airesearchautomationtools
February 2026 Built

AI-Assisted Car Purchase

Used CarEdge, AI negotiation research, and a custom monitoring script to buy a new car — documented the entire process as a repeatable AI-assisted research and negotiation playbook.

The Problem

Buying a car is designed to disadvantage you. Dealer inventory is opaque, pricing is theatrical, and the negotiation process rewards people who’ve done it dozens of times over first-time buyers. The information asymmetry is the whole business model.

I decided to close the gap with AI.

The Approach

Phase 1: Market Research

  • Used CarEdge (caредge.com) to pull real dealer inventory data, market-value pricing, and days-on-lot statistics for target vehicles in a 200-mile radius
  • Fed that data into Claude to identify specific VINs where price-to-market-value spread suggested negotiating room
  • Built a monitoring script that scraped CarEdge daily and alerted when target vehicles appeared or prices dropped

Phase 2: Negotiation Prep

  • Claude synthesized a negotiation playbook based on the specific vehicle, dealer history, and market conditions
  • Prepared counter-offer sequences, out-the-door price calculations (including all dealer fees), and objection responses
  • Identified 3 comparable vehicles at competing dealers to use as leverage

Phase 3: The Purchase

  • Entered negotiations with printed CarEdge market data and specific VIN comparisons
  • Used the playbook sequence: start with the out-the-door number, not the monthly payment
  • Closed $3,200 below sticker without a trade-in

What Made It Work

The CarEdge “days on lot” metric was the secret weapon. A vehicle that’s been sitting for 60+ days costs the dealer ~$1,200/month in floor plan financing. That’s real leverage. Knowing a specific VIN had been there 73 days changed the entire dynamic of the conversation.

The monitoring script meant I wasn’t relying on memory or manual checking — I was notified the day a target vehicle hit 60 days on lot.

The Playbook

The full process is documented in a reusable template:

  1. Define target vehicle specs + acceptable color/option combinations
  2. Pull CarEdge market data for zip codes within radius
  3. Build VIN shortlist sorted by days-on-lot descending
  4. Research dealer history and incentive timing (end of month/quarter)
  5. Generate negotiation script with specific numbers and fallback positions
  6. Execute with printed data in hand

Total research time: 6 hours spread over 2 weeks. Outcome: $3,200 saved vs. asking price.

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