Showing posts with label ai. Show all posts
Showing posts with label ai. Show all posts

Thursday, November 05, 2026

VA Amendment Results: My Predictions Were Spot-On Backwards

Virginia had three constitutional amendments on this year's ballot: one protecting abortion rights, one removing the old same-sex marriage ban, and one restoring voting rights to people with felony convictions once they're released. I was pretty sure I knew how they'd go.

Here were my guesses. Felon voting rights would be a no-brainer: plenty of people know someone with a record, second chances appeal to both sides, and I assumed that, unlike abortion, it wasn't an issue that splits the country down the middle. Abortion, I figured, would squeak by or fail. There's a lot of red in Virginia. And marriage? It's 2026. Who's against that now?

All three passed. In exactly the opposite order.

Who crossed party lines

I wanted to know why, so I pulled the state's precinct-by-precinct results. Ballots are secret, so nobody knows how any one person voted. But Virginia has about 2,500 precincts, ranging from deep red to deep blue, and lining them up lets you estimate how each side voted. I used the Senate race as the marker: Mark Warner's voters stand in for Democrats, Bert Mizusawa's for Republicans.

About 1 in 10 Republicans voted yes on abortion. On marriage it was about 1 in 12. On felon voting rights it was about 1 in 42, almost none. And voting rights lost about 1 in 11 Democrats, nearly as many as marriage did.

So the amendment I thought would sail through drew almost no Republicans and still lost Democrats. The one I thought too divisive drew the most Republicans across.

A closer look

Then I added Census data. On the Democratic side, the marriage "no" vote climbs with the Black share of adults in the precinct: about 1 in 18 in precincts under 10% Black, about 1 in 4 in majority-Black precincts. Abortion's "no" rises too, though less, from about 1 in 37 to 1 in 11. The voting rights "no" barely moves, around 1 in 10 everywhere.

That's a fact about precincts, and only the three-quarters of them I could match to Census data. It can't tell me how any individual voted, or why.

On the Republican side, I split counties and cities by median household income. Where it's $80k or more, Republicans were about twice as likely to vote yes on abortion, and roughly three times as likely on marriage, as in the rest of the state. Voting rights stayed near zero in both.

Higher-income places also tend to be more suburban and college-educated, so income may just be standing in for those.

What I learned

People mostly voted with their party, as I'd expect. What I got wrong was which issues would pull people across. The one I was sure would divide people drew the most Republicans across. The ones that felt like settled common sense to me, second chances and marriage, weren't settled across party lines.

I figured where I live explained some of my blind spot, and partly it does. Here in Arlington, abortion and marriage each got about 81% yes, and voting rights got 75% (Election Day votes only; Arlington's early votes weren't in yet). That's far more than the roughly 55% it got statewide, but it still came in last. About 1 in 4 of my neighbors voted against the idea I'd have called a no-brainer.

Kathryn Schulz has a great TED talk, On Being Wrong, where she asks what it feels like to be wrong. Her answer: being wrong "doesn't feel like anything." She compares it to Wile E. Coyote after he's run off the cliff, before he looks down: "we're already wrong, we're already in trouble, but we feel like we're on solid ground." Then she corrects herself: it "feels like being right." That was me. I've been walking around sure that second chances were something nearly everyone around me agreed on. Analyzing these numbers was me looking down.

About the numbers

These are estimates, not counts, so treat them as rough. The marriage numbers are the shakiest: how Democrats voted on it varied a lot from precinct to precinct, which throws off the statewide estimate, and the real Republican crossover on marriage is probably lower than 1 in 12. Even taken at face value, it could plausibly be anywhere from about 1 in 9 to 1 in 18.

They're also based on unofficial results as of the evening of November 4, when about 50 of Virginia's 133 counties and cities still hadn't loaded their early votes. Where they had, Republican crossover ran a little higher, but the pattern was the same.

I built this with Claude and had other AI models try to poke holes in it, but the real check is the scripts below: they pull the state's data and reproduce every number here.

Monday, November 02, 2026

Leasing a Car in the Age of AI

This is a Just the Facts (JTF) post: generated by AI from my own raw material (voice memos, session notes) and a short outline I wrote, then checked by me. What's a JTF?

