# How to Vibe Code Your Own Recall (and Stop Paying for It)

> Your AI Knowledge Base

- Site: https://recall.wiki
- Category: Productivity & Knowledge Management
- Verdict: **Solid side project** (62/100 vibecodeable)
- Estimated effort: 3-4 weeks of part-time development

## Verdict

Build a solid personal subset of Recall with a Next.js web app and browser extension, but expect friction when wiring robust background media ingestion pipelines.

Cloning Recall for personal use is an ambitious solid side project. While the core UI (Next.js, Tailwind CSS, a block editor, and a force graph component) can be spun up quickly with AI coding tools, the real engineering weight lies in asynchronous media processing. Ingesting, chunking, and transcribing multi-hour YouTube videos and large PDFs without timing out serverless functions requires dedicated background job runners like Trigger.dev and careful database design with pgvector in Neon. Furthermore, maintaining parity with their browser extension and local-first augmented browsing introduces significant extension manifest and CORS complexity.

### What you can't replicate

- The exact 500,000+ user community and organic acquisition loops
- Proprietary enterprise onboarding infrastructure and multi-year data history

## What it does

An AI-powered personal knowledge base and second brain application that saves, summarizes, organizes, and lets you chat with content from across the web, including YouTube videos, podcasts, PDFs, and personal notes.

### Core features

- One-click browser extension content saver for articles, YouTube videos, and PDFs
- Automated multi-media transcription and summarization with timestamps
- Vector embeddings and pgvector storage for semantic search and RAG
- Automated smart-tagging and concept entity extraction
- Interactive visual knowledge graph showing relationships between cards
- Multi-model AI chat (OpenAI, Anthropic, Gemini) with knowledge grounding
- Spaced repetition quiz generator and review schedule
- Notion-style block editor for personal notes

## The business

### Pricing

- Free: $0 — For personal note-taking
- Plus: $10/mo — For your lifelong AI knowledge base
- Max: $38/mo — For power users and complex workflows

### Funding

$1.5M raised.
- Pre-Seed / Seed
Investors: Jason Calacanis / LAUNCH Accelerator, Splash Capital, Blockchain Founders Capital, Rocket Capital

Founded 2022.
Team size: 3 core founders.

## The hard parts

- Robust background ingestion queues that can fetch, parse, and transcribe massive inputs (such as 10-hour YouTube videos or 300-page PDFs) without hitting API limits
- Automated concept extraction and graph linkage pipeline that maps semantic relationships between unstructured notes and media sources
- Local-first augmented browsing architecture that safely resurfaces relevant past knowledge as you browse the open web
- Multi-model provider orchestration allowing seamless context switching across diverse LLM APIs

## How to vibe code Recall

### Prerequisites

- Node.js (free): Required runtime for Next.js development and package management
- GitHub (free): Repository hosting and continuous deployment integration
- OpenAI / Anthropic API Keys (pay-as-you-go): Provides LLM reasoning, embeddings, and transcription models for processing saved content

### Recommended AI tools

- Claude Code: Best-in-class terminal agent for scaffolding complex full-stack apps and managing multi-file Next.js architectures
- Cursor: Essential AI code editor for fine-tuning UI components, graph visualizations, and editor views

### Stack

- Frontend: Next.js with Tailwind CSS and shadcn/ui
- Backend: Next.js Server Actions and API Routes with Trigger.dev for background jobs
- Database: Neon (Serverless Postgres with pgvector)
- Auth: better-auth
- Payments: none
- Other: Vercel AI SDK, Firecrawl

### Hosting

- Vercel (Hosting the Next.js frontend and serverless API functions): $0-20/mo
- Neon (Managed serverless Postgres database with vector support): $0/mo (free tier)

