AI Bookkeeping for Freelancers

AI Prompts to Build This

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1. 1. Project Setup

   Build the weekend MVP of "AI Bookkeeping for Freelancers": connect a bank, auto-categorize the transactions, and read your month in plain English.
   
   Stack: Next.js (App Router), TypeScript, Tailwind, Supabase (Postgres, Row Level Security, Auth with Google sign-in), Plaid for the bank link, Claude (Anthropic API) for the categories and the summary. Deploy on Vercel.
   
   Tables (Row Level Security on, each user reads only their own rows):
   - connections(id, user_id, plaid_item_id, access_token_encrypted)
   - categories(id, user_id, name)
   - transactions(id, user_id, connection_id, plaid_transaction_id, posted_on, merchant, amount_cents, category_id, confidence)
   - rules(id, user_id, merchant, category_id)
   
   Screens: /login, /connect, /dashboard (income, expenses, profit, uncategorized queue).
   Env vars (names only): NEXT_PUBLIC_SUPABASE_URL, NEXT_PUBLIC_SUPABASE_ANON_KEY, SUPABASE_SERVICE_ROLE_KEY (server only), PLAID_CLIENT_ID, PLAID_SECRET, PLAID_ENV, ANTHROPIC_API_KEY.
   Plaid access tokens stay on the server and are never sent to the browser.
   
   Do not build: billing or plans, Stripe or PayPal connections, quarterly tax estimates, Schedule C export, an accountant share link, multi-factor sign-in.
   Done when: npm run dev starts, you can sign in with Google, and the four tables exist with Row Level Security on.

2. 2. Core Feature

   Build the one feature that proves the idea: categorize every transaction and explain the month.
   1. After the Plaid link, pull the last 24 months of transactions and store them. Validate the Plaid webhook signature.
   2. For each new batch, apply the user's rule for the merchant if one exists. Otherwise send the batch to Claude with the user's category list and earlier corrections, and ask for a category and a confidence for each transaction.
   3. Auto-apply high-confidence results and send low-confidence ones to the uncategorized queue.
   4. When the user corrects a category, save it as a per-merchant rule so the next batch skips the model.
   5. Write a monthly summary in plain English: total income, top expense categories, profit and three likely missed deductions. No accounting jargon.
   Rules: use server components for the transaction tables.
   Empty state: with no connection, show the connect-your-bank button and one sentence on what happens next.
   Done when: a sandbox bank account fills the dashboard, correcting one transaction creates a rule, and the month's summary names three possible deductions.

3. 3. Landing Page

   Build a one-page landing site for AI Bookkeeping for Freelancers.
   Hero: "Your books, done. In plain English." Sub: "Connect a bank. Get your profit this month, what you will likely owe, and three deductions you forgot." One button: Join the waitlist.
   Sections: the problem (no chart of accounts, no journal entries, just the answer), how it works in four steps (connect, categorize, review in plain English, export), a sample monthly summary, and an FAQ on bank security and accuracy.
   Waitlist: store the email in a waitlist table in Supabase. No other service.
   Voice: friendly, plain and unafraid of money.
   Done when: the page renders on a phone and a submitted email appears in the waitlist table.

4. 4. Branding Package

   Use a design or image tool for this one. A coding agent cannot draw a logo.
   Brand for AI Bookkeeping for Freelancers: a wordmark and an icon that feel calm and trustworthy with money.
   Colors: a deep green, a warm off-white and one amber accent. Type: one friendly sans for the interface and tabular figures for amounts.
   Deliverables: wordmark, icon, a sample monthly-summary card, and one launch graphic.
   Done when: each deliverable is saved in one folder and the amounts line up in a column.