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“80% of my code is written by AI, 20% is spent reviewing and correcting it.” — Andrej Karpathy
The 80/20 review pattern optimizes this ratio. Instead of reviewing every edit, batch reviews at strategic checkpoints. Between checkpoints, trust the AI and move fast.

The Problem with Constant Review

Reviewing every change kills momentum:
Edit file 1 → Review → Edit file 2 → Review → Edit file 3 → Review
  ↑           ↑         ↑           ↑         ↑           ↑
  2 min       3 min     2 min       3 min     2 min       3 min

Total: 15 minutes (only 6 minutes of actual progress)
Problems:
  • Context switching overhead
  • Interrupts AI’s flow
  • Reviews often find nothing wrong
  • Slows down iteration speed

The 80/20 Solution

Batch reviews at checkpoints:
Edit 5 files → Checkpoint Review → Edit 5 more → Checkpoint Review
  ↑              ↑                   ↑              ↑
  10 min         5 min               10 min         5 min

Total: 30 minutes for 10 files (vs 45 minutes with constant review)
Benefits:
  • 33% faster overall
  • Better context (see changes together)
  • AI maintains flow between reviews
  • Reviews are more thorough (not rushed)

Review Checkpoints

Review at these strategic points:
1

After Plan Approval

Review the plan before any code is written
2

Every 5 File Edits

Checkpoint review during implementation
3

Before Destructive Operations

Review before git operations, deletions, or schema changes
4

At Wrap-Up

Final review before ending the session

Checkpoint 1: After Plan Approval

When: Before any implementation begins What to review:
  • Does the plan make sense?
  • Are all affected files identified?
  • Are risks and mitigations reasonable?
  • Is the approach aligned with project patterns?
Example:
PLAN: Add Webhook Support

Files to modify: 4 files
New files: 2 files
Approach: Event-driven with retry logic
Risks: High volume, circular webhooks

✓ Review: Plan approved, proceed
This is the most important review point. A bad plan leads to many corrections later.

Checkpoint 2: Every 5 File Edits

When: After editing 5 files (or ~20 minutes of work) What to review:
  • Are changes following the plan?
  • Any obvious bugs or logic errors?
  • Tests passing?
  • Ready to continue or need course correction?
Example:
CHECKPOINT: 5 files edited

Completed:
✓ src/models/webhook.ts - Model validation
✓ src/api/events.ts - Event hooks
✓ src/services/delivery.ts - HTTP delivery
✓ src/queue/webhook-queue.ts - Retry logic
✓ migrations/001-webhooks.sql - Schema

Tests: 18/18 passing
Typecheck: Clean

→ Continue to next 5 files

Checkpoint 3: Before Destructive Operations

When: Before operations that are hard to undo Destructive operations:
  • git commit (review before committing)
  • git push (double-check before pushing)
  • File deletion (verify files should really be deleted)
  • Schema changes (migrations are hard to reverse)
  • npm publish (can’t unpublish)
Example:
About to commit:
  M src/models/webhook.ts
  M src/api/events.ts
  A migrations/001-webhooks.sql
  D old-webhook-implementation.ts  ← Verify deletion

Pause for review before commit.

Checkpoint 4: At Wrap-Up

When: Before ending the session What to review:
  • All changes across the session
  • Uncommitted work
  • TODOs or console.log statements
  • What was learned?
  • Any corrections to capture?
Use /wrap-up command:
/wrap-up
See Wrap-Up Ritual guide for details.

Between Checkpoints: Trust Mode

Between review checkpoints, operate in trust mode:
Let AI work without interruption
Run tests automatically after each file
Watch for test failures (pause if tests break)
Trust the plan and process

Quality Gates

Automatic quality gates run between checkpoints:
# Automatically run relevant tests
npm test -- path/to/changed-file.test.ts
Tests catch regressions immediately.

