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Vibe To Agentic Framework

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shanraisshan
vibe-to-agentic-framework

The conceptual framework behind the presentation — what "Vibe Coding to Agentic Engineering" means, why the journey is structured the way it is, and how every slide fits the narrative arc

Overview

Publishershanraisshan
Repositoryclaude-code-best-practice
Skill namevibe-to-agentic-framework
Stars
67.4K
Forks
6.7K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by shanraisshan on GitHub. Read the source before you install it.

Installation

Install the Vibe To Agentic Framework AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/shanraisshan/claude-code-best-practice/tree/main/.claude/skills/presentation/vibe-to-agentic-framework
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/shanraisshan/claude-code-best-practice.git /tmp/claude-code-best-practice
mkdir -p .claude/skills
cp -r /tmp/claude-code-best-practice/.claude/skills/presentation/vibe-to-agentic-framework .claude/skills/vibe-to-agentic-framework
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vibe To Agentic Framework in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Vibe To Agentic Framework on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Vibe To Agentic Framework is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

The "Vibe Coding to Agentic Engineering" Framework

This skill teaches the conceptual model behind the presentation. Every slide and section exists to tell a single story: how a developer incrementally moves from unstructured "vibe coding" (Low level) to high-level agentic engineering (High level).

Core Concept

Vibe Coding (Low level) is when a developer uses Claude Code with no structure — no project context, no conventions, no reusable knowledge. Every prompt is a coin flip. Claude might create random endpoints, ignore existing patterns, skip tests, and produce inconsistent code. The codebase drifts toward entropy with every interaction.

Agentic Engineering (High level) is when Claude Code operates as a fully configured engineering system. It knows the project architecture (CLAUDE.md), follows scoped conventions (Rules), loads domain expertise on demand (Skills), delegates to specialized workers (Agents), orchestrates multi-step workflows (Commands), automates lifecycle events (Hooks), and connects to external tools (MCP Servers). Every prompt produces consistent, tested, production-quality code.

The journey between these two extremes is incremental and cumulative. Each best practice builds on the previous ones, and the presentation teaches them in the order a developer should adopt them.

The 4-Level Journey System

The presentation uses a 4-level scoring system instead of a percentage bar:

LevelOrderColorJourney Bar HeightDescription
Low1Red/orange (hsl(0, 70%, 45%))25%Vibe coding territory — no structure
Medium2Yellow (hsl(40, 70%, 45%))50%Structured workflows, some automation
High3Light green (hsl(80, 70%, 45%))75%Domain knowledge, skills, custom agents
Pro4Deep green (hsl(120, 70%, 45%))100%Full agentic engineering, multi-agent teams

The journey bar is hidden on slide 1 (title slide) and appears from slide 2 onward. Levels are set via data-level attributes on key transition slides and inherited by subsequent slides until the next level change. A .level-badge is JS-injected on the slide's h1 when the level changes (do not hardcode these in HTML).

The Running Example: TodoApp Monorepo

Every technique is demonstrated on a realistic full-stack project. The presentation shows the transformation from a plain project (vibe coding) to one with full Claude Code configuration (agentic engineering):

Before (Vibe Coding):

todoapp/
├── backend/          # FastAPI (Python)
│   ├── main.py
│   ├── routes/
│   ├── models/
│   └── tests/
└── frontend/         # Next.js (TypeScript)
    ├── components/
    ├── pages/
    └── lib/

After (Agentic Engineering):

todoapp/
├── .claude/                  # Claude Code config
│   ├── agents/               # Custom subagents
│   ├── skills/               # Domain knowledge
│   ├── commands/             # Slash commands
│   ├── hooks/                # Lifecycle scripts
│   ├── rules/                # Modular instructions
│   ├── settings.json         # Team settings
│   └── settings.local.json   # Personal settings
├── backend/
│   └── CLAUDE.md             # Backend instructions
├── frontend/
│   └── CLAUDE.md             # Frontend instructions
├── .mcp.json                 # Managed MCP servers
└── CLAUDE.md                 # Project instructions

Why TodoApp? It's small enough to fit on slides but complex enough to demonstrate real problems: a backend with route patterns and test conventions, a frontend with component hierarchy and design tokens, and a monorepo structure where cross-cutting concerns (like adding a new feature) require coordination between both sides.

