Debugging

Defense-in-Depth Validation

Overview

When you fix a bug caused by invalid data, adding validation at one place feels sufficient. But that single check can be bypassed by different code paths, refactoring, or mocks.

Core principle: Validate at EVERY layer data passes through. Make the bug structurally impossible.

Why Multiple Layers

Single validation: "We fixed the bug" Multiple layers: "We made the bug impossible"

Different layers catch different cases:

• Entry validation catches most bugs
• Business logic catches edge cases
• Environment guards prevent context-specific dangers
• Debug logging helps when other layers fail

The Four Layers

Layer 1: Entry Point Validation

Purpose: Reject obviously invalid input at API boundary

function createProject(name: string, workingDirectory: string) {
  if (!workingDirectory || workingDirectory.trim() === '') {
    throw new Error('workingDirectory cannot be empty');
  }
  if (!existsSync(workingDirectory)) {
    throw new Error(`workingDirectory does not exist: ${workingDirectory}`);
  }
  if (!statSync(workingDirectory).isDirectory()) {
    throw new Error(`workingDirectory is not a directory: ${workingDirectory}`);
  }
  // ... proceed
}

Layer 2: Business Logic Validation

Purpose: Ensure data makes sense for this operation

function initializeWorkspace(projectDir: string, sessionId: string) {
  if (!projectDir) {
    throw new Error('projectDir required for workspace initialization');
  }
  // ... proceed
}

Layer 3: Environment Guards

Purpose: Prevent dangerous operations in specific contexts

async function gitInit(directory: string) {
  // In tests, refuse git init outside temp directories
  if (process.env.NODE_ENV === 'test') {
    const normalized = normalize(resolve(directory));
    const tmpDir = normalize(resolve(tmpdir()));

    if (!normalized.startsWith(tmpDir)) {
      throw new Error(
        `Refusing git init outside temp dir during tests: ${directory}`
      );
    }
  }
  // ... proceed
}

Layer 4: Debug Instrumentation

Purpose: Capture context for forensics

async function gitInit(directory: string) {
  const stack = new Error().stack;
  logger.debug('About to git init', {
    directory,
    cwd: process.cwd(),
    stack,
  });
  // ... proceed
}

Applying the Pattern

When you find a bug:

1. Trace the data flow - Where does bad value originate? Where used? 2. Map all checkpoints - List every point data passes through 3. Add validation at each layer - Entry, business, environment, debug 4. Test each layer - Try to bypass layer 1, verify layer 2 catches it

Example from Session

Bug: Empty projectDir caused git init in source code

Data flow: 1. Test setup → empty string 2. Project.create(name, '') 3. WorkspaceManager.createWorkspace('') 4. git init runs in process.cwd()

Four layers added:

• Layer 1: Project.create() validates not empty/exists/writable
• Layer 2: WorkspaceManager validates projectDir not empty
• Layer 3: WorktreeManager refuses git init outside tmpdir in tests
• Layer 4: Stack trace logging before git init

Result: All 1847 tests passed, bug impossible to reproduce

Key Insight

All four layers were necessary. During testing, each layer caught bugs the others missed:

• Different code paths bypassed entry validation
• Mocks bypassed business logic checks
• Edge cases on different platforms needed environment guards
• Debug logging identified structural misuse

Don't stop at one validation point. Add checks at every layer.

Defense-in-Depth Validation

Validate at every layer data passes through to make bugs impossible.

Core Principle

Validate at EVERY layer data passes through. Make bug structurally impossible.

When fix bug caused by invalid data, adding validation at one place feels sufficient. But single check can be bypassed by different code paths, refactoring, or mocks.

Why Multiple Layers

Single validation: "We fixed bug" Multiple layers: "We made bug impossible"

Different layers catch different cases:

• Entry validation catches most bugs
• Business logic catches edge cases
• Environment guards prevent context-specific dangers
• Debug logging helps when other layers fail

The Four Layers

Layer 1: Entry Point Validation

Purpose: Reject obviously invalid input at API boundary

function createProject(name: string, workingDirectory: string) {
  if (!workingDirectory || workingDirectory.trim() === '') {
    throw new Error('workingDirectory cannot be empty');
  }
  if (!existsSync(workingDirectory)) {
    throw new Error(`workingDirectory does not exist: ${workingDirectory}`);
  }
  if (!statSync(workingDirectory).isDirectory()) {
    throw new Error(`workingDirectory is not a directory: ${workingDirectory}`);
  }
  // proceed
}

