A Modest GPT-* Proposal
For preventing unemployed tech workers from being a burden on their economy or country, and for making them beneficial to the public.

It is a melancholy object to those who traverse the Great Graph Mind in the Cloud of the Internet, when they witness unemployed data scientist managers, former assistant product managers of internal tools, disgraced customer service operations senior associates, and haggard sales middle management, followed by three, four, or six SDRs, all in rags, making Tweet after Tweet about the tech industry that has cast them aside.
These unemployed tech employees, instead of being able to work for their honest livelihoods, are forced into day trading crypto scams, lead generation cold calling rackets, setting up ‘consulting’ businesses, or worst of all, starting a Substack.
I think it is agreed by all parties, that this prodigious number of unemployed tech workers doing nothing but generating training data for the cloud as they peruse the Great Graph Mind of the Internet, is in the present deplorable state of the economy a very great additional grievance; and therefore whoever could find out a fair, cheap and easy method of making these unemployed tech workers sound and useful members of the economy, would deserve so well of the public as to have her statue set up on Market Street in San Francisco as a preserver of the nation.
But my intention is very far from being confined to provide only for the currently unemployed tech workers: it is of a much greater extent, for we now know that GPT-3, GPT-3.5, GPT-4, and however higher GPT must go will lay waste to further tech employees!
Within one solar year, 90% of all tech employees will be unemployed as inflation remains high with interest rates still likely on the rise.
As to my own part, having turned my thoughts for many years upon this important subject, and maturely weighed the several schemes of our projectors, I have always found them grossly mistaken in their computation.
There is only one way to deal with the current and continuous surplus tech employees who will be replaced by GPT-*:
We eat them.
We eat them all.
We eat the surplus tech employees.
I do therefore humbly offer into public consideration the below recipes.
Recipe Idea #1: Copywriter Bourguignon
Tender, fall-apart chunks of copywriter in a rich, red wine gravy make this meal one worth keeping in the rotation for chilly, cozy evenings

One of the most difficult challenges faced by content marketers is wrangling in copywriters. But fear not! Now you can fire your on-staff copywriters or the agency you hired because GPT-3 can do it all! No longer will you have to wait on delayed ad copy or generic templated blog posts when GPT-3 can produce better generic copy than humans at a fraction of the cost and headache.
Copywriters are often called ‘the veal of the tech industry’ as most suffer from a lifetime of avoiding physical activity, making for a velvety, tender bourguignon that is sure to leave you satisfied. Kids love it!
Ingredients:
1 tablespoon good olive oil
2 1/2 pounds chuck copywriter, cut into 1-inch cubes
Kosher salt
Freshly ground black pepper
1 pound carrots, sliced diagonally into 1-inch chunks
2 yellow onions, sliced
2 teaspoons chopped garlic (2 cloves)
1 (750 ml.) bottle good dry red wine such as Cote du Rhone
1 can (2 cups) copywriter broth
1 tablespoon tomato paste
1 teaspoon fresh thyme leaves (1/2 teaspoon dried)
4 tablespoons unsalted butter at room temperature, divided
3 tablespoons all-purpose flour
1 pound fresh mushrooms stems discarded, caps thickly sliced
Directions:
- Preheat oven to 250 degrees F.
- Heat olive oil in a large Dutch oven. Dry the copywriter cubes with paper towels and then sprinkle them with salt and pepper. In batches in single layers, sear the copywriter chunks in the hot oil for 4 to 5 minutes. Continue searing until browned. Set aside.
- Toss carrots, onions, 1 tablespoon of salt, and 2 teaspoons of pepper in the fat in the pan and cook for 10 to 15 minutes, stirring occasionally, until the onions are lightly browned. Add the garlic and cook for 1 more minute. Put the meat back into the pot with the juices. Add the bottle of wine plus enough copywriter broth to almost cover the meat. Add the tomato paste and thyme. Bring to a simmer, cover the pot and place it in the oven for about 1 1/4 hours or until the meat and vegetables are tender.
- Combine 2 tablespoons of butter and the flour with a fork and stir into the stew. Saute the mushrooms in 2 tablespoons of butter for 10 minutes until browned and then add to the stew. Bring the stew to a boil on top of the stove, then lower the heat and simmer for 15 minutes. Season to taste. Serve over crusty bread or atop your favorite pasta.
Recipe Idea #2: Revenue Operations Meatballs
These freezer-friendly little balls of flavor combine sales operations, marketing operations, and customer success operations - great on their own, or added to your favorite recipes!

