My Cursor Custom Mode Setup, Part 2: The Execution Team
Last Updated on August 29, 2025 by Editorial Team
Author(s): Mayank Bohra
Originally published on Towards AI.
Don’t just plan, execute. Part 2 of my AI toolkit unveils the 7 expert modes for code reviews, security, and DevOps. Here’s the rest of the setup.
In the first part of this series, I introduced the core philosophy behind my custom AI toolkit: stop using a generic chatbot and start deploying a team of specialized experts. We covered the first seven modes — the “strategists” — who handle high-level tasks like architecture, planning, and complex debugging.

This article continues to explore the remaining modes of the author’s AI toolkit, focusing on execution alongside strategy. It introduces seven hands-on experts specialized in code reviews, security, documentation, and system maintenance, arguing that these roles are crucial for effectively transforming strategic plans into reliable code. Practical applications and methodologies for each expert role are discussed, emphasizing their importance in enhancing software development workflows.
Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.