Aigon
Terminal tabs everywhere
Parallel agents generate momentum, but tracking what each one did and why becomes manual overhead.
Spec-driven development · Multi-agent orchestration
Spec-driven AI development.
Orchestrate any agent — or all of them at once.
Aigon captures the full product lifecycle — research, feature delivery, and user feedback — in specs and logs committed directly to your repository. Run one agent with tight control, or orchestrate competing implementations in parallel — then evaluate and merge the best outcome.
- Work visually with a Kanban board, drop to the CLI for scripting, or drive from slash commands inside your agent — one workflow at every level of control
- Four clear modes: Drive, Fleet, Autopilot, and Swarm
- Specs, logs, and research findings in Git — searchable, portable, permanent
- Works with Claude, Gemini, Cursor, and Codex — swap freely or run them head-to-head
- No required SaaS account, plain files in Git, no proprietary formats
Codex and Gemini compete, Claude Code evaluates — best implementation wins.
1. Fleet started — agents implementing in parallel
2. Both submitted — Claude Code evaluating
3. Evaluation complete — winner merged
The problem
AI agents multiply output fast, but coordination breaks down even faster.
Decisions get lost
Without spec-linked workflows, merge decisions and implementation tradeoffs disappear into chat history.
No clean comparison step
Teams rarely compare multiple implementations side-by-side before merging the best approach.
Feedback loops stay disconnected
User feedback, research, and implementation often live in separate tools with no shared lifecycle.
CLI in action
Slash commands inside your agent — one workflow at every level of control.
Value proposition
Aigon turns multi-agent output into an auditable delivery system.
Traceability
Specs and decisions live in your repo
Research, feature specs, implementation logs, and evaluations stay in Markdown files your team can review and version.
docs/specs/features/03-in-progress/
docs/specs/features/logs/Vendor independent
Use the agents you already prefer
Run the same workflow with Claude, Gemini, Cursor, and Codex without rewriting your process around one tool.
aigon install-agent cc gg cx cuShared lifecycle
Research, delivery, and feedback connect end to end
Aigon links discovery, implementation, review, and follow-up so each cycle improves the next one.
research -> feature -> eval -> closeOperational clarity
Mode-based commands reduce team confusion
Pick the right execution mode for each task and make expected behavior explicit before coding starts.
aigon feedback-triage 14How it works
Research, build, learn — on repeat.
Choose your mode
Hands-on or hands-off, one agent or many.
Hands-on + one agent
Drive mode
Use when you want tight control over implementation details and review checkpoints.
aigon feature-setup 07Outcome: one guided implementation branch with a full spec and log trail.
Hands-on + multi-agent
Fleet mode
Orchestrate competing implementations you can evaluate and adopt the best from.
aigon feature-setup 07 cc gg cxOutcome: parallel worktrees and comparable outputs for structured selection.
Hands-off + one agent
Autopilot mode
Use when the scope is clear and you want autonomous retries against validation checks.
aigon feature-autopilot 07Outcome: automated implement-validate loop that stops when checks pass or budget ends.
Hands-off + multi-agent
Swarm mode
Fully orchestrated, fully autonomous — parallel agent runs converge into comparable outputs ready for evaluation.
aigon feature-setup 07 cc gg cx
# in each worktree:
aigon feature-autopilot 07 --auto-submitOutcome: concurrent autonomous runs across agents with logs ready for comparison.
The steps
From idea to merged code.
Create a feature spec and move it into the backlog.
Your workflow, visualised
A Kanban board for spec-driven development.
The Aigon Dashboard is the visual way into your spec-driven workflow. Same pipeline, same agents — but managed through a browser UI instead of CLI commands. Drag features across columns, launch agent sessions with one click, and watch your pipeline move in real time. No terminal required.
Visual Workflow
Drag specs from inbox to done
Move features through your development pipeline with a familiar Kanban interface. Every column maps to an Aigon workflow state — no commands to memorise.
Monitor
See every agent, every repo, at a glance
The monitor tab shows running sessions, attention items, and recent events across all your repositories — everything you need to know at a glance.
Measure
Throughput, cycle time, agent performance
The statistics tab turns your spec history into metrics. Know which agents ship fastest, how your cycle time trends, and whether your pace is accelerating.
Remote Access
Monitor agents from your phone
The dashboard runs on your local network — open it on your phone or tablet over LAN, or use Tailscale to check on your agents from anywhere. Monitor from the couch.
Documentation
Install in minutes, then run your first end-to-end loop.
git clone https://github.com/jayvee/aigon.git
cd aigon
npm install
npm link
cd /path/to/your/project
aigon init
aigon install-agent cc gg cx cuThen, in Claude Code:
/aigon:feature-now dark-mode
Implement a dark mode capability to the website,
with dark mode/light mode toggle in the top right
position of the menu barTech & philosophy
Open source, git-native, and intentionally simple.
Aigon is built for teams who want disciplined AI-assisted engineering, not opaque automation.
- Open SourceMIT licensed, no paid-tier lockouts.
- Repo-Native ContextSpecs, logs, and evaluations stay as plain Markdown in your repository.
- Agent-AgnosticWorks with whichever coding agents your team chooses.
- Adapts to Your StackWorkflow templates and defaults adjust for web apps, APIs, iOS, Android, and libraries.
Community
Help shape the next generation of collaborative AI development.
Contribute specs, improve workflows, and share real-world patterns for running multi-agent engineering teams effectively.