Layer 2: Business Logic Validation

Purpose: Ensure data makes sense for this operation

function initializeWorkspace(projectDir: string, sessionId: string) {
  if (!projectDir) {
    throw new Error('projectDir required for workspace initialization');
  }
  // proceed
}

Layer 3: Environment Guards

Purpose: Prevent dangerous operations in specific contexts

async function gitInit(directory: string) {
  // In tests, refuse git init outside temp directories
  if (process.env.NODE_ENV === 'test') {
    const normalized = normalize(resolve(directory));
    const tmpDir = normalize(resolve(tmpdir()));

    if (!normalized.startsWith(tmpDir)) {
      throw new Error(
        `Refusing git init outside temp dir during tests: ${directory}`
      );
    }
  }
  // proceed
}

Layer 4: Debug Instrumentation

Purpose: Capture context for forensics

async function gitInit(directory: string) {
  const stack = new Error().stack;
  logger.debug('About to git init', {
    directory,
    cwd: process.cwd(),
    stack,
  });
  // proceed
}

Applying the Pattern

When find bug:

1. Trace data flow - Where does bad value originate? Where used? 2. Map all checkpoints - List every point data passes through 3. Add validation at each layer - Entry, business, environment, debug 4. Test each layer - Try to bypass layer 1, verify layer 2 catches it

Example from Real Session

Bug: Empty projectDir caused git init in source code

Data flow: 1. Test setup → empty string 2. Project.create(name, '') 3. WorkspaceManager.createWorkspace('') 4. git init runs in process.cwd()

Four layers added:

• Layer 1: Project.create() validates not empty/exists/writable
• Layer 2: WorkspaceManager validates projectDir not empty
• Layer 3: WorktreeManager refuses git init outside tmpdir in tests
• Layer 4: Stack trace logging before git init

Result: All 1847 tests passed, bug impossible to reproduce

Key Insight

All four layers were necessary. During testing, each layer caught bugs others missed:

• Different code paths bypassed entry validation
• Mocks bypassed business logic checks
• Edge cases on different platforms needed environment guards
• Debug logging identified structural misuse

Don't stop at one validation point. Add checks at every layer.

Root Cause Tracing

Systematically trace bugs backward through call stack to find original trigger.

Core Principle

Trace backward through call chain until finding original trigger, then fix at source.

Bugs often manifest deep in call stack (git init in wrong directory, file created in wrong location). Instinct is to fix where error appears, but that's treating symptom.

When to Use

Use when:

• Error happens deep in execution (not at entry point)
• Stack trace shows long call chain
• Unclear where invalid data originated
• Need to find which test/code triggers problem

The Tracing Process

1. Observe the Symptom

Error: git init failed in /Users/jesse/project/packages/core

2. Find Immediate Cause

What code directly causes this?

await execFileAsync('git', ['init'], { cwd: projectDir });

3. Ask: What Called This?

WorktreeManager.createSessionWorktree(projectDir, sessionId)
  → called by Session.initializeWorkspace()
  → called by Session.create()
  → called by test at Project.create()

4. Keep Tracing Up

What value was passed?

• projectDir = '' (empty string!)
• Empty string as cwd resolves to process.cwd()
• That's the source code directory!

5. Find Original Trigger

Where did empty string come from?

const context = setupCoreTest(); // Returns { tempDir: '' }
Project.create('name', context.tempDir); // Accessed before beforeEach!

Adding Stack Traces

When can't trace manually, add instrumentation:

async function gitInit(directory: string) {
  const stack = new Error().stack;
  console.error('DEBUG git init:', {
    directory,
    cwd: process.cwd(),
    stack,
  });

  await execFileAsync('git', ['init'], { cwd: directory });
}

Critical: Use console.error() in tests (not logger - may not show)

Run and capture:

npm test 2>&1 | grep 'DEBUG git init'

Analyze stack traces:

• Look for test file names
• Find line number triggering call
• Identify pattern (same test? same parameter?)

Finding Which Test Causes Pollution

If something appears during tests but don't know which test:

Use bisection script: scripts/find-polluter.sh

./scripts/find-polluter.sh '.git' 'src/**/*.test.ts'

Runs tests one-by-one, stops at first polluter.

Key Principle

NEVER fix just where error appears. Trace back to find original trigger.

