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Vibe Coding

What is Vibe Coding?​

Definition: Using AI to translate intent into working software through iterative collaboration.

  • AI accelerates implementation: The bottleneck is no longer writing the syntax.
  • Human ownership: The human still entirely owns the requirements, architecture, and final quality control.

Why it Matters for Hackathons​

  • Faster iteration: Spend less time fighting bugs and more time refining product-market fit and UX.
  • Smaller teams can build more: One or two developers can launch a feature-complete product over a single weekend.

The Vibe Coding Stack​

  • LLMs: ChatGPT, Claude
  • AI IDEs & Tools: Cursor, Copilot, Bolt, Lovable

Key Concepts: Managing your Context

The Context Window​

Requirements + Code + Chat History + Files = Context Window

Everything competes for attention inside an LLM's memory. Every new message carries previous context
(Message 1 → sends 1; Message 2 → sends 1 + 2). As the chat history grows:

  1. Focus decreases
  2. Consistency drops
  3. Quality decreases

Context Rot​

Why AI Starts Getting Weird​

When an AI model starts losing its focus under a heavy context load, it isn't broken—it's experiencing Context Rot.

Watch out for these symptoms:

  • ✅ Good Context: Consistent responses; references previous project requirements correctly.
  • ❌ Context Rot: Hallucinating features, reintroducing old bugs, changing unrelated code, forgetting architecture, or delivering massive, unexplained code changes.

Tokens​

What is a Token?​

AI doesn't see words; it breaks down text into chunks called tokens.

  • "hello" ≈ 1 token
  • "Build a React dashboard" ≈ 4-5 tokens

Token Efficiency Best Practices​

To keep costs low, focus sharp, and prevent early context rot:

  • Give complete requirements upfront.
  • Attach only relevant files.
  • Avoid repeatedly pasting the exact same information.
  • Use summaries and clear project documentation.

💡 Tip: If you are using Claude, type /compact in your chat. This prompts the AI to summarize your message history into fewer tokens, instantly freeing up memory workspace.

Skills​

What are Skills?​

  • Definition: A reusable instruction set that teaches an AI exactly how you want work done.
  • The Analogy: A Prompt is like a direct function call; a Skill is the underlying system instruction file that the AI reads every single time.

Why Skills Matter​

  • Without Skills: You have to manually explain your architectural preferences and rules every time you open a new chat.
  • With Skills: You reuse custom instructions automatically, saving tokens, ensuring strict output consistency, and accelerating developer onboarding.

Skill Examples​

  • React Engineer Skill: "Always use TypeScript, use Tailwind CSS, add descriptive comments, and write automated tests."
  • Hackathon Judge Skill: "Always evaluate submissions based on Novelty, Feasibility, and Demo quality."