Google's Spirit Airlines Bid: Work Data for AI Training

Nate B. Jones (0:00)

Google has more data than almost anyone on Earth. So why does Google need to bid $10 million for Spirit Airlines' old work emails? Because of what it thinks your job is made of. How much is the work that you do worth? If a deal like the Spirit Airlines deal goes through, the company selling the records gets paid, a broker definitely is going to earn a fee there. The buyer, Google, is hoping to build an agentic capability that it can resell, and the person whose work helped create all of that, what do they get? They don't get a seat at the table. It turns out that companies are paying millions and millions and millions of dollars for records of work going back years and years and years and years. And the reason why is that there is a leading theory among AI labs that if they get these records of work, Slack messages, Zoom call transcripts, documents, that they will be able to teach AI to do what you and I do, to do knowledge work. That's the idea at least. I think there's some reason for skepticism, and I think if nothing else, it's worth you and I knowing about it so that we can understand the value of our work, the value we are putting in, and the value of the data that we're putting out. Why does this matter, by the way? Because when we started the year in 2026, what we mostly talked about was what I call verifiable work. If the code runs, it's good. If it runs and it works, that's great, and that's a verifiable domain, and we're done. It's like a light switch. It's on or it's off. It works or it doesn't. Well, now we're talking about less verifiable domains. How do you know the document you wrote is good? Can you prove it? Is it a particular sentence that made it good? Is it something you changed in V5 versus V4, or V37 versus V36?

You know, I did get up into those numbers when I was writing PRDs in Amazon. They do get that high. How do you know it's good? What makes it good? What makes it true knowledge work? That's the kind of thing that we need to get a better read on, because really, a lot of the value that we humans produce is not well captured by the kinds of data that these labs are purchasing. Now think about your own job. How much of the record explains where you created value? How much records the effort it took to find the right information, to get permission, to schedule the meeting, and then schedule the follow-up to the meeting? Someone buying that history has to decide which parts the machine ought to learn. And that decision is going to matter to your job and to my job, and you and I may not have a lot of say in it. What is the work that matters? That's the question that is underneath this whole market that matters for you and me for the next decade. If you spent the afternoon in Slack getting an invoice fixed, did the work consist of those messages? Was it finding the mistake? Was it getting somebody with the authority to correct it to actually do the thing? And what is the record worth to the buyer if the agent can't tell the difference?

This is a fight over what we do and how what we do counts. The answer affects what a machine learns, what a buyer will pay, and whether your employer thinks it can replace you, or whether it buys a convincing performance of your job and leaves you to deal with everything the agent misses, which I've also seen stories of. Imagine an invoice that doesn't match a purchase order and someone needs to resolve it before the month closes. The invoice is in system A over here, the purchase order is in system B over here, a supplier is emailing a credit somewhere, but the reviewer wasn't copied, and somewhere in all of that mess, there's a disagreement about whether a partial delivery counts as complete. This is a very realistic scenario. If you've ever dealt with invoicing, it's a complete mess.

If you know this company, you may remember that the supplier combines two shipments on one invoice, or that an exception approved last month would be a mistake this month. Like if you are in the invoicing world and you know the customer, right? The business needs to get all of that squared away, and depends on your tribal knowledge to understand that, and depends on you to authorize any correction, etc.

The messages you produce in the act of cleaning that up matter to the extent that they help make those things happen, but they're not the work, are they? They don't get money in the door. The record of this job would also maybe contain some of the effort that it would take in getting the organization to let the work happen, but again, they're not the work. Maybe someone needs a status update on the invoicing, but it's not the work. Maybe a meeting happened because two systems didn't agree, but that's not the work either. Now, some of that coordination was necessary. Some of it was the cost of working inside that particular company. And if you've never had beers after work and argued about your company, you probably haven't had the knowledge work experience. I'm just going to tell you, happy hour and complaining is how white collar workers talk about where work matters. And so what we're really talking about here is the difference between work and the performance of work. How do you demonstrate availability, show involvement, make sure your contribution is visible? Those are things we talk about in big companies for our careers, but they're not the same thing as work. And the archives that are for sale capture all of that. A message that prevents a costly mistake and a message that says you're following up will sit right next to each other and the agent is going to read both. Suppose the invoice took 30 messages and three meetings to resolve. That sounds very plausible. The valuable intervention was one person noticing that the credit hadn't been correctly applied, somewhere in that mess. If a buyer treats the whole sequence of data as examples of competent accounting, what is the agent supposed to learn here? How does the agent know what matters? How does the agent learn anything except the performance of work? There's another problem. The thread might end with somebody saying the invoice is approved and the ticket might close and that looks like success to the agent, but perhaps a duplicate payment was discovered six weeks later. And if you think I'm being theoretical, you have not worked enough in companies that have real messes. Every single example I am giving you is something that is lightly anonymized that I have lived through. This is a case where we are underestimating the degree to which data is reflecting the real mess of the company. And I know that buyers are hoping to extract a lot from network archives that is valuable. In the August auction, Google made the winning $10 million bid over Mercore that bid $7.5. There's going to be a hearing on the proposed sale, so it's not gone through yet. That's slated for the 14th of October. And then someone has to figure out, what are we going to teach an agent from a failed airline?