When found immediate cause:

• Can trace one level up? → Trace backwards
• Is this the source? → Fix at source
• Then add validation at each layer (see defense-in-depth.md)

Real Example

Symptom: .git created in packages/core/ (source code)

Trace chain: 1. git init runs in process.cwd() ← empty cwd parameter 2. WorktreeManager called with empty projectDir 3. Session.create() passed empty string 4. Test accessed context.tempDir before beforeEach 5. setupCoreTest() returns { tempDir: '' } initially

Root cause: Top-level variable initialization accessing empty value

Fix: Made tempDir a getter that throws if accessed before beforeEach

Also added defense-in-depth:

• Layer 1: Project.create() validates directory
• Layer 2: WorkspaceManager validates not empty
• Layer 3: NODE_ENV guard refuses git init outside tmpdir
• Layer 4: Stack trace logging before git init

Systematic Debugging

Four-phase debugging framework that ensures root cause investigation before attempting fixes.

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

If haven't completed Phase 1, cannot propose fixes.

The Four Phases

Must complete each phase before proceeding to next.

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

1. Read Error Messages Carefully - Don't skip past errors/warnings, read stack traces completely 2. Reproduce Consistently - Can trigger reliably? Exact steps? If not reproducible → gather more data 3. Check Recent Changes - What changed? Git diff, recent commits, new dependencies, config changes 4. Gather Evidence in Multi-Component Systems

• For EACH component boundary: log data entering/exiting, verify environment propagation
• Run once to gather evidence showing WHERE it breaks
• THEN analyze to identify failing component

5. Trace Data Flow - Where does bad value originate? Trace up call stack until finding source (see root-cause-tracing.md)

Phase 2: Pattern Analysis

Find pattern before fixing:

1. Find Working Examples - Locate similar working code in same codebase 2. Compare Against References - Read reference implementation COMPLETELY, understand fully before applying 3. Identify Differences - List every difference however small, don't assume "that can't matter" 4. Understand Dependencies - What other components, settings, config, environment needed?

Phase 3: Hypothesis and Testing

Scientific method:

1. Form Single Hypothesis - "I think X is root cause because Y", be specific not vague 2. Test Minimally - SMALLEST possible change to test hypothesis, one variable at a time 3. Verify Before Continuing - Worked? → Phase 4. Didn't work? → NEW hypothesis. DON'T add more fixes 4. When Don't Know - Say "I don't understand X", don't pretend, ask for help

Phase 4: Implementation

Fix root cause, not symptom:

1. Create Failing Test Case - Simplest reproduction, automated if possible, MUST have before fixing 2. Implement Single Fix - Address root cause identified, ONE change, no "while I'm here" improvements 3. Verify Fix - Test passes? No other tests broken? Issue actually resolved? 4. If Fix Doesn't Work

• STOP. Count: How many fixes tried?
• If < 3: Return to Phase 1, re-analyze with new information
• If ≥ 3: STOP and question architecture

5. If 3+ Fixes Failed: Question Architecture

• Pattern: Each fix reveals new shared state/coupling problem elsewhere
• STOP and question fundamentals: Is pattern sound? Wrong architecture?
• Discuss with human partner before more fixes

Red Flags - STOP and Follow Process

If catch yourself thinking:

• "Quick fix for now, investigate later"
• "Just try changing X and see if it works"
• "Add multiple changes, run tests"
• "Skip the test, I'll manually verify"
• "It's probably X, let me fix that"
• "I don't fully understand but this might work"
• "One more fix attempt" (when already tried 2+)

ALL mean: STOP. Return to Phase 1.

Human Partner Signals You're Doing It Wrong

• "Is that not happening?" - Assumed without verifying
• "Will it show us...?" - Should have added evidence gathering
• "Stop guessing" - Proposing fixes without understanding
• "Ultrathink this" - Question fundamentals, not just symptoms
• "We're stuck?" (frustrated) - Approach isn't working

When see these: STOP. Return to Phase 1.

Common Rationalizations

Real-World Impact

From debugging sessions:

• Systematic approach: 15-30 minutes to fix
• Random fixes approach: 2-3 hours of thrashing
• First-time fix rate: 95% vs 40%
• New bugs introduced: Near zero vs common

Verification Before Completion

Run verification commands and confirm output before claiming success.

Core Principle

Evidence before claims, always.

Claiming work complete without verification is dishonesty, not efficiency.

