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AI-Native Boilerplate
170+ rules that stop AI coding agents from drifting
AI coding assistants drift. Every new session starts with zero context — and slowly, your architecture diverges from its own conventions. AI-Native Boilerplate is a structured discipline layer for AI agents (Claude Code, Cursor, Copilot, Windsurf, Cline). A generator builds a single token-efficient context file tailored to your stack, so your agent follows your rules from session one. 6 layers: Core → Stack → Features → Design System → Custom → Compliance (GDPR, HIPAA, SOC2, PCI) MIT licensed.
Hey Product Hunt! 👋
I'm Srikanth, the maker of AI-Native Boilerplate.
This started as a personal frustration — I was building production apps with Claude Code and Cursor, and no matter how carefully I set up my architecture, the AI would slowly drift from my conventions. New session = blank slate = drift.
The fix was structural: encode your rules once, generate a single context file, and your agent follows them consistently across every session.
The project is MIT licensed and I'm actively maintaining it. Would love your honest feedback — especially from teams already using AI coding agents in production.
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About AI-Native Boilerplate on Product Hunt
“170+ rules that stop AI coding agents from drifting”
AI-Native Boilerplate was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #130 on the daily leaderboard. AI coding assistants drift. Every new session starts with zero context — and slowly, your architecture diverges from its own conventions. AI-Native Boilerplate is a structured discipline layer for AI agents (Claude Code, Cursor, Copilot, Windsurf, Cline). A generator builds a single token-efficient context file tailored to your stack, so your agent follows your rules from session one. 6 layers: Core → Stack → Features → Design System → Custom → Compliance (GDPR, HIPAA, SOC2, PCI) MIT licensed.
AI-Native Boilerplate was featured in Design Tools (262.4k followers), Developer Tools (519k followers), Artificial Intelligence (478.1k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 274.3k products, making this a competitive space to launch in.
Who hunted AI-Native Boilerplate?
AI-Native Boilerplate was hunted by Srikanth Vemulapalli. 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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Srikanth Vemulapalli