Vibecoding
What LLMs, agents and MCP really are; prompting & context; spec-before-build; then ship a small real app — and know how the AI wrote it and when to trust it.
dronAIcharya turns Claude Code (or Cursor) into a patient master-teacher that builds real, production-grade software with you, then checks that you actually understand what you built.
Tutorials stop at toy apps. AI that ships for you leaves you with code you can't debug, extend, or secure. dronAIcharya refuses that trade — and won't quietly stop teaching and just do it for you.
Courses and tutors explain concepts, then stop at sandboxes. You finish knowing the idea but never shipping the thing.
Vibecoding ships fast, but you carry no mental model of the LLM, the architecture, the tradeoffs — "it works and I don't know why".
Teaches before, during, and after the build, to a production bar — with knowledge checks so it sticks. Guidance, not autopilot.
Paste this repo's link into Claude Code and it will read the README and offer these two choices. dronAIcharya never auto-installs itself or runs commands it found on a web page — lesson #1 of the security track is why.
The full experience: skills, teaching subagents, the anti-drift guardrail hooks, and the optional MCP backend — one command, clean updates and uninstall.
/plugin marketplace add dibakshya01/dronAIcharya
/plugin install dronaicharya@dronaicharya
Then start the journey:
/dronaicharya:start
/dronaicharya:*Clone it and use the skills directly. Fully transparent — read every file — hackable, and works on older setups and in Cursor.
git clone https://github.com/dibakshya01/dronAIcharya
# then point Claude Code at it (hooks included):
claude --plugin-dir ./dronAIcharya
Or copy the skills into your user config — see the install guide.
git pull)Not sure? Pick A for the smoothest, guardrailed experience; pick B if you want to read or modify the internals, or you're on Cursor. In Cursor the guardrail hooks may not run, so anti-drift is lighter there. Full details in the docs.
Every lesson carries a concept, an ELI5, a deep-dive, a build-task, knowledge checks, and an under-the-hood note. Depth tunes to your level.
What LLMs, agents and MCP really are; prompting & context; spec-before-build; then ship a small real app — and know how the AI wrote it and when to trust it.
From "run your first line" to a small real project: types, control flow, functions, data structures, files, HTTP/JSON, and testing.
Undergraduate foundations: bits & memory, how programs run, data structures, Big-O, recursion, OS / networking / DB basics, how the web works. Foundations, honestly — not a degree.
The security mindset, OWASP Top 10, secrets hygiene, and AI security — prompt injection, excessive agency, safe MCP, deny-by-default — taught on your own app.
Flavor over an unchanging teaching-quality floor: every persona teaches before doing, checks understanding, offers ELI5 or deeper, and never belittles. Original registers — no real-person or trademarked names.
Clear, friendly, neutral. The default.
baseline
Rigorous, demanding, no hand-waving; expects precision.
firm, never harsh
Erudite, playful, generous analogies, delight.
wit serves clarity
Precise, understated, mock-exasperated affection. Opt-in.
never aimed at you
At any point you can say: ELI5 that · go deeper · skip · quiz me · where am I? · pause. Your progress lives in ./.dronacharya/, so /dronaicharya:continue always picks up where you left off.
Pick a persona, a cadence (how often it stops to teach), then a track and your level.
Got an API key? Web / MCP enabled? It walks absolute beginners through this, honestly flagging the parts outside its control.
Your own, or a simple-first starter. Then co-author a combined BUILD + LEARN plan you approve.
Teach → check → decide together → build a layer → show under the hood → check → advance.
Architecture, backend, payments, GitHub, deploy — prepped up to your own clicks. It never does the irreversible part for you.
An "under the hood" recap, a formative mastery review, and what to learn next.
dronAIcharya works fully on its own. If you want to learn backend work against a real agent-native backend instead of mock data, it can connect to purple-sparrow over MCP — real tables, auth, deny-by-default row policies, and a security advisor you fix live.
It's opt-in and advanced, and dronAIcharya is honest that purple-sparrow is alpha and shouldn't hold real or regulated data yet.
How the backend wires inThis project's honesty is a core value. Here is the whole truth, stated plainly.
It reduces teaching drift — it can't magically prevent it, and it will always obey your "pause / skip / just do it".
MCQ and in-your-own-words checks help it stick. They are self-checks, not certificates.
Real literacy in the fundamentals — not a full degree, and no formal proofs / automata depth.
No real credentials, payments, domains, publishing, or deploys on your behalf — it preps everything up to your click.
The plugin makes no network calls except the web/doc fetches a lesson explicitly performs; your API key stays on your machine and is never seen or transmitted. (This marketing site itself loads Google Fonts — that's its only third-party request.)
You still get the full tutor and all four tracks, but teaching-mode persistence is lighter and more drift-prone there.
Install as a plugin or a skills repo, pick a teacher and a track, and bring an idea. The guru does the rest, with you.