Designing with Intention: Why Vibe Coding Ships 80% Waste and What to Do About It | Doha .

Members-Only

Recent Talks & Demos are for members only

Exclusive feed

You must be an AI Tinkerers active member to view these talks and demos.

June 15, 2026 · Doha

Designing with Intention: Vibe Coding

Learn to avoid shipping AI-built products in the wrong direction. This talk introduces a 5-question "Intention Brief" to ensure you're building what matters, preventing wasted effort.

Overview
Links
Tech stack
  • Replit
    Replit is the AI-powered, cloud-based development environment: go from natural language idea to deployed full-stack application in minutes, with zero setup.
    Replit is the definitive cloud-based development environment (CDE), enabling developers and teams to bypass complex local setup entirely. It supports hundreds of languages (e.g., Python, Node.js, C++) and features real-time, Google Docs-style collaboration for seamless pair programming. The core differentiator is the integrated Replit Agent: an AI developer that scaffolds, codes, and debugs full-stack applications from natural language prompts, accelerating the 'idea-to-app' cycle to minutes. Projects benefit from built-in version control (Git/GitHub integration) and one-click deployment to production, often leveraging Google Cloud infrastructure.
  • Cursor
    The AI-native code editor designed for high-velocity development through deep LLM integration.
    Cursor is a fork of VS Code that embeds AI directly into the development workflow while maintaining full extension compatibility. It leverages models like Claude 3.5 Sonnet and GPT-4o to power features such as Cmd+K for inline edits and Cmd+L for codebase-wide chat. By indexing local files, Cursor provides precise context for its predictive 'Tab' completions and multi-file 'Composer' mode. This setup allows engineers to move from high-level intent to functional code without leaving the editor or losing context.
  • PostHog
    PostHog is the all-in-one, open-source platform for product engineers: analyze, test, observe, and deploy features from a single stack.
    PostHog delivers a comprehensive developer platform, eliminating tool sprawl for product teams. It bundles critical tools like Product Analytics, Session Replay, Feature Flags, and A/B Testing into a single, cohesive system. Engineers gain a single source of truth for customer data, allowing them to debug code, ship features faster, and understand user behavior without complex integrations. The platform is open-source, offers a generous free tier, and is trusted by over 190,000 teams (as of 2024) for its transparent, usage-based pricing model.
  • Claude Code
    Anthropic's agentic coding tool: Unleash Claude's raw power directly in your terminal or IDE to turn complex, hours-long workflows into a single command.
    Claude Code is Anthropic’s powerful agentic coding assistant, designed for high-velocity development. It operates natively within your terminal, IDE (VS Code, JetBrains), or via a web interface, allowing you to delegate complex tasks like feature building, bug fixing, and codebase navigation. The agent plans, edits files, executes commands, and creates commits, maintaining awareness of your entire project structure. Internally, Anthropic engineers using Claude Code reported a 67% increase in productivity, demonstrating its capacity to deliver significant gains for Pro and Max plan users.
  • NotebookLM
    Google’s AI research assistant that grounds every response in your specific documents to eliminate hallucinations and provide cited insights.
    NotebookLM leverages Google’s Gemini 1.5 Pro model to transform private documents into interactive knowledge bases. Users upload up to 50 sources (PDFs, Google Docs, or URLs) per notebook to generate summaries, study guides, and deep-dive Audio Overviews. The system maintains strict source-grounding: every claim includes a direct citation to the original text. It handles 500,000 words per source, providing a high-capacity tool for researchers and professionals managing complex datasets without the risk of generic AI fabrications.