Spec Driven Development isn't Waterfall

2026-04-09 · Source: Marc Brooker's Blog · Field: Technology & Digital — Software Development & Engineering, Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

Marc Brooker clarifies that Specification Driven Development (SDD) is not a return to the Waterfall model, but rather an iterative approach where specifications are living, versioned artifacts that evolve alongside software implementation. Unlike static upfront designs, SDD treats specifications as explicit statements of requirements and key design choices, abstracting from low-level code to a blend of words, images, and even mathematics. This method supports the inherently iterative nature of complex software development, aligning with Agile principles like "Customer collaboration over contract negotiation" and "Responding to change over following a plan." A significant advantage of SDD is its ability to enable autonomous AI agents to build and test code by providing a clear "map," accelerating development velocity. Humans remain essential for refining specifications and navigating conflicting requirements.

Key takeaway

For AI/ML engineering leaders evaluating development methodologies, embrace Specification Driven Development (SDD) to significantly boost velocity and quality. SDD treats specifications as dynamic, iterative blueprints, not static upfront designs. This approach empowers autonomous AI agents to build and test code more effectively, freeing your human teams to focus on refining requirements and resolving complex trade-offs. You should integrate living, versioned specifications into your iterative development cycles to fully utilize AI's potential.

Key insights

Specification Driven Development iterates on living specifications, enabling autonomous AI agents to accelerate software delivery.

Principles

• Software development is inherently iterative.
• Specifications are living, versioned artifacts.
• Humans resolve conflicting requirements.

Method

Specifications are explicit statements of requirements and key design choices, separated from low-level implementation. They are iterated on, with implementation derived from them, often by AI agents.

In practice

• Guide AI agents with clear specifications.
• Mix formality levels in specifications.
• Use specs for always-in-sync documentation.

Topics

• Specification Driven Development
• AI Agents
• Iterative Software Development
• Agile Principles
• Requirements Engineering
• Software Architecture

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

Related on AIssential

• Trump’s AI Order Won’t Stymie U.S. Competition with China — A future Trump AI order is predicted to not hinder U.S. AI competition with China.
• EU Unveils Sweeping Tech Sovereignty Push, Balancing Autonomy with Openness — Europe's tech sovereignty strategy balances reducing foreign dependency with fostering domestic capacity and open markets.
• Personalization is the #1 Driver of Meaningful Employee Recognition, Snappy Workforce Study Finds — Personalized recognition, particularly through gifting, is the top driver for meaningful employee appreciation and engagement.
• Micro-Dyn, a leader in healthcare claims pricing software, announces its acquisition of CMSPricer. — Micro-Dyn's acquisition of CMSPricer expands its healthcare claims pricing and contract management platform with new technology and executive expertise.
• ThroughPut.AI Now Available on SBIR Aisle of CDAO’s Tradewinds Solutions Marketplace — AI-driven materiel flow optimization significantly improves military equipment readiness by preempting shortages and streamlining maintenance.
• Asset Panda Introduces “Build with Excel” to Streamline AI-Powered Account Setup in Asset Panda Pro — Asset Panda's "Build with Excel" uses AI to convert existing spreadsheet data into a functional asset tracking system, simplifying setup.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Marc Brooker's Blog.