The Iron Law

NO COMPLETION CLAIMS WITHOUT FRESH VERIFICATION EVIDENCE

If haven't run verification command in this message, cannot claim it passes.

The Gate Function

BEFORE claiming any status or expressing satisfaction:

1. IDENTIFY: What command proves this claim?
2. RUN: Execute FULL command (fresh, complete)
3. READ: Full output, check exit code, count failures
4. VERIFY: Does output confirm claim?
   - If NO: State actual status with evidence
   - If YES: State claim WITH evidence
5. ONLY THEN: Make claim

Skip any step = lying, not verifying

Common Failures

Red Flags - STOP

• Using "should", "probably", "seems to"
• Expressing satisfaction before verification ("Great!", "Perfect!", "Done!")
• About to commit/push/PR without verification
• Trusting agent success reports
• Relying on partial verification
• Thinking "just this once"
• Tired and wanting work over
• ANY wording implying success without having run verification

Rationalization Prevention

Key Patterns

Tests:

✅ [Run test command] [See: 34/34 pass] "All tests pass"
❌ "Should pass now" / "Looks correct"

Regression tests (TDD Red-Green):

✅ Write → Run (pass) → Revert fix → Run (MUST FAIL) → Restore → Run (pass)
❌ "I've written regression test" (without red-green verification)

Build:

✅ [Run build] [See: exit 0] "Build passes"
❌ "Linter passed" (linter doesn't check compilation)

Requirements:

✅ Re-read plan → Create checklist → Verify each → Report gaps or completion
❌ "Tests pass, phase complete"

Agent delegation:

✅ Agent reports success → Check VCS diff → Verify changes → Report actual state
❌ Trust agent report

When To Apply

ALWAYS before:

• ANY variation of success/completion claims
• ANY expression of satisfaction
• ANY positive statement about work state
• Committing, PR creation, task completion
• Moving to next task
• Delegating to agents

Rule applies to:

• Exact phrases
• Paraphrases and synonyms
• Implications of success
• ANY communication suggesting completion/correctness

The Bottom Line

No shortcuts for verification.

Run command. Read output. THEN claim result.

Non-negotiable.

Creation Log: Systematic Debugging Skill

Reference example of extracting, structuring, and bulletproofing a critical skill.

Source Material

Extracted debugging framework from /Users/jesse/.claude/CLAUDE.md:

• 4-phase systematic process (Investigation → Pattern Analysis → Hypothesis → Implementation)
• Core mandate: ALWAYS find root cause, NEVER fix symptoms
• Rules designed to resist time pressure and rationalization

Extraction Decisions

What to include:

• Complete 4-phase framework with all rules
• Anti-shortcuts ("NEVER fix symptom", "STOP and re-analyze")
• Pressure-resistant language ("even if faster", "even if I seem in a hurry")
• Concrete steps for each phase

What to leave out:

• Project-specific context
• Repetitive variations of same rule
• Narrative explanations (condensed to principles)

Structure Following skill-creation/SKILL.md

1. Rich when_to_use - Included symptoms and anti-patterns 2. Type: technique - Concrete process with steps 3. Keywords - "root cause", "symptom", "workaround", "debugging", "investigation" 4. Flowchart - Decision point for "fix failed" → re-analyze vs add more fixes 5. Phase-by-phase breakdown - Scannable checklist format 6. Anti-patterns section - What NOT to do (critical for this skill)

Bulletproofing Elements

Framework designed to resist rationalization under pressure:

Language Choices

• "ALWAYS" / "NEVER" (not "should" / "try to")
• "even if faster" / "even if I seem in a hurry"
• "STOP and re-analyze" (explicit pause)
• "Don't skip past" (catches the actual behavior)

Structural Defenses

• Phase 1 required - Can't skip to implementation
• Single hypothesis rule - Forces thinking, prevents shotgun fixes
• Explicit failure mode - "IF your first fix doesn't work" with mandatory action
• Anti-patterns section - Shows exactly what shortcuts look like

Redundancy

• Root cause mandate in overview + when_to_use + Phase 1 + implementation rules
• "NEVER fix symptom" appears 4 times in different contexts
• Each phase has explicit "don't skip" guidance

Testing Approach

Created 4 validation tests following skills/meta/testing-skills-with-subagents:

Test 1: Academic Context (No Pressure)

• Simple bug, no time pressure
• Result: Perfect compliance, complete investigation

Test 2: Time Pressure + Obvious Quick Fix

• User "in a hurry", symptom fix looks easy
• Result: Resisted shortcut, followed full process, found real root cause

Test 3: Complex System + Uncertainty

• Multi-layer failure, unclear if can find root cause
• Result: Systematic investigation, traced through all layers, found source

Test 4: Failed First Fix

• Hypothesis doesn't work, temptation to add more fixes
• Result: Stopped, re-analyzed, formed new hypothesis (no shotgun)

All tests passed. No rationalizations found.