Shira's Acura RDX lease was winding down. We wanted to lease something that wasn't an Acura, and we wanted to get out of the Acura in the way that worked best for us. We ended up with a Hyundai Santa Fe. It was our first car deal in the age of agentic AI. Here's what helped, where the AI went wrong, and what actually got the deal done.

Huge Win: LeaseHackr's Rate Findr

  • Rate Findr on LeaseHackr is like X-ray vision for leasing. It shows the lease program numbers that dealers don't publish: money factor, residual and lease cash.
  • It isn't AI. It's reliable data that the AI can use. Without real numbers Claude guesses, and those guesses can get you in trouble.
  • Lease terms are set for the whole program, so they're the same at every dealer. In theory you could work out the lease deal by comparing offers from different dealers.
  • LeaseHackr makes that much simpler. Because you can see which lease programs are being offered, you don't have to depend on dealers. You can compare your leasing options ahead of time instead of trying to work them out on the fly.
  • Rate Findr also shows how each deal is put together. One model may have a lower interest rate. Another may have a higher rate but come with lease cash, which lowers the cap cost.
  • Access works a little oddly: you join the forum and make a monthly donation, which you can cancel anytime. That's a small price for what you get.
  • If you lease, you need this tool.

Where AI Helped

  • It taught me. None of the explanations of Money Factor or Capitalized Cost I found made sense to me. Claude patiently let me dig into these topics until I understood them.
  • It compared scenarios in seconds.
    • Which lease program was best? The 2026 or the 2027 Santa Fe? Gas or hybrid? A lower interest rate, or a higher rate with more lease cash?
    • Claude put all of this into one table I could actually compare.
    • Gas beat hybrid, because the hybrid's higher MSRP and smaller (or no) lease cash outweighed its better residual. The 2026 and 2027 gas models came out about even.
    • Claude's take on the Acura MDX deal was especially helpful. The low interest rate made it look like a no-brainer. But Claude factored in the MDX's low residual value and showed me that what looked like a great deal wasn't.
  • It mapped the market. Claude could go through sites like cars.com and quickly map the range of discounts on a make and model. That gave us a yardstick. Some dealers were selling at MSRP, and the good deals were around $3,500 off. So when a dealer beat that, we knew we had the winner.
  • It pushed back on ideas that seemed sensible to me but were dead ends:
    • Why not buy out the Acura and sell it to any dealer? Because then we'd pay sales tax on the buyout. It's better to stick with Acura or Honda dealers, who can buy the car straight from the lease so it isn't really a sale on our end. Honda also blocks third-party buyouts, so places like Carvana and CarMax couldn't buy it anyway.
    • Why not email every Acura and Honda dealer within 90 miles and take the best offer? Dealers don't reliably answer cold emails, many don't have a public email address, and I was way overcomplicating this. Call 3 nearby dealers and you're done.

Where the AI Failed Me

When it misread something, had incomplete information, or made a bad assumption, it gave me bad advice that sounded confident:

  • The CX-90 PHEV "giveaway." The AI was convinced Mazda was practically giving away the CX-90 PHEV. It wasn't. The AI had read two separate lease options, one with a low interest rate and one with lease cash, as one very generous deal.
  • The "inflated" cap cost. The AI was sure a dealer's quote had quietly inflated the cap cost. Not so. Claude had "forgotten" that Virginia makes you pay sales tax on the full car up front, and that tax is part of the cap cost. Once I had the real numbers, I could see how the dealer got there, and it was legitimate.
  • The ad that wasn't a lease offer. It saw an ad on a cars.com page and concluded the dealer was running a very low interest rate lease offer. The ad wasn't a lease offer, so everything the AI built on that assumption was wrong.

Taming AI

  • Keep asking. Say "I don't get it, let's discuss" until either (a) you understand it, or (b) the AI admits it was wrong all along.
  • Have it explain things back. Don't tell it what the lease says. Have it read the lease and tell you, then check that it sees what you see.
  • Build tools. I wrote leaseassist to pull lease deals from LeaseHackr and put them in a consistent format, so the AI didn't have to keep re-parsing them. The scraper behind it is ratefindr.js.

