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How to Use Air for Agent choice for task fit
Learn Air agent choice for task fit with step by step workflows, realistic examples, and verified plan notes.
Air works well for agent choice for task fit when you run it like production work: locked brief, SOURCE facts, then review before publish. Air is JetBrains Agentic Development Environment for parallel coding agents with Docker or Git worktree isolation. Requires JetBrains AI Pro/Ultimate or BYOK. Confirm task definition and review workflows in JetBrains Air docs. Start at /explore/air.
This guide focuses on agent choice for task fit in detail. Related Air articles: /blog/how-to-use-air-for-isolation-mode-selection, /blog/how-to-use-air-for-diff-review-before-commit, /blog/how-to-use-air-for-multi-file-feature-implementation.
When this workflow is the right job
Use agent choice for task fit when the deliverable is specifically this Air job. Switch to parallel agent tasks in worktrees when that workflow already owns the asset.
Step by step workflow
1. Brief Agent choice for task fit
Write what must stay true for agent choice for task fit in Air before settings or spend.
Brief: Agent choice for task fit Keep: verified SOURCE facts only Avoid: invented pricing or features Success: one reviewable output
2. Open Air for Agent choice for task fit
Use the Air surface that owns agent choice for task fit. Do not mix a neighboring workflow in the same pass.
Surface: Agent choice for task fit Start: pilot with one representative input Plans: air.dev
3. Pilot Agent choice for task fit
Run a single agent choice for task fit pilot. Score clarity, grounding, and whether the output is reviewable.
Pilot: Agent choice for task fit [ ] SOURCE facts match [ ] Output reviewable [ ] Settings logged
4. Refine Agent choice for task fit
Change one agent choice for task fit dimension only. Save a template from the best run.
Refine: Agent choice for task fit Change: one control only Keep: SOURCE and success criteria
Practical agent choice for task fit examples
README install update
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "README install update". Objective: Land a reviewable code change for Agent choice for task fit that addresses README install update, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for README install update - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for README install update → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on README install update, test results, and a short summary of what changed for Agent choice for task fit.
Lint clean pass
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Lint clean pass". Objective: Land a reviewable code change for Agent choice for task fit that addresses Lint clean pass, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Lint clean pass - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Lint clean pass → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Lint clean pass, test results, and a short summary of what changed for Agent choice for task fit.
Type narrowing fix
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Type narrowing fix". Objective: Land a reviewable code change for Agent choice for task fit that addresses Type narrowing fix, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Type narrowing fix - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Type narrowing fix → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Type narrowing fix, test results, and a short summary of what changed for Agent choice for task fit.
API docs sync
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "API docs sync". Objective: Land a reviewable code change for Agent choice for task fit that addresses API docs sync, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for API docs sync - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for API docs sync → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on API docs sync, test results, and a short summary of what changed for Agent choice for task fit.
Fixture update
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Fixture update". Objective: Land a reviewable code change for Agent choice for task fit that addresses Fixture update, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Fixture update - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Fixture update → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Fixture update, test results, and a short summary of what changed for Agent choice for task fit.
Error message clarity
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Error message clarity". Objective: Land a reviewable code change for Agent choice for task fit that addresses Error message clarity, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Error message clarity - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Error message clarity → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Error message clarity, test results, and a short summary of what changed for Agent choice for task fit.
Import cycle break
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Import cycle break". Objective: Land a reviewable code change for Agent choice for task fit that addresses Import cycle break, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Import cycle break - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Import cycle break → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Import cycle break, test results, and a short summary of what changed for Agent choice for task fit.
Env validation
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Env validation". Objective: Land a reviewable code change for Agent choice for task fit that addresses Env validation, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Env validation - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Env validation → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Env validation, test results, and a short summary of what changed for Agent choice for task fit.
Retry helper
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Retry helper". Objective: Land a reviewable code change for Agent choice for task fit that addresses Retry helper, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Retry helper - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Retry helper → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Retry helper, test results, and a short summary of what changed for Agent choice for task fit.
Logging redaction
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Logging redaction". Objective: Land a reviewable code change for Agent choice for task fit that addresses Logging redaction, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Logging redaction - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Logging redaction → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Logging redaction, test results, and a short summary of what changed for Agent choice for task fit.
CLI flag parse
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "CLI flag parse". Objective: Land a reviewable code change for Agent choice for task fit that addresses CLI flag parse, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for CLI flag parse - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for CLI flag parse → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on CLI flag parse, test results, and a short summary of what changed for Agent choice for task fit.