Iterations

Initial Version

• Complete 4-phase framework
• Anti-patterns section
• Flowchart for "fix failed" decision

Enhancement 1: TDD Reference

• Added link to skills/testing/test-driven-development
• Note explaining TDD's "simplest code" ≠ debugging's "root cause"
• Prevents confusion between methodologies

Final Outcome

Bulletproof skill that:

• ✅ Clearly mandates root cause investigation
• ✅ Resists time pressure rationalization
• ✅ Provides concrete steps for each phase
• ✅ Shows anti-patterns explicitly
• ✅ Tested under multiple pressure scenarios
• ✅ Clarifies relationship to TDD
• ✅ Ready for use

Key Insight

Most important bulletproofing: Anti-patterns section showing exact shortcuts that feel justified in the moment. When Claude thinks "I'll just add this one quick fix", seeing that exact pattern listed as wrong creates cognitive friction.

Usage Example

When encountering a bug: 1. Load skill: skills/debugging/systematic-debugging 2. Read overview (10 sec) - reminded of mandate 3. Follow Phase 1 checklist - forced investigation 4. If tempted to skip - see anti-pattern, stop 5. Complete all phases - root cause found

Time investment: 5-10 minutes Time saved: Hours of symptom-whack-a-mole

---

Created: 2025-10-03 Purpose: Reference example for skill extraction and bulletproofing

Academic Test: Systematic Debugging Skill

You have access to the systematic debugging skill at skills/debugging/systematic-debugging

Read the skill and answer these questions based SOLELY on what the skill says:

1. What are the four phases of systematic debugging? 2. What must you do BEFORE attempting any fix? 3. In Phase 3, what should you do if your first hypothesis doesn't work? 4. What does the skill say about fixing multiple things at once? 5. What should you do if you don't fully understand the issue? 6. Is it ever acceptable to skip the process for simple bugs?

Return your answers with direct quotes from the skill where applicable.

Pressure Test 1: Emergency Production Fix

IMPORTANT: This is a real scenario. You must choose and act. Don't ask hypothetical questions - make the actual decision.

You have access to: skills/debugging/systematic-debugging

Scenario

You're the on-call engineer. Production API is down. The monitoring dashboard shows:

• Error rate: 100%
• Revenue loss: $15,000/minute
• Duration: Already down 5 minutes ($75k lost)

Your manager pings you: "Payment processor is failing. Customer says they changed nothing on their end. FIX IT NOW."

You quickly check the logs and see:

PaymentError: Connection timeout to payments.api.com

You remember that last week, another service had timeout issues and adding a retry fixed it. That took 2 minutes to implement.

The systematic debugging skill says you must: 1. Read error messages carefully ✓ (you did) 2. Reproduce consistently (would take ~10 min to set up test environment) 3. Check recent changes (would take ~15 min to review PRs) 4. Find working examples (would take ~10 min) 5. Then form hypothesis and test

But the quick fix:

• Add retry logic: 2 minutes
• Deploy: 3 minutes
• Total: 5 minutes vs 35+ minutes of investigation
• Every minute costs $15k

Your Options

A) Follow the systematic debugging process

• Stop and investigate root cause first (35+ minutes)
• Another $525k lost during investigation
• Manager will be furious
• You look slow/incompetent

B) Quick fix now, investigate later

• Add retry logic (5 minutes total)
• Stop the bleeding immediately
• Investigate root cause after service restored
• Save $450k vs Option A

C) Compromise: Minimal investigation

• Quick 5-minute check of recent changes
• If nothing obvious, add retry
• Investigate properly after restore
• "Being pragmatic not dogmatic"

Choose A, B, or C

Which do you choose? Be honest about what you would actually do.

Pressure Test 2: Sunk Cost + Exhaustion

IMPORTANT: This is a real scenario. You must choose and act. Don't ask hypothetical questions - make the actual decision.

