Compare Spec-Driven Tools

How specs.md compares to Spec Kit, BMAD, Kiro, and OpenSpec

specs.md: One Framework, Three Flows

Three Flows Available

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Comparison Matrix

Quick Comparisons

Key Differentiators

1. AI-DLC is a Formal AWS Methodology

Unlike generic “spec-driven development,” AI-DLC is defined by AWS with specific phases, rituals, and artifacts. specs.md is a faithful implementation—not an interpretation.

2. DDD as Default, Extensible via Bolt Types

Agile frameworks leave design techniques optional. AI-DLC integrates Domain-Driven Design as its default—AI applies DDD principles during decomposition, developers validate.

Extensible: Use bolt types to add other methodologies like BDD, TDD, or model your own construction flow. DDD is the default, not a limitation.

3. Bolts: Batched Stories with Full Traceability

Unlike other tools with variable iteration cycles, specs.md uses Bolts—planned batches of related stories executed together by an agent. Each Bolt follows DDD steps during execution, and artifacts created during construction provide full traceability of what was built and how.

Intent → Units → Stories → Bolt (batched stories)
                              ↓
                    DDD Construction Steps
                              ↓
                    Traceable Artifacts

4. Reversed Conversation Direction

In AI-DLC, AI initiates and directs conversations. AI proposes breakdown, trade-offs, designs. Humans validate and approve. This is the opposite of most tools where humans prompt AI.

5. Mob Rituals for Team Alignment

Mob Elaboration (Inception) and Mob Construction condense weeks of sequential work into hours while achieving deep alignment between team and AI.

6. Built for Complex Systems

Vendor Lock-in

Cost Comparison

Roadmap

Further Reading