Deep Reasoning for Features

Building software isn’t just about writing code - it’s about making hundreds of interconnected decisions that shape your system for years to come. Claude Code’s deep reasoning capabilities transform feature planning from guesswork into systematic exploration of possibilities, trade-offs, and optimal solutions.

The Power of Deep Thinking

Scenario: Your CEO just announced a major pivot. The e-commerce platform needs to support B2B wholesale ordering with complex pricing tiers, approval workflows, bulk discounts, and integration with enterprise ERPs. You have 6 weeks. Traditional approach? Panic, then guess. With Claude Code? Let’s unlock its full reasoning potential.

Thinking Modes Explained

> Add user authentication to our app

Claude: I'll add a basic auth system...
[Quick implementation without deep analysis]

> Think about how to add user authentication to our app

Claude: Let me analyze the requirements and options...
[~5,000 tokens of reasoning]
- Evaluates different auth strategies
- Considers security implications
- Weighs framework options
- Plans implementation approach

> Think harder about our authentication architecture

Claude: I'll deeply explore all architectural possibilities...
[~10,000 tokens of reasoning]
- Comprehensive analysis of auth patterns
- Detailed security threat modeling
- Performance impact analysis
- Migration strategy from current system

> Ultrathink about designing our enterprise auth system

Claude: Engaging maximum reasoning capacity...
[~128,000 tokens of deep analysis]
- Exhaustive exploration of all options
- Detailed trade-off analysis
- Edge case identification
- Long-term scalability planning
- Compliance considerations

The PRD → Plan → Todo Workflow

Phase 1: From PRD to Understanding

Transform business requirements into technical clarity:

Load the PRD

> Read the PRD for our B2B wholesale feature in docs/b2b-wholesale-prd.md
> Summarize the key requirements and identify any ambiguities

Clarify Requirements

> Think about potential edge cases in the B2B wholesale requirements.
> What questions should we ask the product team?

Technical Exploration

> Think harder about the technical implications of these requirements.
> What are the main architectural challenges we'll face?

Create Technical Specification

> Based on the PRD, create a technical specification that addresses:
> - Data model changes
> - API design
> - Integration points
> - Performance requirements
> - Security considerations

Phase 2: Deep Planning

Architecture Planning

> Ultrathink about the architecture for B2B wholesale.
> Consider:
> - Current system constraints
> - Scalability requirements
> - Integration complexity
> - Team capabilities
> - Timeline constraints
>
> Propose 3 different architectural approaches with
> detailed trade-offs for each

Risk Analysis

> Think hard about risks in implementing B2B wholesale.
> Categorize by:
> - Technical risks
> - Business risks
> - Timeline risks
> - Integration risks
>
> Provide mitigation strategies for each

Dependency Mapping

> Analyze dependencies for the B2B feature.
> Map out:
> - Code dependencies
> - Service dependencies
> - Data dependencies
> - External system dependencies
>
> Identify potential bottlenecks

Implementation Strategy

> Think about the best implementation approach.
> Should we:
> - Build alongside existing system?
> - Create separate B2B service?
> - Refactor current system?
>
> Consider rollback strategies

Phase 3: Convert to Actionable Todos

Transform the plan into executable tasks:

> Based on our B2B wholesale plan, create a detailed todo list.
> For each task:
> - Estimate complexity (S/M/L/XL)
> - Identify dependencies
> - Note which team member would be best suited
> - Flag any blockers
>
> Organize by implementation phases

Claude generates structured todos:

# B2B Wholesale Implementation Todos

## Phase 1: Foundation (Week 1-2)

### Database Schema Updates
- [ ] Design wholesale_accounts table (M)
  - Dependencies: None
  - Assignee: Backend team
  - Notes: Includes approval hierarchy

- [ ] Create price_tiers table (M)
  - Dependencies: wholesale_accounts
  - Assignee: Backend team
  - Notes: Support volume-based pricing

- [ ] Add bulk_orders table (L)
  - Dependencies: price_tiers
  - Assignee: Backend team
  - Notes: Complex state machine for approvals

### API Development
- [ ] Create wholesale account CRUD endpoints (M)
  - Dependencies: Database schema
  - Assignee: API team
  - Details: POST /api/wholesale/accounts, etc.

