for supervision and review across all modes.

Context Windows How mode choice affects context consumption and session length.

Cost per Context The cost implications of different modes and autonomy levels.

Grill Me & Grill With Docs Ask mode taken to its logical end — the agent interviews you one question at a time until you align.