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GenAI development techniques — comparison

A comprehensive, evidence-based comparison of techniques, methodologies, and frameworks for structured AI-assisted software development. The focus is on how humans organize and direct AI coding agents — not on the AI models or tools themselves.


Start here

Choosing Your Approach — Which technique fits your situation? Decision guide by team size, project type, industry, and development activity.

Overview and comparison matrix — Executive summary, full comparison table, and category analysis.


Deep-dive documents

Decision guide

Document Description
Choosing Your Approach Which technique for which situation — by team size, project type, industry, methodology, and task type

Spec-Driven Development

Star counts are snapshots observed on August 8, 2026. They are awareness signals, not adoption evidence.

Technique Description Stars
GSD (Get Shit Done) Spec-driven workflow continued as GSD Core after the original repository was archived ~7.9K*
Spec Kit GitHub's official toolkit for spec-driven development — specs → plans → tasks ~126K
OpenSpec Change-centric SDD with delta specs, broad multi-tool support, and a vendor-neutral skills target ~64K

* GSD migrated from an archived repository with ~64.7K stars to open-gsd/gsd-core; the successor repository started its own count.

Multi-Agent Orchestration

Technique Description Stars
Squad Coordinator-based multi-agent orchestration with persistent memory, casting, and ceremonies ~3.1K
BMAD AI-driven agile framework with specialized roles, structured phases, and modular workflows ~52K

Skill-Based Development

Technique Description Stars
Superpowers Mandatory skills methodology — TDD, subagent-driven development, and review enforcement ~269K

Autonomous Iteration

Technique Description Stars
Ralph Autonomous bash-loop methodology — tests as backpressure, git as memory, tool-agnostic Community

Enterprise AI-Native SDLC

Technique Description Stars
HVE Microsoft ISE's RPI workflow with constraint-based governance and a growing repository-level skills inventory ~1.3K

Cross-cutting

Technique Description
Context Engineering The practice of structuring project context via rules files across an 8-layer model

Skills ecosystem

This supporting market layer is not an eleventh Tier 1 technique or a sixth methodology category.

Document Description
Skills ecosystem Agent Skills specification, mattpocock/skills, skills.sh, Anthropic reference skills, GitHub's Copilot channel, portability, provenance, and selection guidance

Audience: Developers, tech leads, and engineering managers evaluating structured approaches to AI-assisted development.

What this is not: A ranking. Each technique serves different needs. The Decision Guide in the overview helps match techniques to situations.