Industry Insight
Top 12 Abilities for AI-Native Software Developers: What to Look For When Hiring
Industry Insight

Top 12 Abilities for AI-Native Software Developers: What to Look For When Hiring

A comprehensive guide for CTOs and HR recruiters on identifying developers with the perspectives, traits, and knowledge that make them highly effective at leveraging AI coding tools.

Industry Insight
Top 12 Abilities for AI-Native Software Developers: What to Look For When Hiring
Dr. Brian Scott Glassman
12 minutes
December 2025
8 pages
AI-Native Software Developer AI Coding Tools Claude Code Cursor AI Prompt Engineering CTO Guide Technology Recruiting AI Coding

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Industry Insight
Top 12 Abilities for AI-Native Software Developers: What to Look For When Hiring
Author: Dr. Brian Scott Glassman
Reading Time: 12 minutes
Published: December 2025
Pages: 8

Details for the Article

Core Take Aways

AI coding tools deliver 20x to 100x productivity gains, fundamentally changing what CTOs should look for in developers

Three key perspectives: acting as virtual department head, optimizing code for AI consumption, and using processes to de-risk results

Critical abilities include multitasking at scale, rapid problem solving, and building mental models of AI behavior

Natural talents required: high IQ for real-time course correction, innate organization skills, and curiosity to experiment

Essential knowledge spans solution architectures, cross-area expertise, prompt engineering, and token budget management

Traditional skills like expert hand-coding and Agile methodology knowledge are no longer necessary for AI-native roles

Executive Summary

AI coding tools like Claude Code and Cursor are delivering 20x-100x productivity gains. CTOs and recruiters must now hire for AI-first abilities—not traditional coding skills.

The 12 key abilities fall into three categories: perspectives (directing AI agent teams, optimizing for AI consumption, de-risking outputs), traits (multitasking at scale, rapid pivoting, thinking like your AI model), and knowledge (solution architecture, prompt engineering, token management).

Traditional hiring criteria are obsolete. Expert hand-coding and Agile methodology knowledge no longer matter—what counts is the ability to orchestrate AI systems effectively.

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