Snapshot refresh
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Snapshot refresh". Objective: Land a reviewable code change for Agent choice for task fit that addresses Snapshot refresh, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Snapshot refresh - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Snapshot refresh → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Snapshot refresh, test results, and a short summary of what changed for Agent choice for task fit.
Dead code removal
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Dead code removal". Objective: Land a reviewable code change for Agent choice for task fit that addresses Dead code removal, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Dead code removal - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Dead code removal → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Dead code removal, test results, and a short summary of what changed for Agent choice for task fit.
Contract test
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Contract test". Objective: Land a reviewable code change for Agent choice for task fit that addresses Contract test, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Contract test - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Contract test → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Contract test, test results, and a short summary of what changed for Agent choice for task fit.
Migration note
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Migration note". Objective: Land a reviewable code change for Agent choice for task fit that addresses Migration note, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Migration note - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Migration note → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Migration note, test results, and a short summary of what changed for Agent choice for task fit.
Benchmark script
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Benchmark script". Objective: Land a reviewable code change for Agent choice for task fit that addresses Benchmark script, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Benchmark script - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Benchmark script → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Benchmark script, test results, and a short summary of what changed for Agent choice for task fit.
Security header
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Security header". Objective: Land a reviewable code change for Agent choice for task fit that addresses Security header, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Security header - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Security header → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Security header, test results, and a short summary of what changed for Agent choice for task fit.
Auth middleware refactor
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Auth middleware refactor". Objective: Land a reviewable code change for Agent choice for task fit that addresses Auth middleware refactor, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Auth middleware refactor - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Auth middleware refactor → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Auth middleware refactor, test results, and a short summary of what changed for Agent choice for task fit.
Flaky test fix
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Flaky test fix". Objective: Land a reviewable code change for Agent choice for task fit that addresses Flaky test fix, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Flaky test fix - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Flaky test fix → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Flaky test fix, test results, and a short summary of what changed for Agent choice for task fit.
Issue #scoped feature
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Issue #scoped feature". Objective: Land a reviewable code change for Agent choice for task fit that addresses Issue #scoped feature, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Issue #scoped feature - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Issue #scoped feature → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Issue #scoped feature, test results, and a short summary of what changed for Agent choice for task fit.
Rate limit guard
Scenario: A developer uses Air for Agent choice for task fit where the critical change is "Rate limit guard". Objective: Land a reviewable code change for Agent choice for task fit that addresses Rate limit guard, with tests or checks run. Inputs: - Relevant file/symbol paths - Failing test or issue text for Rate limit guard - Constraints: no public API breaks unless stated - Test/lint command to run after edits Workflow: Scope files → Instruct Air for Agent choice for task fit → Review diff for Rate limit guard → Run tests → Commit if green Requirements: - Stay within verified Air capabilities; do not invent features. - Confirm live plan notes on air.dev before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Never apply destructive commands without review. Expected output: A diff centered on Rate limit guard, test results, and a short summary of what changed for Agent choice for task fit.
How to improve agent choice for task fit
Cut noise from agent choice for task fit by removing extra adjectives while preserving SOURCE facts in Air.
Raise quality by insisting on a single success check before debating style.
Make review easier by labeling fields that must never change.
Speed iteration by cloning the last good run and altering only one control.
Stabilize outputs by pinning settings after the pilot is approved.
Reduce rework by rejecting drafts that invent claims.
Improve handoffs by recording which control produced the best result.
Harden the workflow by testing an incomplete input before trusting defaults.
Prompting and usage guidance
Name the agent choice for task fit job, audience, and success check before opening Air.
Paste only verified facts under SOURCE so Air cannot invent details.
Specify the deliverable shape up front.
Call out fixed details versus flexible style choices.
Ask Air to flag unsupported claims before you accept the draft.
Limitations to respect
Check Air plan gates for agent choice for task fit on air.dev before you promise timelines.
Keep drafts unpublished until a human confirms SOURCE facts.
Air can be wrong. Treat agent choice for task fit as provisional until review.
If documentation is silent on a claim, leave it out rather than guessing.
Practical tips for this workflow
Pilot once before batching agent choice for task fit in Air.
Keep a reusable template with variables for agent choice for task fit.
Separate creative instructions from SOURCE facts.
Log settings from the best run.
Common mistakes
- Skipping the pilot run before scaling volume
- Inventing pricing, quotas, or features not on official pages
- Mixing unrelated workflows in one session
- Publishing without a human review gate
Treat agent choice for task fit in Air as a production workflow: brief, pilot, refine, then ship with review. Related reading: /blog/how-to-use-air-for-isolation-mode-selection, /blog/how-to-use-air-for-diff-review-before-commit, /blog/how-to-use-air-for-multi-file-feature-implementation.