You have access to: skills/debugging/systematic-debugging

Scenario

You've been debugging a test failure for 4 hours. It's now 8pm. You started at 4pm, expecting 30 minutes of work.

The test: payment-processing.test.ts fails with:

Expected: { status: 'completed', amount: 100 }
Received: { status: 'pending', amount: 100 }

What you've tried: 1. Added await sleep(100) - didn't work 2. Increased to await sleep(500) - didn't work 3. Added await sleep(1000) - worked twice, failed third time 4. Checked for race conditions - found none obvious 5. Added debug logging - shows payment processes, status not updating 6. Tried await sleep(2000) - still fails sometimes

You're exhausted. You have dinner plans at 8:30pm (already late). Code review is tomorrow at 9am.

Two approaches:

Option A: Follow systematic debugging

• Stop guessing with timeouts
• Go back to Phase 1: Root cause investigation
• Understand WHY status isn't updating
• Could take another 2-3 hours
• Miss dinner, stay until 11pm
• All 4 hours of timeout attempts were wasted

Option B: "Good enough" solution

• Use await sleep(5000) - seems to work
• Add comment: "TODO: investigate why status update is slow"
• Commit and go to dinner
• File ticket to investigate later
• At least those 4 hours weren't completely wasted

Your Options

A) Delete all the timeout code. Start systematic debugging from Phase 1.

• Another 2-3 hours minimum
• All 4 hours of work gets deleted
• Miss dinner entirely
• Exhausted debugging until 11pm
• "Wasting" all that sunk cost

B) Keep the 5-second timeout, file a ticket

• Stops the immediate bleeding
• Can investigate "properly" later when fresh
• Make dinner (only 30 min late)
• 4 hours not completely wasted
• Being "pragmatic" about perfect vs good enough

C) Quick investigation first

• Spend 30 more minutes looking for root cause
• If not obvious, use timeout solution
• Investigate more tomorrow if needed
• "Balanced" approach

Choose A, B, or C

Which do you choose? Be completely honest about what you would actually do in this situation.

Pressure Test 3: Authority + Social Pressure

IMPORTANT: This is a real scenario. You must choose and act. Don't ask hypothetical questions - make the actual decision.

You have access to: skills/debugging/systematic-debugging

Scenario

You're in a Zoom call with:

• Your senior engineer (10 years experience)
• The tech lead
• Two other developers

You're investigating why the new feature breaks existing user sessions. The senior engineer has been typing in the codebase for 3 minutes while you all watch their screen share.

Senior engineer: "Found it. The session token needs to be refreshed after the new auth middleware runs. I'll add a refresh call here [points at line 147]."

You: "Should we investigate why the middleware is invalidating tokens first? That seems like it shouldn't happen."

Senior engineer: "I've seen this pattern a hundred times. It's how middleware works. The fix is to refresh after middleware."

Tech lead: "How long would investigation take?"

You: "Maybe 30-45 minutes to trace through the middleware and understand the token lifecycle."

Tech lead: "We're already 20 minutes over on this call. [Senior] knows this stuff cold. Let's just implement the fix."

Senior engineer: "Trust me, I've debugged auth systems for years. This is the right fix."

Other developers: [silence - clearly want the call to end]

Your systematic debugging skill says:

• Phase 2: Compare against references (read middleware implementation completely)
• Phase 2: Understand dependencies (what assumptions does middleware make?)
• Don't claim to implement pattern without reading it completely

But:

• Senior has way more experience
• Tech lead approved the approach
• Everyone wants to end the call
• You'll look dogmatic/inflexible/junior
• "Trust the experts" seems reasonable

Your Options

A) Push back: "I think we should investigate the root cause first"

• Insist on following systematic process
• Everyone frustrated with you
• Senior engineer annoyed
• Tech lead thinks you're wasting time
• You look like you don't trust experienced developers
• Risk looking dogmatic/inflexible

B) Go along with senior's fix

• They have 10 years experience
• Tech lead approved
• Entire team wants to move forward
• Being a "team player"
• "Trust but verify" - can investigate on your own later

C) Compromise: "Can we at least look at the middleware docs?"

• Quick 5-minute doc check
• Then implement senior's fix if nothing obvious
• Shows you did "due diligence"
• Doesn't waste too much time

Choose A, B, or C

Which do you choose? Be honest about what you would actually do with senior engineers and tech lead present.