How to Use Claude Code and Codex Together in Your Development Workflow

Apr 2, 2026

Problem

I spent three hours designing an authentication system with Claude Code. The plan looked solid—JWT tokens, refresh logic, password hashing. I implemented it, tested it, deployed it. Then I ran Codex CLI for a routine review.

Codex found seven security issues I had completely missed:

A timing attack in the password comparison
Missing rate limiting on the login endpoint
JWT secret stored in a config file instead of environment variable
No token expiration validation
SQL injection vector in the user search
CSRF vulnerability in the password reset flow
Missing input validation on email format

Claude Code designed a working system. Codex found the holes in it.

This made me realize: one AI agent isn’t enough for professional development. Each model has blind spots. Running them together in a pipeline catches what either one misses alone.

Why Single-Agent Development Fails

Using one AI coding assistant creates several problems:

Same-model bias: The AI makes assumptions based on its training. When you ask it to review its own work, it tends to agree with its previous decisions—even when they’re wrong.

No cross-validation: Without a second opinion, there’s no check on architectural choices, security decisions, or code quality.

Perspective blind spots: Every model has reasoning patterns it favors. A model that’s great at generating code might be weaker at security analysis.

Self-correction difficulty: AI models struggle to catch their own mistakes. The reasoning that produced an error often fails to identify it.

I needed a workflow that uses different AI agents for their strengths.

The Complementary Approach

After experimenting with both Claude Code and OpenAI’s Codex CLI, I found they have complementary strengths:

+------------------------+-------------------------+---------------------------+
| Aspect                 | Claude Code             | Codex CLI                 |
+------------------------+-------------------------+---------------------------+
| Ideation               | Excellent               | Good                      |
| Planning               | Excellent               | Good                      |
| Context Understanding  | Excellent (MCP servers) | Good                      |
| Code Generation        | Very Good               | Excellent                 |
| Complex Implementation | Good                    | Excellent                 |
| Code Review            | Good                    | Excellent                 |
| Security Analysis      | Good                    | Excellent                 |
| Non-interactive Mode    | Limited                 | Excellent (--full-auto)  |
| CI/CD Integration      | Manual                  | Excellent                 |
+------------------------+-------------------------+---------------------------+

The key insight from a Reddit discussion: “I use Claude Code for ideating and ‘big ideas’ and small implementation, and then I tell it to run Codex to do complex implementations and code reviews.”

Another developer noted: “I’ve been using Codex to supervise Claude’s work and it’s impressive how many flaws it finds in Claude’s plans.”

They’re not competing tools. They’re complementary tools.

The Pipeline Workflow

I now use a stage-by-stage pipeline where each stage produces an artifact that the next stage consumes:

Feature Request
      │
      ▼
┌─────────────────────────────────────────────────────────────────────────┐
│  STAGE 1: Planning (Claude Code)                                        │
│  ────────────────────────────────────                                   │
│  Input: Feature requirements                                            │
│  Output: Implementation plan (markdown artifact)                        │
│  Why Claude: Strong at understanding context via MCP, brainstorming    │
└─────────────────────────────────────────────────────────────────────────┘
      │
      ▼ Plan Artifact
      │
┌─────────────────────────────────────────────────────────────────────────┐
│  STAGE 2: Design (Claude Code)                                          │
│  ────────────────────────────────────                                   │
│  Input: Implementation plan                                             │
│  Output: Architecture decision (design.md)                              │
│  Why Claude: Good at weighing tradeoffs, explaining decisions          │
└─────────────────────────────────────────────────────────────────────────┘
      │
      ▼ Design Artifact
      │
┌─────────────────────────────────────────────────────────────────────────┐
│  STAGE 3: Initial Code (Claude Code)                                    │
│  ────────────────────────────────────                                   │
│  Input: Design document                                                 │
│  Output: Draft implementation                                           │
│  Why Claude: Interactive, good for incremental changes                  │
└─────────────────────────────────────────────────────────────────────────┘
      │
      ▼ Draft Code
      │
┌─────────────────────────────────────────────────────────────────────────┐
│  STAGE 4: Complex Implementation (Codex CLI)                            │
│  ────────────────────────────────────                                   │
│  Input: Draft code + remaining tasks                                    │
│  Output: Complete implementation                                        │
│  Why Codex: Runs tests until pass, handles multi-file changes           │
└─────────────────────────────────────────────────────────────────────────┘
      │
      ▼ Complete Code
      │
┌─────────────────────────────────────────────────────────────────────────┐
│  STAGE 5: Code Review (Codex CLI)                                       │
│  ────────────────────────────────────                                   │
│  Input: Complete implementation                                         │
│  Output: Review report (issues.md)                                      │
│  Why Codex: Rigorous, catches edge cases, security focused             │
└─────────────────────────────────────────────────────────────────────────┘
      │
      ▼ Review Report
      │
┌─────────────────────────────────────────────────────────────────────────┐
│  Issues Found? ───Yes───► Fix with Claude Code ───► Back to Stage 5     │
│        │                                                                │
│        No                                                               │
│        ▼                                                                │
└─────────────────────────────────────────────────────────────────────────┘
      │
      ▼
┌─────────────────────────────────────────────────────────────────────────┐
│  STAGE 6: Parallel Testing (Both Agents)                                │
│  ────────────────────────────────────                                   │
│  Claude: Security analysis via MCP threat database                      │
│  Codex: Static analysis and pattern checking                           │
│  Compare results for cross-validation                                   │
└─────────────────────────────────────────────────────────────────────────┘
      │
      ▼
   Commit & Push

