A couple of days ago, I sat down with Vivek Bharathi and dumped my brains. Here's the interview.

2026-03-12 · Source: Geoffrey Huntley · Field: Technology & Digital — Software Development & Engineering, Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, medium

Summary

Jeff Huntley, a software industry pioneer, asserts that artificial intelligence is fundamentally reshaping the software landscape, driving the cost of software development down to approximately \$10.42 per hour. He distinguishes between "software development," which is becoming a ubiquitous, prompt-driven activity accessible to anyone, and "software engineering," which now focuses on designing robust systems, ensuring safety, and managing risks. Huntley argues that open source software is effectively "dead" because AI can generate code faster and more reliably than relying on human maintainers, thereby eliminating dependency issues and supply chain vulnerabilities. Furthermore, he contends that software is transforming into a "hyper commodity" or utility, eroding traditional competitive "moats" like vendor lock-in. The new competitive advantages will stem from business relationships and contracts, not technological scarcity, prompting venture capitalists to question software's investability.

Key takeaway

For Directors of AI/ML or CTOs evaluating software development strategy, recognize that AI commoditizes basic coding, making traditional "typing on a keyboard" skills obsolete. Your teams should pivot from manual development to engineering robust, automated systems that manage risk and leverage AI for code generation. Embrace AI to accelerate development and control your software supply chain. Otherwise, risk losing competitive advantage and facing "employability suicide" for your staff.

Key insights

AI makes software development a commodity, shifting engineering focus to system design and risk management.

Principles

• Software engineering prioritizes system design and safety over coding.
• Relying on human-maintained open source introduces inefficiencies.
• Traditional software "moats" based on technology are eroding.

Method

Engineering away concerns involves implementing risk-based code review, automating migrations with feature flags, and generating first-party code to control the supply chain.

In practice

• Evaluate current code review processes for risk-based automation.
• Explore AI-driven code generation for internal libraries.
• Reassess business "moats" beyond technological lock-in.

Topics

• AI in Software Development
• Software Engineering
• Open-Source Software
• Code Generation
• Competitive Moats
• AI Career Impact

Best for: Software Engineer, Director of AI/ML, CTO

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Editorial summary, takeaway, and curation by AIssential. Original article published by Geoffrey Huntley.