AI coding agents write code fast — but PRDs still miss acceptance criteria, prototypes can't be tested, and dev handoff is chaos. AI Delivery Spec fixes this with a tiered spec framework (L0-L3) that bridges product, engineering, and AI agents into one delivery pipeline.
Hey Product Hunt! 👋 I'm franklinxkk, a ToB AI product manager based in China.
Why I built this:
AI coding agents (Claude Code, Codex, Cursor) write code insanely fast. But product delivery is still chaos:
- PRDs missing acceptance criteria
- Prototypes that can't be tested
- Dev handoff that's ambiguous
- AI features without runtime governance
After 7+ years shipping ToB SaaS and seeing the same problems across CRM, traffic safety, education IT, and healthcare IT projects, I realized: the bottleneck isn't coding speed — it's specification quality.
What makes AI Delivery Spec different:
| Problem | AI Delivery Spec |
|---------|-----------------|
| Every feature gets the same template | L0–L3 tier system adapts to complexity |
| Prototype ≠ testable | Built-in prototype testability rules |
| AI features lack guardrails | AI runtime contract, human gates, rollback |
| Coding agents guess business rules | DDD handoff + ac_structured YAML contracts |
| Generic skills don't know your domain | 4 replaceable domain modules (CRM, traffic safety, education, healthcare) |
Quick start (under 5 minutes):
git clone https://github.com/franklinxkk/a...
Then tell your AI tool: "Use AI Delivery Spec. Mode=Lite, Tier=L1. Write a light PRD for [your feature]."
Works with: Claude Code, Cursor, Codex, Copilot, OpenClaw, Gemini — any AI that reads Markdown.
Complementary with GitHub Spec-Kit: spec-kit handles spec→code, AI Delivery Spec handles requirement→spec+prototype.
I'd love feedback from:
- Product managers shipping ToB/ToG products
- Tech leads managing multi-team delivery
- Teams adopting coding agents in production
Ask me anything! 🙌
🔗 GitHub: https://github.com/franklinxkk/a...
📄 License: Apache 2.0
⭐ v4.6.2
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