The TodoApp makes the vibe-coding problem concrete: without structure, asking Claude to "add a notes feature" produces a random /api/notes endpoint that doesn't follow routes/todos.py patterns, a standalone page with no sidebar navigation, and zero tests. With full agentic setup, the same request produces a route following existing patterns, a page integrated into the sidebar, and tests matching test_todos.py style.

The Journey Arc: Why This Order

The presentation follows a deliberate pedagogical sequence. Each section unlocks a new capability layer:

Part 0: Introduction (Slides 1–4, no weight)

Purpose: Set the stage. Introduce the TodoApp, define vibe coding, and show the destination.

  • Title slide establishes the journey metaphor
  • Example Project shows the transformation: before/after comparison of TodoApp — plain project structure vs one with full Claude Code configuration (.claude/, CLAUDE.md, .mcp.json, etc.)
  • "What is Vibe Coding?" creates the 0% baseline — the pain point
  • Journey Map provides a clickable TOC showing the full path ahead

Part 1: Prerequisites (Slides 5–9, no weight)

Purpose: Get Claude Code installed and running. This is purely logistical — no engineering practices yet.

  • Installing, authentication, first session, interface overview
  • No weight because knowing how to install a tool doesn't improve code quality
  • The "first session" IS vibe coding — this is intentional, so the developer experiences the 0% state firsthand

Part 2: Better Prompting (Slides 10–17, Level: Low)

Purpose: The first real improvement. Better inputs produce better outputs, even without any project configuration.

  • Good vs Bad Prompts: Specific, scoped prompts vs vague requests. The simplest possible improvement.
  • Providing Context: Using @files to give Claude the code it needs. Reduces hallucination immediately.
  • Context Window & /compact: Understanding the finite context window prevents degraded responses in long sessions.
  • Plan Mode: /plan forces thinking before coding. Prevents wasted effort on wrong approaches.

Why Low level: Prompting is foundational but limited. It improves individual interactions but doesn't create lasting project knowledge. Each session starts from zero.

Part 3: Project Memory (Slides 18–24, Level: Medium)

Purpose: The leap from session-level to project-level knowledge. Claude now remembers across sessions.

  • CLAUDE.md & /init: The project's "README for Claude." Establishes architecture, tech stack, and conventions. This is the single most impactful file.
  • What to Include: Practical guidance on writing effective CLAUDE.md content (keep under 150 lines, focus on what Claude needs to know).
  • Rules: Path-scoped conventions in .claude/rules/. Rules are a multiplier — they apply automatically to every matching file, enforcing consistency without developer effort. A single backend-testing.md rule ensures every test follows the same pattern forever.

Why Medium level: Project memory transforms Claude from a stateless tool into a context-aware collaborator. But knowledge alone doesn't create workflows.

Part 4: Structured Workflows (Slides 25–28, Level: Medium)

Purpose: Systematic approaches that prevent wasted effort and improve execution quality.

  • Task Lists: Breaking complex work into trackable steps. Prevents scope drift and ensures completeness.
  • Model Selection: Choosing the right model (Opus for architecture, Sonnet for implementation, Haiku for quick tasks) optimizes cost and quality.

Why still Medium level: Workflows are important but relatively simple concepts. They build on Part 3's project memory and use it more systematically. The step up to High comes with domain knowledge.

Part 5: Domain Knowledge (Slides 29–33, Level: High)

Purpose: Reusable, on-demand expertise. Skills are the bridge between static memory (CLAUDE.md/Rules) and dynamic agents.

  • What Are Skills: Skills as packaged domain knowledge that Claude loads when relevant. The concept of progressive disclosure.
  • Creating Skills: Hands-on: building a frontend-conventions skill for the TodoApp that teaches Tailwind tokens, component patterns, and sidebar integration.
  • Skill Frontmatter & Invocation: The technical details: YAML frontmatter, manual vs auto-discovery invocation, the context: fork option.

Why High level: Skills are the first "multiplier" concept — one skill definition improves every future interaction in its domain. But skills are passive knowledge; they need agents to become active.

Part 6: Agentic Engineering (Slides 34–46, Level: High)

Purpose: The destination covered in this presentation. Autonomous, specialized agents that coordinate to build features end-to-end.

