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How to Use Caffeine for Conversation-driven edits
Learn Caffeine conversation-driven edits with step by step workflows, realistic examples, and verified plan notes.
Caffeine works well for conversation-driven edits when you run it like production work: locked brief, SOURCE facts, then review before publish. Caffeine builds and hosts software from a description, editable in conversation. Host/Studio/Business plans are listed on caffeine.ai/pricing. Free remix of App Market apps is noted officially; confirm export and hosting terms. Start at /explore/caffeine.
This guide focuses on conversation-driven edits in detail. Related Caffeine articles: /blog/how-to-use-caffeine-for-screen-by-screen-scaffolds, /blog/how-to-use-caffeine-for-hosting-plan-selection, /blog/how-to-use-caffeine-for-app-market-remix-starts.
When this workflow is the right job
Use conversation-driven edits when the deliverable is specifically this Caffeine job. Switch to habit tracker app builds when that workflow already owns the asset.
Step by step workflow
1. Brief Conversation-driven edits
Write what must stay true for conversation-driven edits in Caffeine before settings or spend.
Brief: Conversation-driven edits Keep: verified SOURCE facts only Avoid: invented pricing or features Success: one reviewable output
2. Open Caffeine for Conversation-driven edits
Use the Caffeine surface that owns conversation-driven edits. Do not mix a neighboring workflow in the same pass.
Surface: Conversation-driven edits Start: pilot with one representative input Plans: caffeine.ai/pricing
3. Pilot Conversation-driven edits
Run a single conversation-driven edits pilot. Score clarity, grounding, and whether the output is reviewable.
Pilot: Conversation-driven edits [ ] SOURCE facts match [ ] Output reviewable [ ] Settings logged
4. Refine Conversation-driven edits
Change one conversation-driven edits dimension only. Save a template from the best run.
Refine: Conversation-driven edits Change: one control only Keep: SOURCE and success criteria
Practical conversation-driven edits examples
README install update
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "README install update". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for README install update → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Lint clean pass
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Lint clean pass". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Lint clean pass → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Type narrowing fix
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Type narrowing fix". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Type narrowing fix → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
API docs sync
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "API docs sync". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for API docs sync → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Fixture update
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Fixture update". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Fixture update → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Error message clarity
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Error message clarity". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Error message clarity → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Import cycle break
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Import cycle break". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Import cycle break → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Env validation
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Env validation". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Env validation → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Retry helper
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Retry helper". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Retry helper → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Logging redaction
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Logging redaction". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Logging redaction → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
CLI flag parse
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "CLI flag parse". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for CLI flag parse → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Snapshot refresh
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Snapshot refresh". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Snapshot refresh → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Dead code removal
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Dead code removal". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Dead code removal → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Contract test
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Contract test". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Contract test → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Migration note
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Migration note". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Migration note → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Benchmark script
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Benchmark script". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Benchmark script → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Security header
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Security header". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Security header → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Auth middleware refactor
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Auth middleware refactor". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Auth middleware refactor → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Flaky test fix
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Flaky test fix". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Flaky test fix → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Issue #scoped feature
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Issue #scoped feature". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Issue #scoped feature → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
Rate limit guard
Scenario: A developer uses Caffeine for Conversation-driven edits where the critical change is "Rate limit guard". Objective: Land a reviewable code change for Conversation-driven edits 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 Caffeine for Conversation-driven edits → Review diff for Rate limit guard → Run tests → Commit if green Requirements: - Stay within verified Caffeine capabilities; do not invent features. - Confirm live plan notes on caffeine.ai/pricing 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 Conversation-driven edits.
How to improve conversation-driven edits
Cut noise from conversation-driven edits by removing extra adjectives while preserving SOURCE facts in Caffeine.
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 conversation-driven edits job, audience, and success check before opening Caffeine.
Paste only verified facts under SOURCE so Caffeine cannot invent details.
Specify the deliverable shape up front.
Call out fixed details versus flexible style choices.
Ask Caffeine to flag unsupported claims before you accept the draft.
Limitations to respect
Check Caffeine plan gates for conversation-driven edits on caffeine.ai/pricing before you promise timelines.
Keep drafts unpublished until a human confirms SOURCE facts.
Caffeine can be wrong. Treat conversation-driven edits 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 conversation-driven edits in Caffeine.
Keep a reusable template with variables for conversation-driven edits.
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 conversation-driven edits in Caffeine as a production workflow: brief, pilot, refine, then ship with review. Related reading: /blog/how-to-use-caffeine-for-screen-by-screen-scaffolds, /blog/how-to-use-caffeine-for-hosting-plan-selection, /blog/how-to-use-caffeine-for-app-market-remix-starts.