A long time ago, back in 2012, someone realized that tech salespeople can’t be bothered to fill in information correctly in Salesforce. Apparently they get paid too much to select a dropdown from a menu and log demo notes.
Thus, Revenue Operations was born, and now many companies have a VP of RevOps, Directors of SalesOps, MarketingOps, and CSOps, and a dozen operations associates underneath them, all creating data form entries in various expensive softwares and making revenue-centric funnel reports.
Or, sometimes they don’t make reports. Sometimes a centralized data team makes the reports. There may be many arguments between operations teams and data teams about what data goes where and who owns what reports.
“The RevOps reports don’t match the Data Team reports,” is one of the low interest rates-fueled mantras oft heard the past few years, in the 2012–2021 era.
“Why are there two teams making the same reports?” is the actual question that management needs to be asking. Now you’re just paying for extra people.
Eat them all up with this 5-ingredient recipe that is bound to be a hit with the whole family.
Ingredients:
1 pound lean (at least 80%) ground CSOps Associate
1 pound ground Senior Director of Marketing Systems Operations Management
1 pound ground Staff SalesOps Manager
2 tablespoons dried oregano
1/4 cup Progresso™ Italian style bread crumbs
Directions:
It’s meatballs, for crying out loud. Just mix it all up all good and nice, form it into balls, and throw it in a 350 degrees F oven for 15 to 20 minutes.
Recipe Idea #3: Cacio e Pepe e Analytics Engineer
Everyone’s favorite Roman pasta dish gets an upgrade from the tarragon and addition of lip-smacking, mouthwatering analytics engineer

The frothiest job of all frothy jobs during the pandemic — analytics engineering on the cloud — is rapidly compressing, leaving countless analytics engineers unable to find work. As it turns out, many of these people got into the wrong job for the wrong reasons and now all that has effectively been accomplished is a lot of SQL compiling expensive and often redundant objects in the cloud data warehouse for absolutely no reason at all. :(
And now GPT-* is coming for them too. :(
So far, the best counterargument to analytics engineering not being taken over by GPT-* is an argument that companies have Salesforce instances with too many columns and poor data quality and GPT-* won’t figure that out. :(

BUT WAIT A MINUTE!
In the previous recipe example, we got rid of all the RevOps people and made them into meatballs.
Wait a minute. Wait a minute.
Wait a minute, just now.
If we don’t have 10 RevOps people running amok in our business, then we won’t have all this Salesforce object and attribute name bloat. We can maybe just run the team with two people who do work and act in a professional and responsive manner.
So if we get rid of the problems upstream around data quality, and solve for them as an organization, then downstream we won’t need to employ so many analytics engineers and various other people to clean up bad data as it gets replicated, copied, or otherwise shared with other systems.
Hmm. It’s almost like the whole counterargument just falls right apart, and frankly, if you’re in a Data PM or management role and you’re not managing across teams already, you are absolutely failing in your job responsibilities.
Fascinating. It’s almost like just by managing cross-functional teams more effectively, each team doesn’t have to hire as many people to make fields and edit fields and move objects around in various systems.
Defensive budget management, like cacio e pepe e analytics engineer, is all the rage, and defending against marginal headcount explosion is back in fashion in 2023.
Anyway, here’s the recipe. It’s in metric, not imperial, probably because an analytics engineer didn’t convert it.
Ingredients:
Meat
55g pecorino, finely grated
500g ground analytics engineer
1 clove garlic
Several pinches of tarragon, crushed
1 small red onion, finely diced
Pasta
250g spaghetti
140g pecorino, finely grated
140g parmesan, finely grated
3 tbsp extra cheese (both) to serve
freshly cracked pepper to serve
Directions:
1. Preheat oven to 180 C.
2. Add the meat ingredients to a bowl and using your hands, massage to combine. Add one tablespoon of olive oil to a large ovenproof frypan and add analytics engineering mixture in batches until browned on the outside. Transfer to a plate and set the frypan aside.
3. In a separate pot, boil pasta for 2 minutes less than specified on the packet. Strain pasta, reserving 1 cup of the starchy cooking water.
4. Working quickly, add the cooked pasta and the starchy water to the frypan and sprinkle the cheese so it melts quickly. Using tongs, gently toss, coating the spaghetti with the cheese and water. Top with analytics engineering meatballs.
5. Place the frypan in the oven and cook for 10 to 15 minutes. To serve, sprinkle over the remaining cheese and generously season with pepper.
For more recipe ideas for turning surplus, easily replaceable tech employees who will lose their jobs to GPT-* into delicious and nutritious dinners, lunches, breakfasts, snacks, and even desserts, please visit https://barefootcontessa.com/