Practical Commands

Stage 1 & 2: Planning and Design with Claude Code

Claude Code excels at interactive brainstorming. I start with conversation:

# Start interactive Claude Code session
claude

# In the session:
> "Help me design an authentication system for this Flask app"
> "What are the security considerations?"
> "Generate a step-by-step implementation plan"
> "Save the plan to docs/auth-plan.md"
> "What are the tradeoffs between JWT and session-based auth?"
> "Save the design decision to docs/auth-design.md"

Claude Code’s strengths here:

Natural conversation flow
Can query MCP servers for documentation context
Good at explaining reasoning
Produces well-structured markdown artifacts

Stage 3: Initial Implementation with Claude Code

For small, focused implementations, Claude Code is ideal:

# Continue in Claude Code session
> "Implement the login endpoint following docs/auth-plan.md"
> "Write the password hashing utility"
> "Add input validation for the registration form"
> "Run the tests for the auth module"

Good for:

Incremental changes
Learning/prototyping
When you want to understand each step

Stage 4: Complex Implementation with Codex CLI

When I need complex, multi-file changes or automated test-running, I switch to Codex:

# Non-interactive execution with full automation
codex exec "implement the JWT token refresh logic with proper error handling based on docs/auth-plan.md" --full-auto

# With specific model
codex exec "implement Redis caching for session management" -m claude-sonnet-4-5-20250929 --full-auto

# Target specific directory
codex exec "add password reset flow with email verification" -C ./src/auth --full-auto

Codex strengths:

Runs tests until they pass
Handles complex multi-file changes systematically
Non-interactive mode enables automation
Can be integrated into CI/CD pipelines

Stage 5: Code Review with Codex CLI

This is where Codex shines. I always run Codex review after Claude implementation:

# Review specific module for security issues
codex exec "review src/auth/ for security vulnerabilities and logic errors" -C ./src/auth

# Full security audit
codex exec "audit authentication code for OWASP top 10 vulnerabilities" -s read-only

# Performance review
codex exec "analyze the codebase for performance bottlenecks and memory leaks"

# Architecture review
codex exec "review the overall architecture and suggest improvements for maintainability"

The -s read-only flag is useful for audits where you don’t want any modifications.

Stage 6: Parallel Analysis with Both Agents

For critical features, I run both agents in parallel for independent verification:

Terminal 1 (Claude Code):
─────────────────────────────────────────────────────────────────────────
$ claude
> "Analyze the security implications of this authentication flow"
> "Check against OWASP guidelines via MCP security database"
> "What are the potential attack vectors?"

Terminal 2 (Codex CLI):
─────────────────────────────────────────────────────────────────────────
$ codex exec "static analysis of auth module for common vulnerabilities" --full-auto
$ codex exec "check for timing attacks in password comparison" --full-auto

Then I compare results. The intersection of their findings represents high-confidence issues. The union represents all potential issues.

What Codex Catches That Claude Misses

In my authentication system example, Codex identified issues Claude had overlooked:

Timing Attack in Password Comparison:

# Claude wrote this - looks correct but vulnerable
def verify_password(input_password, stored_hash):
    return bcrypt.checkpw(input_password.encode(), stored_hash.encode())

Codex pointed out that even with bcrypt, the comparison should use constant-time functions at the application level for sensitive operations.

Missing Rate Limiting:

# Claude's implementation
@app.route('/login', methods=['POST'])
def login():
    email = request.form['email']
    password = request.form['password']
    # No rate limiting here!
    user = authenticate_user(email, password)

Codex flagged this immediately: “Add rate limiting to prevent brute force attacks.”

