The AI Development Orchestrator.
Geoffrussy is a CLI-based development platform that interviews you about your project, designs the architecture, generates executable plans, and orchestrates code generation across multiple AI models. Written in Go, distributed as a single binary with zero external dependencies.
# Install via Go toolchain
$ go install github.com/mojomast/geoffrussy@latest
# Or download a pre-built binary from GitHub Releases
$ geoffrussy init
✔ Config initialized at ~/.geoffrussy/config.yaml
$ geoffrussy interviewAn interactive CLI mode where Geoffrey asks probing questions to understand your project scope, constraints, and goals. No prompt engineering required — just have a conversation.
Generates complete system architecture documents with tech stack choices, data models, and component diagrams before a single line of code is written.
Breaks projects into atomic tasks organized in phases. Plans are exported as standard Markdown — portable, version-controllable, and readable by any agent.
Route planning to high-reasoning models (Claude, GPT) and execution to fast, cheap models (Llama, GLM, any Ollama-compatible model). Built-in cost tracking and rate limit monitoring.
Automated checkpoint reviews between phases to catch architectural drift, security issues, and alignment with the original design intent.
SQLite-backed state persistence with checkpoint/rollback. Summarizes project context into a context.md that lives with your repo.
Geoffrey asks clarifying questions about your project using high-reasoning models. What are we building? What's the tech stack? What are the constraints? The interview adapts based on your answers.
A comprehensive architecture document is generated — tech stack, component structure, data models, API design. This becomes the source of truth for everything that follows.
The project is broken down into phased DevPlans with 7-10 phases of 3-5 tasks each. Complex tasks get routed to stronger models; routine coding goes to fast, cheap ones.
Geoffrey orchestrates execution across configured models, tracking progress through each phase. Built-in cost tracking shows exactly what each step costs.
Multi-agent orchestration with 7 specialized AI workers. Proved that cheap agents could coordinate on complex dev tasks. Python-based. 3 stars.
Autonomous CLI coding agent with TUI, swarm mode, and DevPlan workflows. Bash + Python hybrid. Introduced structured planning but needed a ground-up rewrite.
Lessons from both ancestors distilled into a single Go binary. Interview mode, architecture-first, multi-model orchestration, DevUssy engine built in.
DevUssy started as a standalone Python planning pipeline (and still works as one — it has 15 stars on GitHub). Its circular development methodology has been integrated into Geoffrussy as the core planning engine.
When Geoffrussy generates a plan, it uses the DevUssy Protocol — the adaptive interview, complexity analysis, and phased plan generation that DevUssy pioneered. DevUssy provides the thinking patterns; Geoffrussy handles the execution (file I/O, terminal commands, git operations).