Two Bars, Spreading Apart

2026-07-28 · Source: Writing is clarifying · Field: Technology & Digital — Software Development & Engineering, Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, medium

Summary

AI is profoundly reshaping software development. One builder's experience shows over 50% of time dedicated to reviewing and challenging AI-generated product and technical strategy. This shift threatens traditional coding and system design skills, sharply raising the bar for excellence. The skill pyramid is transforming: its bottom widens due to lower entry barriers, while the top narrows. This top demands novel problem-solving, durable solutions, and compelling adoption cases. This phenomenon is less pronounced in brownfield companies, hindered by organizational inertia and technical debt. Historical parallels include photography's impact on 19th-century painting. Similarly, AI's effect on writing is evident. New book releases surged from 100,000 to 300,000 per month between mid-2022 and late 2025, coinciding with ChatGPT's introduction. This surge led to declining average quality.

Key takeaway

For software engineers and entrepreneurs navigating the AI-driven landscape, recognize that your traditional coding and system design skills are no longer sufficient differentiators. You must elevate your focus to identifying truly hard problems and crafting novel, durable solutions with exceptionally high effectiveness. Proactively adapt your workflow to incorporate rigorous AI output challenging and independent design reviews, or risk being relegated to the widening bottom of the skill pyramid where competition is fierce and value is commoditized.

Key insights

AI is rapidly reshaping professional skill pyramids, demanding higher excellence at the top and lowering entry barriers at the bottom.

Principles

• The bar for professional excellence rises sharply with AI adoption.
• Differentiated value now lies in insights and novel problem-solving.

Method

The author's workflow involves 50% reviewing/challenging AI strategy and 50% AI implementation, utilizing independent design reviews and quality-gated parallel agents.

In practice

• Focus on novel problem identification and durable solution design.
• Implement independent design reviews for AI-generated code.

Topics

• AI Skill Transformation
• Software Development Workflow
• Competitive Differentiation
• Organizational Adaptation
• AI Content Generation
• Professional Development

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Engineer, Software Engineer, Entrepreneur

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Editorial summary, takeaway, and curation by AIssential. Original article published by Writing is clarifying.