- [ ] Implement pricing calculation service (XL)
  - Dependencies: price_tiers table
  - Assignee: Senior backend dev
  - Blocker: Need pricing rules from business

## Phase 2: Core Features (Week 3-4)

### Approval Workflow
- [ ] Design approval state machine (L)
  - Dependencies: bulk_orders table
  - Assignee: Architecture team
  - Notes: Consider using temporal.io

- [ ] Implement approval API endpoints (L)
  - Dependencies: State machine design
  - Assignee: Backend team

### Integration Layer
- [ ] Create ERP integration interface (XL)
  - Dependencies: None
  - Assignee: Integration team
  - Blocker: Waiting for ERP API docs

## Phase 3: UI/UX (Week 5-6)
[... continues with detailed tasks ...]

Real-World Feature Planning Examples

Example 1: Payment System Redesign

Challenge: Migrate from Stripe to a multi-provider payment system supporting 15 countries.

> Ultrathink about migrating our payment system from Stripe-only
> to supporting multiple providers (Stripe, PayPal, Adyen, local providers).
> Current system processes $10M/month. Zero downtime allowed.
> Consider:
> - Data migration strategy
> - Provider abstraction design
> - Rollback capabilities
> - A/B testing approach
> - Compliance requirements per country

Claude’s deep reasoning produces:

graph TB A[Payment Request] --> B[Payment Router] B --> C{Provider Selection} C -->|Strategy Pattern| D[Stripe Adapter] C -->|Strategy Pattern| E[PayPal Adapter] C -->|Strategy Pattern| F[Adyen Adapter] C -->|Strategy Pattern| G[Local Adapters] D --> H[Provider API] E --> I[Provider API] F --> J[Provider API] G --> K[Provider APIs] H --> L[Response Normalizer] I --> L J --> L K --> L L --> M[Payment Result] N[Circuit Breaker] -.->|Monitors| C O[Fallback Provider] -.->|Backup| C

Feature Flags per Provider

if (featureFlag.isEnabled('paypal_usa')) {
  providers.register('US', PayPalProvider);
}

Automatic Rollback Triggers
- Error rate > 1%
- Response time > 2s
- Success rate < 98%
Data Consistency Checks
- Dual-write to old and new systems
- Async reconciliation job
- Alert on mismatches
Provider Health Monitoring
- Real-time dashboard
- Automatic failover
- SLA tracking per provider

Example 2: Real-time Collaboration Feature

Challenge: Add Google Docs-style real-time collaboration to your project management tool.

> Think harder about implementing real-time collaboration.
> Current architecture: Traditional REST API with PostgreSQL.
> Requirements:
> - Support 50 concurrent users per document
> - Show user cursors and selections
> - Conflict-free editing
> - Work offline with sync
> - Scale to 10k documents

Claude’s analysis produces a comprehensive plan:

Technology Selection After analyzing options (WebSockets, WebRTC, SSE, polling), recommends:
- Yjs for CRDT implementation
- WebSocket with Socket.io for transport
- Redis for presence and ephemeral data
- PostgreSQL for persistence

Architecture Design

Client (Yjs) ↔ WebSocket ↔ Collaboration Service
                                   ↓
                           Redis (Presence)
                                   ↓
                           PostgreSQL (Persistence)

Implementation Phases
- Phase 1: Basic real-time sync (2 weeks)
- Phase 2: Presence (cursors, selections) (1 week)
- Phase 3: Offline support (2 weeks)
- Phase 4: Performance optimization (1 week)
Critical Decisions
- Use Yjs for automatic conflict resolution
- Implement operation batching for performance
- Add snapshot system for large documents
- Use connection pooling for WebSocket scaling

## Architectural Decision Records

Claude Code can help create ADRs during planning:

Create an Architecture Decision Record for choosing between microservices vs modular monolith for our B2B wholesale feature. Use the Y-statement format.

