A Future Vision
Why AI-Driven Software Development Makes Agile Obsolete
A Future Vision

Why AI-Driven Software Development Makes Agile Obsolete

Explore why Agile's 25-year dominance is ending as AI shatters assumptions about development speed, collaboration, sustainable pace, and team organization.

A Future Vision
Why AI-Driven Software Development Makes Agile Obsolete
Dr. Brian Scott Glassman
6 minutes
January 2025
4 pages
Agile Methodology AI Development Software Engineering Development Process AI Mesh Agents Team Structure Development Speed Future of Work Process Innovation AI Transformation

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A Future Vision
Why AI-Driven Software Development Makes Agile Obsolete
Author: Dr. Brian Scott Glassman
Reading Time: 6 minutes
Published: January 2025
Pages: 4

Details for the Article

Core Take Aways

AI compresses development cycles from months to weeks and weeks to days, making sprint-based planning obsolete

AI mesh agents coordinate simultaneously across codebases, moving faster than human daily standups can manage

Development velocity becomes uncoupled from human effort when AI generates hundreds of lines of code per minute

Marginal cost of generating extra code becomes minimal, eliminating Agile's simplicity principle

AI-powered customer simulation and intent analysis resolves the new bottleneck: understanding genuine customer needs

Executive Summary

For a quarter century, Agile has been the premier framework for managing software development. But CTOs and VPs of Engineering now recognize that its core principles, designed for human-paced development, are being fundamentally broken by AI models that generate hundreds of lines of code per minute. What once made Agile revolutionary—speed, collaboration, and iterative feedback—has become obsolete.

The article systematically dismantles six key Agile principles: Delivery Speed becomes Agile's fatal flaw when two-week sprints force artificial delays on features AI completes in two days. Daily Collaboration cannot keep pace when AI mesh agents coordinate simultaneously across codebases faster than standups can address. Sustainable Pace loses relevance when velocity becomes completely uncoupled from human effort and AI generates in two weeks what humans would produce in six months.

Simplicity and Self-Organized Teams fade when AI makes the marginal cost of generating extra modules or multiple UI options minimal—teams can mock up several interfaces and cross-compare them with AI-simulated customer reviews, openly violating the simplicity principle but producing better results. Meanwhile, team size shrinks dramatically as a few experienced developers with high-performance AI models accomplish what once required entire departments.

Most critically, Customer Needs Over Lines of Code inverts when development moves so fast that entire projects complete before the next scheduled customer feedback session. AI-powered systems can simulate hundreds of rich customer interactions, collaborate with stakeholders to uncover true issues driving change requests, and validate whether changes are necessary across the entire codebase. When coding capacity becomes effectively infinite, understanding genuine customer intent becomes the primary challenge. The article concludes that the industry now demands a new framework designed from the ground up for AI capabilities—one that forward-thinking organizations must begin adopting now or risk becoming as obsolete as Waterfall.

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