What is specification driven development with coding agents? Lessons from 40+ successful builds
The velocity that AI agents bring to virtually any use case can never be overstated. One prime use case is its utility as coding agents. With one prompt and a general sense of direction, anybody anywhere can generate working code - but for it to work meaningfully within a codebase is a different matter altogether. Piecing together chunks of code requires careful oversight and rarely works in the…
Spec driven development with coding agents is a methodology that leverages artificial intelligence to generate code based on a clear and concise specification. This approach aims to produce high-quality, maintainable code that aligns with the overall system architecture.
In the year 2026, GoML, a software development company, has successfully implemented 40+ AI systems using this technique with Claude Code. The key to the success of this methodology lies in the structured process it follows.
Traditionally, AI-assisted engineering involves a loop of writing prompts, receiving generated code, reviewing the differences, applying corrections, and repeating the process. However, this method starts to falter when the AI agent transitions from autocompleting functions to implementing multi-tiered features. As the codebase grows, the context gradually degrades, causing the implementation to drift away from the system's actual requirements.
Specification driven development (SDD) addresses this issue by reorganizing the AI coding session around three documents instead of one conversational document: a spec, a plan, and the code itself. The spec is a plain language document describing what a change should do and what it should not do, written before any code is generated.
The plan breaks down the spec into a numbered sequence of implementation tasks, naming the files involved. The code is then generated by the AI assistant against the plan, with a human checkpoint between phases.
The spec provides a persistent anchor throughout the session, ensuring that the AI model's intent remains consistent. This approach verifies that the feature does what the requirement says, across files and services, something that unit tests alone cannot achieve. Unlike vibe coding, which relies on natural language prompts and natural language prompts, SDD verifies the feature against the requirement, spanning multiple files and services.
There are three levels of specification rigour in SDD: Spec First, Spec Anchored, and Spec-as-Source. The choice of which level to use depends on the specific needs of the project. Spec First minimizes overhead in case of isolated feature additions, while Spec Anchored provides documentation for long-lived systems, regulatory audits, and onboarding new developers. Spec-as-Source requires a mature compiler infrastructure and is suited to strict, API-first environments.
Anthropic's EPIC pattern, which stands for Explore, Plan, Implement, and Commit, provides a foundation for SDD. However, true specification driven development goes beyond this pattern by turning the intent of Plan Mode into a persistent batch of repository files, enabling longer context work. This ensures that the codebase remains clunky-free and the feature aligns with the system's overall requirements.
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