Result:

```markdown
# ADR-001: B2B Wholesale Architecture Pattern

## Status
Proposed

## Context
We need to add B2B wholesale capabilities to our e-commerce platform. This includes complex pricing, approval workflows, and ERP integrations. Team has 5 developers, 6-week deadline.

## Decision
In the context of **adding B2B wholesale to our e-commerce platform**,
facing **complexity of requirements and tight timeline**,
we decided for **modular monolith approach**,
and against **microservices architecture**,
to achieve **faster initial delivery and simpler deployment**,
accepting **potential future refactoring costs**.

## Consequences

### Positive
- Single deployment unit (reduces DevOps complexity)
- Shared database transactions (data consistency)
- Easier local development
- Faster initial development
- Lower operational overhead

### Negative
- Harder to scale individual components
- Risk of coupling between modules
- Single point of failure
- Potential performance bottlenecks

### Mitigation
- Strict module boundaries using separate packages
- Clear interfaces between modules
- Database schema separation
- Plan extraction points for future services

Using Subagents for Complex Analysis

For extremely complex features, leverage subagents:

> Use subagents to analyze different aspects of our B2B feature:
> 1. Security implications and required controls
> 2. Performance impact on existing system
> 3. Data migration requirements
> 4. Integration complexity with top 3 ERPs
>
> Synthesize findings into a risk matrix

Claude orchestrates multiple specialized agents:

Planning Anti-Patterns to Avoid

1. The Big Bang Rewrite

❌ "Rewrite the entire payment system at once"
✅ "Create adapter layer, migrate incrementally"

2. Perfect Planning Paralysis

❌ "Ultrathink about every possible edge case"
✅ "Think hard about core architecture, iterate on details"

3. Ignoring Team Reality

❌ "Use cutting-edge tech stack we've never used"
✅ "Leverage familiar tools, introduce new ones gradually"

4. Skipping Risk Analysis

❌ "This plan looks good, let's start coding"
✅ "What could go wrong? How do we mitigate?"

Interactive Planning Sessions

Make planning collaborative:

Initial Brain Dump

> What are all the things we need to consider for B2B wholesale?
> Don't organize yet, just list everything

Categorize and Prioritize

> Organize these considerations into:
> - Must have for MVP
> - Should have
> - Nice to have
> - Future considerations

Spike Uncertain Areas

> We're unsure about ERP integration complexity.
> Create a technical spike plan to investigate

Review and Refine

> Review our plan. What have we missed?
> What assumptions are we making?

## Translating Plans to Code

Once planning is complete, seamlessly transition to implementation:

We’ve decided on the modular monolith approach. Create the initial module structure for B2B wholesale:

Core domain models

API module structure

Database migrations

Interface definitions between modules

Claude generates the foundational code structure based on the plan, ensuring alignment between architecture decisions and implementation.

## Best Practices for Feature Planning

### 1. Start with Why

Always understand the business reason:

Before we plan the technical solution, help me understand why B2B wholesale is important for our business. What problems does it solve for our customers?

### 2. Consider the Whole System

How will B2B wholesale impact:

Current B2C customers

System performance

Support team workload

Future feature development

### 3. Plan for Observability

What metrics and monitoring do we need for B2B wholesale? Design the observability strategy alongside the feature

### 4. Document Decision Rationale

For each major decision in our plan, document:

What we decided

Why we decided it

What alternatives we considered

What would make us reconsider

## Related Lessons

<LinkCard
  title="From Plan to Implementation"
  description="Turn your carefully crafted plans into working code"
  href="/en/claude-code/lessons/implementation"
/>

<LinkCard
  title="Architecture Patterns"
  description="Deep dive into system design with Claude Code"
  href="/en/claude-code/lessons/architecture"
/>

<LinkCard
  title="Project Initialization"
  description="Set up new projects aligned with your architectural decisions"
  href="/en/claude-code/lessons/project-setup"
/>

## Next Steps

You've learned how to harness Claude Code's deep reasoning capabilities for feature planning. This transforms you from a coder into an architect, from a task executor into a strategic thinker.

Remember: The best code is the code you don't have to write because you planned a simpler solution. The fastest feature is the one where you avoided the pitfalls through careful analysis. Let Claude Code's thinking capabilities amplify your own, turning complex requirements into clear, actionable plans that lead to successful implementations.