This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Drop markdown files into your IDE workspace and your AI coding agent gains structured expertise — it knows what to ask, what to produce, and when to hand off to the next stage. No plugins. No APIs. No vendor lock-in. Just professional process knowledge, packaged so an AI assistant can execute it with human oversight at every gate.
**The problem it solves:**
AI coding agents are powerful but directionless. They write code fast but skip architecture, ignore governance, produce no test strategy, and deliver nothing a team can actually ship with confidence.
AIPDLC gives them structure — the same stage-gate discipline a senior engineering org would follow, delivered as injectable files.
**How it works:**
11 packages chain across two layers:
- **Portfolio Layer** — AI-ILC (idea evaluation) → AI-PILC (project initiation) → AI-PPM (portfolio governance)
- **Project Layer** — AI-POLC (product ownership) → AI-UXD (UX design) → AI-ADLC (architecture) → AI-DWG (workspace generation) → build
- **Continuous** — AI-GCE (compliance) + AI-TGE (test accountability) run alongside
Each package makes the agent adopt a professional role (PMO advisor, CTO, DevOps engineer, QA lead) and produce real deliverables with approval gates at every stage.
**Key facts:**
- Works with Cursor, Claude Code, Kiro, Amazon Q, Cline, GitHub Copilot
- Each package works standalone OR chained
- Human-in-the-loop — you approve every gate
- Apache 2.0 licensed, free to use
- Install in 60 seconds
**One-command install:**
```
npx skills add mbmd/AIPDLC
One thing that would really help me adopt this is a starter library of templated PDLCs for common workflows like bug triage, API design reviews, or onboarding new repo contributors. Right now figuring out the right structure and gate definitions for each team seems like a lot of upfront work, and a few battle tested templates would lower the barrier to trying it out on a real project.
Would love to see a built-in diff view that shows which parts of the markdown process docs the agent actually consulted during a session, so I can audit what shaped its decisions. Right now I have to guess why it asked certain clarifying questions or produced specific artifacts, and that opacity makes the human oversight loop feel less tight than it should.
the whole approach of dropping markdown files into your workspace and letting the agent pick it up is honestly pretty clever, feels way more natural than another config-heavy tool.
Drop markdown files into the workspace and the agent picks up structured expertise. Nice approach, no vendor lock-in is a big plus. One thing that would make this more useful for my team: a small CLI or watcher that validates the markdown structure against a schema before the agent ingests it, so we catch missing gates or broken handoffs at commit time instead of mid-run.
AIPDLC was submitted on Product Hunt and earned 8 upvotes and 5 comments, placing #157 on the daily leaderboard. Drop markdown files into your IDE workspace and your AI coding agent gains structured expertise — it knows what to ask, what to produce, and when to hand off to the next stage. No plugins. No APIs. No vendor lock-in. Just professional process knowledge, packaged so an AI assistant can execute it with human oversight at every gate.
AIPDLC was featured in Open Source (68.6k followers), Developer Tools (515.9k followers), Artificial Intelligence (473.8k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 221.8k products, making this a competitive space to launch in.
Who hunted AIPDLC?
AIPDLC was hunted by AIFLC. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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