The trend is undeniable: Juniors are leaning hard on LLMs. They aren't just using them as assistants; they’re using them as proxies for thinking.
As a mentor in 2026, I’ve had to pivot. You can’t ban the tools, so you have to weaponize them. I mix two things that actually work: Extreme Feature Ownership + Ruthless AI Reviewing.
The Simple Rule: Explain or Delete
The workflow is non-negotiable:
- Take the ticket.
- Run the AI version (GitHub Copilot, etc.).
- Spend 2x the time tearing it apart.
In standups and PRs, they must explain every single line. If they can't justify a logic gate or a dependency, we throw it away and redo it together. No exceptions.
The "Ruthless 5" Review Framework 🛡️
To make the review process more than just a "looks good to me," I force them to answer these 5 questions every single time:
- 📈 Scalability & Perf: “What happens if this hits 10K TPS or the database grows 100x?”
- 🚨 Security & Edge Cases: “Where does this break with malicious input or a race condition?”
- 🏚️ Tech Debt: “Which part of this code will bite us in 6 months? Why this specific shortcut?”
- 🏗️ Architecture: “Why this pattern instead of the simpler one we already have in the codebase?”
- 🎯 Business Alignment: “Does this actually solve the core ticket, or is the AI just 'looking smart'?”
The 90-Day Shift
In my experience, after 90 days of this "Ownership + Audit" model, juniors shift. They stop being passengers of the LLM and start becoming the architects guiding it.
The Outcome: Faster ramp-up and more robust code, even without the old-school “write every character from scratch” days.
Let's Talk Strategy 💬
- Who else is implementing structured AI reviews for their teams?
- What specific questions do you force your juniors to answer?
- Are you seeing real growth, or just a mountain of hidden technical debt?
Drop your mentorship patterns in the comments! 👇
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