🧠 django × ai-system

Ship ai system on Django with sensible defaults.

Django is a Python workable choice for ai system. GreatCTO auto-detects both — adds the ai-system archetype overlay, wires ai-system-specific gates, and runs 34 specialist agents around your existing Django workflow.

$ npx great-cto init 🧠 See archetype →
What changes when GreatCTO joins your Django project

Detection → overlay → gates → reviewers.

1 · DETECT

Stack + archetype

GreatCTO reads your pyproject.toml / requirements.txt and detects django + ai-system archetype from signals: imports, file structure, env vars, README hints.

2 · OVERLAY

Archetype pack

Attaches the ai-system archetype overlay: EU AI Act + GDPR + OWASP LLM gates, training-data lineage, model card requirements. Override if your specifics differ; the defaults are sensible for Django-style projects.

3 · GATES

Django-aware reviewers

qa-engineer runs mypy / ruff / pytest --cov; security-officer scans for SQL injection patterns common in ORMs (SQLAlchemy, Django ORM); performance-engineer profiles async patterns for inference latency.

4 · MEMORY

Cross-project lessons

Bugs you've hit before in other Django projects (connection-pool exhaustion, ORM N+1 queries, retry storms) — the agent's Step 0 includes the prior detection order. MTTR drops 94 % on second occurrence (methodology).

First 10 minutes

Concrete walkthrough.

$ cd my-django-app && npx great-cto init
✓ scanning manifests… found pyproject.toml
✓ stack: django (Python)
✓ archetype: ai-system
⚠ archetype + stack combo is unusual — review overlay manually
✓ 34 agents ready

$ /start "add model inference endpoint"
▸ architect drafting ARCH-ai-system.md…
▸ pm decomposing into beads tasks…
⚐ gate:plan — your approval needed

Approve → 3 senior-devs run in parallel worktrees → 5 reviewers fan out in parallel → gate:ship → deploy. One real run walked stage-by-stage: /proof.

⚠ Honest caveat

Django (Python) is not a typical fit for ai system. The archetype overlay still attaches, but you may want to override defaults more aggressively. Check the ai-system archetype page for the typical stack list and decide if your case is the right tool / right archetype.

Architecture

Every step of the pipeline, transparent.

No black-box "AI does it all" loop. GreatCTO is a deterministic state machine — 8 stages, 22 nodes, 2 human gates. Every node maps to a real agent on GitHub. Inspect the state machine →

Install

Django + GreatCTO in one command.

$ npx great-cto init

Free, MIT, runs locally. Works in Claude Code, Cursor, OpenAI Codex CLI, Aider, and Continue.