Most AI coding agents (Claude Code, OpenAI Codex, OpenCode, DeepSeek Harness) write code fast, but they break architectures in large production codebases.
Here are the 3 biggest problems with raw agents:
To fix this, I created Supergraph — an open-source workflow and orchestration engine for AI coding agents.
Supergraph enforces a strict 8-step engineering lifecycle on every task:
scan → analyze → plan → TDD → execute → fix → verify → review
Powered by Codebase Memory MCP (SQLite + ZSTD graph database) and Serena LSP, Supergraph indexes your repository locally. Before proposing a single code change, it calculates the mathematical blast radius. If you attempt to modify a high-degree hub node or bridge node, it flags the risk immediately and halts reckless edits.
Supergraph enforces a strict RED → GREEN → REFACTOR cycle:
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For complex features or refactors, Supergraph schedules tasks as a Wave DAG. Each agent worker claims an isolated git worktree branch. Tasks execute in parallel without dirtying your main working tree. A verification gate checks tests and linter before merging back into main, with a live status dashboard running at http://localhost:3333.
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Built on native Rust CDP (agent-browser, zero Playwright bloat). It bypasses anti-bot defenses using real browser profiles, captures token-efficient Accessibility Tree snapshots (@ref), and executes 5-dimension ISTQB test matrices (UI + API + database fault injection).
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Built-in prompt engineering and tool-result pruning strip conversational fluff while keeping code and terminal outputs technically exact, saving token costs across multi-hour sessions.
Supergraph runs identically across 5 agent platforms:
Install in one command (macOS/Linux/WSL):
curl -fsSL https://raw.githubusercontent.com/datit309/supergraph/master/install.sh | sh
Or on Windows PowerShell 5.1+:
irm https://raw.githubusercontent.com/datit309/supergraph/master/install.ps1 | iex
Start your session with:
/supergraph:scan # Ingest graph context
/supergraph:analyze # Risk & blast radius check
/supergraph:plan # Generate DAG plan
/supergraph:execute # Parallel git worktrees execution
Supergraph is 100% open-source under the MIT license:
⭐ GitHub Repository: https://github.com/datit309/supergraph
If you find this approach useful, please drop a Star on GitHub! Pull requests for new skills, test runners, and platform integrations are warmly welcomed.