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AI transforms Agile in software development

AI radically changes development methodologies, making Agile obsolete due to process acceleration. A three-level requirements system is proposed for comprehensive coding and return to a structured approach with prototyping. Adaptation of organizations to new developer roles.

Why AI kills Agile: new rules for dev processes
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AI is Killing Agile: New Software Development Methodologies

Artificial intelligence is radically speeding up software development, making traditional Agile constraints obsolete. Instead of iterative sprints and breaking tasks into tiny pieces, we can now deliver comprehensive solutions in a single pass. Coding time drops to near zero with a clear outcome description, shifting focus back to high-level architecture and domain expertise.

AI eliminates the need for Agile's bloated rituals, which arose from human limitations. Task formulation evolves: from user stories for transparency to detailed specs that enable efficient code generation.

Resistance to Change and the New Role of Developers

Adopting AI faces pushback in organizations where faster processes aren't always welcome. Kent Beck points to a trend toward introverted programmers who focus on a tight circle of colleagues and AI agents. Companies need to foster safe environments for these "production units."

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The shift means ditching constant meetings for deep task immersion. The process starts with domain understanding, architecture selection, then detailed breakdown.

Three-Tier Requirements Formulation System

A structured approach to task descriptions for AI is emerging in practice:

  • Functional requirements — 1–2 sentences for the project backlog.
  • Solution description — 1–2 paragraphs covering tech nuances and approaches.
  • Refined requirements — 2–4 pages, AI-generated and tweaked for focus, ready for coding.

AI handles the full context: from architecture to UI. No more sprints for trivial tasks like "build a button" — the entire requirement gets implemented at once.

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Back to Waterfall with Prototyping

Documentation flows from high-level to specifics: project vision, architecture, details. It's like waterfall, but with vibe-coding for prototypes.

  • Rapidly build working models to test hypotheses.
  • Refine drafts into structured specs.
  • Repackage prototypes to meet production standards.

This workflow is simpler than iterative cycles: you see a working system before full development, slashing risks.

Key Takeaways

  • AI removes speed limits, rendering Agile redundant.
  • Detailed specs replace user stories for end-to-end coding.
  • Three-tier requirements provide context and precision.
  • Vibe-coding prototypes speed up production readiness.
  • Organizations must adapt cultures for introverted AI-savvy specialists.

— Editorial Team

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