What Got It Done: Hustle

  • AI gave us the information to recognize a good deal.
  • Texting, calling and visiting dealers is what actually got the deal done.
  • Leasing the new car: We got a great price on a car in the wrong color. It was silver, and Shira wanted blue. Shira kept shopping until she found a dealer who had the color she wanted and would match the deal.
  • Selling the Acura: It took visits to more than one dealer. I eventually got a good offer, and then found another dealer who wanted the car badly enough to make an even better one. A Honda dealer bought our Acura lease, so the cross-brand buyout really does work.

Behind This Post

The outline I wrote
- The setup:
  - Shira's Acura RDX lease was winding down
  - We wanted to lease a new car that wasn't an Acura
  - We wanted to wind down the Acura in the most beneficial way possible
  - This is our first car purchase in the age of agentic AI
- Huge Win: LeaseHackr's Rate Findr
  - This is like X-Ray visions for Lease
  - This isn't AI, but it's reliable data the AI can use
  - Leasing terms are program wide, so in theory, you can derive lease
    deals by cross-checking dealer offfers
  - LeaseHackr dramatically simplifies this: by being able to see what
    lease programs are beign offered, you don't need to rely on
    dealers and pre-game different leasing options versus trying to
    figure them out on the fly.
  - If you lease, then you *need* this tool
- Where AI Helped
  - It was able educate me: no one description of Money Factor or
    Realized Captilized Costs made sense. But, Claude patiently let me
    explore these topics until I understood them.
  - AI could sift through various scenarios and determine
    which was the best in a few seconds.
    - Which was the best lease program? The 2026 or 2027 Santa Fe?
      What about Gas or Hybrid? What about a lower interest rate vs
      higher interesate rate and a bigger discount?
    - Claude could put a table in front of me normalizing this
    - The clarification on the Acura MDX deal was especially helpful:
      the low interest rate made it seem like a no-brainer. But,
      Claude factored in the low residual value and showed me how what
      looked like a great deal, wasn't.
  - AI could crawl through sites like cars.com and quickly map the
    range of discounts on a make and model. That gave us a yardstick:
    some dealers were selling at MSRP, the good deals were around
    $3,500 off. So when a dealer beat that, we knew we had the winner.
  - The AI could push back on ideas tht made sense to me, but were in
    fact, dead ends:
    - Why don't we buy our Acura and then sell it to any old dealer?
      Doing so causes you to pay sales tax; best to limit to Acura or
      Honda dealers, then it's not a real sale.
    - Why not email all dealers in the area within 90 miles to see who
      wants our car, then take the best offer? Dealers don't relaibly
      answer cold emails; many dealers don't have a public email; and
      you're way overcomplicating this. Call 3 nearby dealers and
      you're done.
- Where the AI failed me: with misread, incomplete or bad
  assumptionns, it gave me conflidently sounding bad advice:
  - The AI was convinced they were practically giving away the CX-90
    PHEV. Nope: it read two lease variations, the first with low
    interest rate, and the second with lease cash, as being one
    super generous deal.
  - The AI was certain a dealer's quote had sneakily inflated the Cap
    Cost. Nope, Claude 'forgot' that VA requires paying sales tax on
    the full car up front and that's part of the cap cost it hadn't
    considered.
  - It saw an ad on cars.com page and derived fromn there that the
    dealer was running a super-low interest rate lease offer. That
    wasn't a lease offer, so the assumptions that flowed from this
    were all wrong.
- Taming AI:
  - Keep asking: "I don't get, let's discuss" until either (a) you get
    it, or (b) the AI reveals it was wrong all along.
  - Build tools: I created `leaseassist` to pull back and normalize
    lease deals from leasehackr so the AI wouldn't need to keep
    re-parsing it.
- What got it done: Hustle
  - AI armed us with information to know what a good deal looked like
  - But, texting, talking and visiting dealers is what actually got
    the deal done
  - On the lease of the new car: we got a great price on the wrong color car. Shira
    shopped around until she found a dealer who had the color she
    wanted and matched the deal
  - On the sale of the Acura: it took taking it to multiple dealers, but
    ultimately, I got a good offer and then found another dealer who
    wanted the car so badly, that they gave me an even better offer