### Build guide

1. **Project Scaffolding & Database Schema** — Initialize the Next.js repository with Tailwind CSS, shadcn/ui, and better-auth connected to a Neon Postgres database configured with pgvector.

```
Scrape or set up a fresh Next.js project using App Router, Tailwind CSS, and TypeScript. Configure better-auth for single-user authentication with email/password. Connect the app to a Neon Postgres database using Drizzle ORM or Prisma. Create database tables for users, recall_cards (storing title, url, raw_content, summary, content_type, and embedding vector via pgvector), tags, and card_relations. Ensure the migration files are properly structured and test the local development server starts without errors.
```

2. **Content Ingestion & Scraping Pipeline** — Build backend extraction endpoints that take URLs, PDFs, or YouTube links, extract text using Firecrawl or platform APIs, and store raw content.

```
Build a robust API route in Next.js that accepts a URL or uploaded file (PDF, text note). Integrate Firecrawl API for web page scraping and use OpenAI Whisper or direct text extraction for PDFs and YouTube transcripts. Implement error handling for rate limits, payload size limits, and invalid URLs. Save the extracted clean text into the recall_cards table in Neon with a status of 'pending_summary'.
```

3. **AI Summarization & Smart Tagging Engine** — Implement background processing tasks that generate structured summaries, timestamped notes, and smart tags using the Vercel AI SDK.

```
Implement an asynchronous background processing function using Trigger.dev or a serverless queue that picks up newly saved recall_cards. Using the Vercel AI SDK and Anthropic Claude or OpenAI models, generate a structured JSON object containing a concise summary, timestamped key points, and smart tags. Compute text embeddings for the summary using OpenAI's embedding model and store them in the pgvector column. Update the card status to 'completed'.
```

4. **Knowledge Graph & Visual Connections** — Create an interactive knowledge graph visualization using D3.js or React Flow that links related cards based on vector similarity and shared tags.

```
Build a dedicated /graph page in the Next.js app featuring an interactive graph visualization using React Flow or D3.js. Query the database for recall_cards and their semantic relationships, calculated via vector distance in pgvector or shared smart tags. Render nodes representing cards and edges representing relationships, allowing users to click a node to view its summary and connected notes.
```

5. **Multi-Model AI Chat & Search Interface** — Build the central chat interface that retrieves relevant saved cards via vector search and allows querying across user knowledge or the open web.

```
Create a chat interface component using the Vercel AI SDK useChat hook. Implement a retrieval-augmented generation (RAG) backend query that searches the user's saved recall_cards using pgvector cosine similarity against the user's prompt. Allow users to select their preferred AI model (OpenAI, Anthropic, Gemini) from a dropdown switcher. Ensure chat responses cite specific saved Recall Cards as sources.
```

6. **Spaced Repetition Quizzes & Polish** — Add an active recall quiz generator that creates flashcards from saved summaries and schedules reviews using a spaced repetition algorithm.

```
Implement a spaced repetition review module. Create a backend action that prompts an LLM to generate 3-5 multiple-choice and short-answer quiz questions from a selected Recall Card summary. Store these in a quizzes table with review intervals and scheduling metadata. Build a review dashboard frontend that presents due cards, records user recall performance, and adjusts the next review timestamp accordingly.
```

### Cost vs paying

**Starting costs (one-time):**

- Domain name (optional): $12 one-time
- AI coding tool subscription: $20 one-time
- Total: ~$32 one-time

**Ongoing costs (monthly):**

- Vercel Hobby / Neon Postgres: $0/mo
- OpenAI / Anthropic API usage for summaries & chat: ~$5-15/mo
- Total: ~$5-15/mo

- Paying for the SaaS instead: $10/mo (Plus) or $38/mo (Max)
- Build time: 30-40 hours
- AI tool credits: $20 one-time (Claude Pro / Cursor)
- Break-even: N/A (Built for personal use and learning)

## Sources

- [Recall Website - Home](https://recall.wiki)
- [Recall Pricing Page](https://recall.wiki/pricing)
- [Recall About & FAQ](https://recall.wiki/about)