Agile AI development framework that simulates a full team of specialized agent personas across a four-phase lifecycle, scaling its ceremony to project complexity.
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Metrics updated Sep 1, 2026 · collected automatically from the GitHub API
Core approach
Simulates an agile team of 12+ specialized AI agent personas (PM, Architect, Developer, UX, and more) that facilitate structured workflows across a four-phase lifecycle. Planning depth auto-adjusts to project complexity, from bug fixes to enterprise systems. Installed via npx as a module ecosystem with 34+ workflows in the core module.
Parallel Quick Flow track — quick-dev and an unattended dev loop for small changes
Supported tools
Claude Code
Cursor
Codex
Gemini Gems
ChatGPT Custom GPTs
Strengths
Broadest lifecycle coverage of the frameworks tracked here — ideation through retrospective, not just spec-to-code
Modular ecosystem (builder, test architect, game dev, creative suite) plus web bundles that offload planning to Gemini Gems or ChatGPT Custom GPTs on flat-rate LLM subscriptions
Scale-adaptive planning depth, with a help workflow that guides users to the next step
Free and open source with a large, active community and frequent releases
Limitations
Heavyweight and ceremony-rich compared to lighter SDD kits — many agents, phases, and workflows to learn
V6 was a breaking restructure; upgrading from v4/v5 requires a dedicated migration guide
Prerequisites span Node.js 20.12+, Python 3.10+, and uv
The repo does not visibly dogfood its own story/PRD artifacts in-tree, and BMAD/BMad are trademarks with usage restrictions
Neurosymbolic AI agent framework (LLM + Prolog reasoning, Python and Rust) running BMAD's story and QA-gate workflow at real scale — hundreds of story files and QA artifacts — while skipping the PRD and architecture documents.
BMAD reads less like a spec format and more like an operating model: it recreates the roles of an agile team as
agent personas and routes work through their ceremonies. That makes it the most complete lifecycle of the tracked
frameworks and also the heaviest. Its repository moved from bmadcode/BMAD-METHOD to the bmad-code-org
organization, and GitHub reports its license as “Other” because the MIT text carries a custom preamble. Well-starred
active adopters are hard to observe in public — code search finds ~400 v4-era .bmad-core configs, but the most
visible ones have gone idle — so evidence of long-term outcomes is currently thin.
Added Jul 18, 2026 · Assessment last reviewed Jul 18, 2026 ·
How we track