Hook Integration

Pro Workflow hooks enforce checkpoint reviews: PreToolUse Hook (tracks edit count)
{
  "hooks": {
    "PreToolUse": "Track edit count. Remind at 5, 10, 15 edits."
  }
}
PreToolUse Hook (before git operations)
{
  "hooks": {
    "PreToolUse": "Before git commit/push, remind about quality gates."
  }
}
Stop Hook (context-aware reminders)
{
  "hooks": {
    "Stop": "If >5 edits since last checkpoint, suggest review."
  }
}

Review Checklist

What to look for at each checkpoint:
  • Logic matches the plan
  • Edge cases handled
  • Error cases handled
  • No obvious bugs
  • Calculations and conditions correct
  • Follows existing patterns
  • Clear variable and function names
  • No unnecessary duplication
  • Comments for non-obvious logic
  • No debug statements (console.log, debugger)
  • No hardcoded secrets
  • Input validation present
  • SQL injection prevention
  • XSS prevention
  • Authentication checks
  • Tests passing
  • New tests for new code
  • Edge cases tested
  • Error cases tested
  • Coverage maintained or increased
  • No obvious N+1 queries
  • Large loops optimized
  • Appropriate indexes (database)
  • Caching where needed
  • No memory leaks

When to Pause Mid-Flow

Sometimes you need to pause before the next checkpoint: Pause if:
  • Tests suddenly break
  • Error messages you don’t understand
  • AI asks a clarifying question
  • Approach seems wrong
  • About to make a destructive change
Don’t pause for:
  • Stylistic preferences (add to LEARNED instead)
  • Minor improvements (note for later)
  • Curiosity about implementation (trust the process)

Correction Workflow

When you find an issue at a checkpoint:
1

Point out the issue

Be specific: “The webhook retry logic doesn’t handle 404s correctly”
2

Let AI propose fix

AI explains what went wrong and proposes solution
3

Capture as learning

[LEARN] Error Handling: Webhooks should not retry on 404 (permanent failure)
4

Apply fix

AI fixes the issue
5

Verify fix

Run tests to confirm fix works
6

Continue

Resume trust mode until next checkpoint

Metrics and Analytics

Track your review effectiveness:
/insights
Metrics to watch:
  • Corrections per checkpoint: Should decrease over time
  • Issues found: More at early checkpoints vs late (front-load validation)
  • Time between checkpoints: Should be consistent (5 files or ~20 min)
  • Tests catching issues: High number means good test coverage

Comparison: Constant vs Checkpoint Review

FactorConstant ReviewCheckpoint Review (80/20)
SpeedSlow (many interruptions)Fast (sustained flow)
ContextLost between reviewsPreserved between checkpoints
ThoroughnessRushed, shallowBatch review is deeper
AI FlowInterruptedMaintained
Time to completion40-60% longerBaseline
Corrections foundSameSame (batched)

Best Practices

Do

Review the plan thoroughly before implementation
Pause every 5 file edits for checkpoint review
Run quality gates automatically
Trust the process between checkpoints
Capture corrections as learnings
Use /wrap-up for final review

Don’t

Integration with Other Patterns

Multi-Phase Development
  • Each phase has its own review checkpoint
  • Research phase: review confidence score
  • Plan phase: review plan before implementation
  • Implement phase: review every 5 edits
  • Final phase: wrap-up review
Self-Correction Loop
  • Corrections found at checkpoints → [LEARN] rules
  • Rules prevent same issues at future checkpoints
  • Checkpoints become faster over time
Agent Teams
  • Each teammate reports at checkpoints
  • Lead reviews all teammate outputs together
  • Synchronization points prevent conflicts

Real-World Example

9:00 AM - Planning Phase
  → Review: Plan approved (Checkpoint 1)

9:15 AM - Implementation starts
  → Edit: 5 files (models, services, routes)
  → Tests: All passing
  → Checkpoint 2: Review, all good

9:35 AM - Continue implementation  
  → Edit: 5 more files (tests, migrations, docs)
  → Tests: All passing
  → Checkpoint 3: Found issue with migration
  → Fix: Update migration script
  → Verify: Tests still passing

9:55 AM - Quality gates
  → Lint: Clean
  → Typecheck: Clean  
  → Tests: 45/45 passing
  → Checkpoint 4: Ready to commit

10:00 AM - Commit
  → Review git diff (Checkpoint 5)
  → Commit with conventional message
  → /wrap-up (Checkpoint 6)

Total: 1 hour, 10 files edited, 1 issue found and fixed

Without checkpoints: Would have taken 1.5 hours with constant review

Adjusting Checkpoint Frequency

Tune checkpoint frequency based on complexity:
Task ComplexityCheckpoint Frequency
Simple, well-understoodEvery 7-10 files
Moderate complexityEvery 5 files (default)
High complexity, new domainEvery 3 files
Critical (auth, payments)Every 1-2 files
ExperimentationEvery 10+ files (trust mode)

Next Steps

Self-Correction Loop

Capture review findings as learnings

Multi-Phase Development

Apply checkpoints in structured workflows

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