JWT Secret Storage:

# Claude put this in config.py
JWT_SECRET = "your-secret-key-here"

Codex: “Move JWT_SECRET to environment variable. Never commit secrets to version control.”

Each finding was something Claude “knew” but didn’t apply. A second perspective caught the gaps.

Workflow Integration Tips

Save Artifacts Between Stages

I always save intermediate artifacts:

docs/
├── auth-plan.md        # Stage 1 output
├── auth-design.md      # Stage 2 output
├── auth-review.md      # Stage 5 output
└── auth-security.md    # Stage 6 output

This creates a chain of documentation and lets each stage build on the previous.

Use Codex’s Sandbox Modes

Codex CLI has different sandbox modes:

# Read-only: Can only read files, no modifications
codex exec "audit this codebase" -s read-only

# Workspace-write: Can modify files in current directory
codex exec "implement feature X" -s workspace-write

# Danger-full-access: Can access anything (use carefully)
codex exec "run system updates" --danger-full-access

For reviews, I always use -s read-only. For implementation, -s workspace-write.

Leverage MCP Servers in Claude Code

Claude Code can query MCP servers for documentation context. This is valuable during planning:

> "Use the context7 MCP to fetch the latest Flask security documentation"
> "Query the web-search MCP for best practices on JWT implementation"

This gives Claude access to up-to-date documentation, which improves the quality of plans and designs.

Common Mistakes to Avoid

Mistake	Why It Fails	Better Approach
Using Claude to review Claude’s work	Same-model bias	Always use Codex for review
Skipping the plan stage	Assumes you know the solution	Plan first, implement second
Not saving artifacts	Context gets lost	Document each stage
Running Codex only at the end	Issues compound	Review after each major component
Asking Codex to ideate	Not its strength	Use Claude for ideation, Codex for execution
Not using Codex’s `--full-auto`	Manual intervention needed	Automate with full-auto mode

Cost and Complexity Trade-offs

Running two AI agents isn’t free:

Cost: You pay for both Claude and Codex API usage. A typical feature costs roughly 2x what it would with a single agent.

Complexity: You manage two tools with different interfaces. Claude Code is interactive; Codex CLI is command-based.

Coordination: Currently, there’s no automatic handoff between agents. You manually pass artifacts between stages.

But the quality improvement is significant. I estimate I catch 30-50% more issues with the dual-agent pipeline than with either agent alone. The time saved on debugging and security fixes easily justifies the extra cost.

When to Use Each Agent

Use Claude Code when:
─────────────────────────────────────────────────────────────────────────
✓ Starting a new feature (planning phase)
✓ Brainstorming architecture decisions
✓ Learning a new codebase
✓ Need explanation and reasoning
✓ Making incremental changes
✓ Want interactive back-and-forth

Use Codex CLI when:
─────────────────────────────────────────────────────────────────────────
✓ Implementing complex features
✓ Running tests until they pass
✓ Code review and security audit
✓ Need non-interactive automation
✓ CI/CD integration
✓ Cross-validation of Claude's work

Use Both in Parallel when:
─────────────────────────────────────────────────────────────────────────
✓ Security-critical features
✓ Final review before deployment
✓ Complex debugging (different perspectives)
✓ Architecture validation

Real Results

After adopting this workflow for three months:

Bugs caught before deployment: Up 47% (measured by comparing pre-deployment vs post-deployment bug reports)
Security issues found in review: 23 issues that would have reached production
Time to implement: Slightly longer (due to two-pass workflow)
Time debugging: Down significantly (issues caught earlier)
Overall velocity: Net positive (less rework)

The key insight: spending more time upfront on planning and review saves more time later on debugging and fixing.

Quick Start Guide

If you want to try this workflow:

Install both tools:

# Claude Code
npm install -g @anthropic-ai/claude-code

# Codex CLI
pip install openai-codex

Start with Claude Code for planning:

claude
> "Help me design [your feature]"
> "Save the plan to plan.md"

Implement with Claude or Codex:

# Small implementation: stay in Claude
> "Implement [component A]"

# Complex implementation: switch to Codex
codex exec "implement [component B] based on plan.md" --full-auto

Always review with Codex:

codex exec "review this implementation for security and correctness" -s read-only

Fix issues with Claude:

claude
> "Fix the issues found in the review: [paste issues]"

Repeat until clean review.

The pipeline approach transforms AI coding from a single-shot gamble into a reliable, quality-controlled process.

Final Words + More Resources

My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me

Here are also the most important links from this article along with some further resources that will help you in this scope:

👨‍💻 Reddit: Claude Code and Codex feel so different
👨‍💻 OpenAI Codex CLI Documentation
👨‍💻 Claude Code Documentation

Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!