  • What Are Agents: The concept of specialized subagents with constrained tools and preloaded skills.
  • Frontend Engineer Agent: A concrete agent that uses the TodoApp's frontend conventions, adds routes to sidebar, follows design tokens. Before/after comparison shows the transformation.
  • Backend Engineer Agent: Parallel agent for the backend — follows FastAPI route patterns, SQLAlchemy models, writes tests matching existing style.
  • Commands & Orchestration: The capstone pattern: Command → Agent → Skills. A single /add-feature command coordinates frontend + backend agents, each with their own skills, to deliver a complete feature. This is the architectural pinnacle.
  • Hooks & MCP: Lifecycle automation (pre-commit checks, sound notifications) and external tool integration. The final automation layer.
  • Command → Agent → Skills: The full architecture diagram. Shows how all pieces connect: commands invoke agents, agents load skills, skills provide knowledge. This is the "High level" understanding slide.

Why High level: This section covers the highest-value practices taught in this presentation. Everything before it was building toward this. Orchestration and agentic workflows represent the ceiling of what this course covers — full Pro (multi-agent teams, advanced orchestration patterns) is beyond this presentation's scope.

The High Level Slide (Slide 44)

The celebration moment. Shows the complete TodoApp configuration:

  • CLAUDE.md for project context
  • Rules for path-scoped conventions
  • Skills for domain knowledge
  • Agents for consistent execution
  • Commands for orchestrated workflows
  • Hooks for lifecycle automation
  • MCP servers for external tools

Appendix (Slides 47+, no weight)

Purpose: Reference material. Every command, setting, and configuration option. No weight because these are reference lookups, not journey milestones. Includes: tool usage, all slash commands, commit/PR workflows, customization options, debugging tips, and golden rules.

How to Use This Framework When Editing Slides

When creating or modifying slides, consider:

  1. Where does this concept sit on the journey? A slide about "better error messages in prompts" belongs in Part 2 (prompting, Low level). A slide about "agent memory scopes" belongs in Part 6 (agentic, High level).

  2. What's the before/after? Every significant slide should implicitly or explicitly show the contrast: what happens at Low level (vibe coding) vs what happens with this technique. Use the TodoApp to make it concrete.

  3. Does the level assignment feel right? Level transitions happen at Part section boundaries. Individual slides within a section inherit the section's level.

  4. Does it build on what came before? Skills assume the developer already knows about CLAUDE.md and Rules. Agents assume they know about Skills. Commands assume they know about Agents. Never reference a concept before its section.

  5. Use the TodoApp. Abstract explanations lose the audience. Show the actual routes/todos.py code, the actual Sidebar.tsx component, the actual CLAUDE.md content. The running example is what makes the framework tangible.

Level Transition Reference Table

SlideSlide Namedata-levelLevel Label
10Better Prompting (section divider)data-level="low"Low
18Project Memory (section divider)data-level="medium"Medium
29Domain Knowledge (section divider)data-level="high"High
34Agentic Engineering (section divider)data-level="high"High

All other slides inherit the level from the last data-level attribute set before them. Slides 1–9 (Intro + Prerequisites) have no level and keep the bar hidden until slide 2 shows "Low" (slides 2–9 are below the first level transition at slide 10, so the bar shows empty/zero until slide 10).

Note: The main presentation (presentation/index.html) caps at High level — data-level="pro" is not used. The Pro tick mark remains visible on the journey bar as the theoretical ceiling, but the fill never reaches it. The video presentation (1-video-workflow.html) caps at Medium level.

Frequently asked questions

What does the Vibe To Agentic Framework AI skill do?

The conceptual framework behind the presentation — what "Vibe Coding to Agentic Engineering" means, why the journey is structured the way it is, and how every slide fits the narrative arc

Why use Vibe To Agentic Framework on TypingMind?

Because you install it once and use it with any model. Vibe To Agentic Framework is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Vibe To Agentic Framework in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/shanraisshan/claude-code-best-practice/tree/main/.claude/skills/presentation/vibe-to-agentic-framework. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Vibe To Agentic Framework?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Vibe To Agentic Framework?

As many as you like. As long as a model supports skills, you can use Vibe To Agentic Framework with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Vibe To Agentic Framework AI skill free?

Yes. It is published on GitHub by shanraisshan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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