New Pair Programming and AI Co-Pilots

Planet Fitness has a Black Card membership with a simple but powerful feature: bring a friend. Two people can enter the gym, train together, support each other, and build consistency through shared effort. The more I thought about this, the more I realized how deeply this model resembles something in software engineering: pair programming, and more broadly, the way we should approach development with AI co-pilots and human partners today.

This gym feature is not just a fitness perk. It reflects a philosophy that modern engineering needs.

1. Bring a Friend: The Spirit of Pair Programming

Traditional pair programming teaches one simple truth: one person alone, no matter how experienced, cannot guarantee a perfect outcome.

A second pair of eyes catches:

• Subtle logic gaps
• Dangerous assumptions
• Hidden bugs
• Architectural inconsistencies

This is exactly like two friends working out together. One pushes the other. One sees what the other cannot. They go further together.

Pair programming is not just about two people typing on one keyboard. It is about support across an entire workflow: design, implementation, testing, debugging, refactoring, and maintenance. Just like building a long-term fitness habit, software quality is built slowly, consistently, and socially.

2. The New Reality: AI Co-Pilots as the Friend

Today, AI tools like ChatGPT, GitHub Copilot, and other LLM-based assistants play the role of a new kind of pair programmer. They help with:

• Brainstorming designs
• Spotting mistakes
• Translating patterns
• Explaining complex code
• Generating test cases
• Speeding up refactoring

In the comfortable zone of engineering tasks, coding, designing, writing tests, the AI co-pilot is a reliable gym buddy. It amplifies productivity, creativity, and confidence. This is the modern equivalent of Planet Fitness saying:

"Don't train alone. Bring someone with you."

For developers, that someone is increasingly AI.

But this is where the story changes.

3. Not All Workouts Are the Same: Critical vs Non-Critical Tasks

Planet Fitness lets you bring a friend, but there are rules: your friend cannot access the tanning beds, red-light therapy, or certain high-risk equipment. Why? Because some things require supervision, expertise, and trained staff.

Software engineering is the same.

Non-critical work where AI is safe and helpful:

• Writing code
• Unit tests
• Refactoring
• Debugging suggestions
• Design exploration
• Documentation
• Data parsing
• Prototyping

Critical work where AI should not act alone:

• Database migrations
• Data deletion or modification
• Security configurations
• IAM and permission changes
• AWS deployments
• Infrastructure operations
• Cost-impacting changes
• Production environment actions

These are like the gym's dangerous equipment. If something goes wrong, the consequence is not a small bug. It can be catastrophic, damaging real users, real systems, and real data.

In these zones, we need:

• Experienced DevOps engineers
• Senior developers
• Human reviewers
• Peer approvals
• Two-person rules

AI is helpful for drafting or analyzing, but a real human must finalize and execute. This is not about distrust in AI. It is about understanding risk.

4. A Better Model for Modern Teams: Three Levels of Pairing

Bringing everything together, here is a clear model for how engineering teams can work today.

Level 1: Autonomous Coding with an AI Friend (Safe Zone)

• Writing code
• Writing tests
• Debugging
• Low-risk automation

This improves speed and quality without major risk.

Level 2: Human Pairing for Design and Review (Important Zone)

• Architecture decisions
• Core feature design
• Code review
• Cross-service interaction

Like gym buddies learning together and preventing injury, humans catch what AI might not.

Level 3: Human-Only for Critical Operations (High-Risk Zone)

• Cloud deployments
• Database operations
• Security changes

Require human pairing, approval flows, and real expertise. This protects systems, customers, and companies.

5. The Philosophy That Connects Gyms and Software Engineering

If Planet Fitness taught us anything, it is this: we go further when we do not go alone.

Whether in the gym or in engineering:

• Pairing builds better habits
• Pairing reduces risk
• Pairing increases discipline
• Pairing extends our lifespan, physical or system lifespan

Today, pairing comes in two forms: human pairing and AI pairing. Wisdom is knowing which to use where.

Just like a gym knows which equipment requires supervision, engineering teams must understand which workflows require human control.

This is the future of software engineering: humans and AI working together, with humans steering the critical paths.

Conclusion

The Planet Fitness bring-a-friend feature is more than a marketing trick. It is a philosophy of partnership, safety, and improvement, and the same philosophy should shape how we build software today.

AI can be your daily gym buddy: fast, supportive, always available. Humans must be your partners in critical, high-risk operations. And when both are used wisely, engineering becomes stronger, safer, and more sustainable.

Just like fitness, software engineering is a journey. And no one should walk it alone.