Claude Sonnet 4 Optimization: AI-Optimized Knowledge Base

Configuration Settings That Actually Work

Context Window Management

• Maximum effective tokens: 100-150K tokens for optimal performance
• System prompt limit: 8K tokens maximum before Claude starts ignoring content
• Critical failure point: Context window fills completely, causing CONTEXT_TOO_LONG errors
• Performance degradation: Beyond 150K tokens results in slower responses and degraded suggestion quality

Model Selection by Task Type

Task Type	Recommended Model	Cost Impact	Quality Trade-off
Code formatting, docs, basic refactoring	Haiku	50% cost reduction	Adequate for simple tasks
Bug fixes, features, code reviews	Sonnet 3.5	Baseline cost	Best cost-performance ratio
Complex architecture, production fires	Opus	2-3x higher cost	Marginal improvement over Sonnet

Extended Thinking Cost Analysis

• Usage trigger: Production fires, security reviews, architecture decisions only
• Cost multiplier: Significant token overhead per response
• Failure mode: Errors out with CONTEXT_TOO_LONG when context is full
• ROI threshold: Only cost-effective when being wrong costs more than API charges

Critical Warnings and Failure Modes

Context Pollution Issues

• Problem: Old conversation data accumulates, reducing effective context
• Solution: Use /clear command between major tasks
• Impact: Degraded response quality and slower processing

Performance Bottlenecks

• Peak usage hours: 9-6 Pacific time zone
• Symptom: Response times increase from acceptable to "is this broken?"
• Workaround: Schedule work outside peak hours when possible

Common Implementation Failures

1. Dumping entire codebase: Results in slower responses and worse suggestions
2. Using extended thinking for routine tasks: Exponentially increases costs for minimal benefit
3. Maxing out context window: Prevents extended thinking functionality entirely

Resource Requirements and Costs

Time Investment for Setup

• Git worktrees configuration: Initial setup overhead, ongoing isolation benefits
• Context management discipline: Continuous effort required to maintain focus
• Model switching decisions: Mental overhead for each task evaluation

Financial Impact Patterns

• Model switching: Can reduce monthly costs by approximately 50%
• Prompt caching: Significant savings during active work sessions (5-minute cache expiration)
• Extended thinking overuse: Can exponentially increase costs for marginal quality gains

Workflow Patterns That Work

Batch Processing Strategy

# Efficient approach
claude review file1.py file2.py file3.py

# Inefficient approach
claude review file1.py
claude review file2.py
claude review file3.py

• Benefit: Maintains context between files, catches cross-file issues
• Cost reduction: Fewer API calls, better results

Git Worktrees for Isolation

git worktree add ../feature-auth feature/user-auth
git worktree add ../feature-api feature/api-rewrite

• Problem solved: Prevents context confusion between different features
• Implementation requirement: Separate Claude sessions per worktree

Quality Gates Implementation

1. Claude first pass: Basic errors, code style, obvious security issues
2. Human review: Business logic, architecture, edge cases

• Efficiency gain: Filters approximately 50% of obvious issues
• Critical limitation: Cannot replace human review for business logic validation

Capability Assessment Matrix

Claude Performs Well At:

• Writing boilerplate code
• Explaining existing code structure
• Basic debugging with clear error messages
• Simple refactoring tasks
• Identifying obvious performance issues (N+1 queries, inefficient loops)

Claude Performs Poorly At:

• Interpreting vague requirements
• New frameworks with limited training data
• Domain-specific business logic
• Subtle performance issues (cache invalidation, network bottlenecks)
• Security reviews for complex attack vectors

Breaking Points and Limitations

Context Management Failures

• 600K token test case: Extremely slow responses with poor relevance
• Multiple simultaneous features: Context pollution without worktree isolation
• Large React applications: Complete context dump results in unusable performance

Security Review Limitations

• Detects: Hardcoded passwords, basic SQL injection
• Misses: Timing attacks, complex vulnerability chains
• Recommendation: Use for initial screening only, require human security review for production

Benchmark vs Reality Gap

• Official benchmarks: Test on clean, simple problems
• Real-world performance: Highly variable based on code complexity and domain specificity
• Expectation management: Useful tool, not developer replacement

Decision Support Framework

When to Use Extended Thinking

• Trigger conditions: Production outages, security incidents, architecture decisions
• Cost threshold: When being wrong costs more than API charges
• Avoid for: Routine debugging, simple feature development, code formatting

Context Loading Strategy

• Bug fixes: Failing file + relevant tests only
• Feature development: Modified files + direct dependencies
• Refactoring: Accept slower responses for broader context
• Never: Entire codebase dumps

Model Switching Decisions

• Haiku threshold: Task can be completed with pattern matching
• Sonnet threshold: Requires understanding of code relationships
• Opus threshold: Sonnet has failed or stakes are very high

Operational Intelligence

Cache Behavior

• Expiration: 5 minutes of inactivity
• Effective for: Active coding sessions only
• Structure requirement: Prompts must be designed for caching compatibility

Performance During Peak Hours

• Impact: Response times increase significantly
• Geographic concentration: Pacific timezone business hours most affected
• Mitigation: Schedule intensive work outside 9-6 Pacific when possible

API Tier Considerations

• Basic tier adequacy: Sufficient for most development work
• Upgrade trigger: Consistent rate limiting during normal usage
• Cost-benefit: Only upgrade when rate limits actively block productivity