Day: October 15, 2025

• When I found out Ina Garten had a penne pasta with five different cheeses, I knew I had to try it. 
• The dish combines Gorgonzola, fontina, mozzarella, Romano, and ricotta. 
• Garten’s pasta is rich without being too heavy, making it perfect for fall and winter nights.

As temperatures start to dip and we settle back into our favorite sweaters, it’s time to whip up some comforting dinners. 

And no chef soothes me more than Ina Garten and her delicious pasta recipes. 

So, when I discovered that the “Barefoot Contessa” star has a penne with five different cheeses, I knew I had to try it. 

Ina Garten’s penne pasta requires five different cheeses.

To whip up her five-cheese penne, you’ll need: 

• 1/2 cup freshly-grated pecorino Romano 
• 1/2 cup shredded Italian fontina 
• 1/4 cup crumbled Italian Gorgonzola 
• 1/4 pound fresh mozzarella, sliced
• 2 tablespoons ricotta cheese

I must admit that I purchased Romano cheese instead of pecorino Romano, which I couldn’t find in my local supermarket’s small fromagerie, no matter how hard I tried.

I did a quick Google search — “Is pecorino the same as Romano?” — and was convinced that they were basically identical. I later learned that the Romano I had purchased was actually made with cow’s milk, while pecorino Romano is always made with sheep’s milk.

But alas, they’re both still in the same family and known for their sharp flavors, so I think the cheese gods will forgive me on this one. 

Garten’s five-cheese penne also requires four additional ingredients.

On top of all that cheese, you’ll need: 

• 1 pound penne rigate pasta
• 2 cups heavy cream
• 1 cup crushed tomatoes in thick tomato puree
• 6 fresh basil leaves, chopped

I preheated my oven to 500°F and started grating and measuring my cheeses.

This is the only part of Garten’s recipe that actually requires a little work.

I hadn’t bought pre-shredded fontina or pre-crumbled Gorgonzola, so I decided to just grate them as well. And let me tell you, it was definitely an arm workout.

Next time, I’ll likely just finely chop the fontina instead, as its creamy texture made it a tad trickier to work with the grater. 

I couldn’t help but admire all the beautiful cheeses in my mixing bowl.

From the creamy ricotta to the sharp Romano, I was excited to see how these different flavors and textures would blend together. 

After I finally stopped staring at my cheese, I added the crushed tomatoes and heavy cream.

I also chopped up some basil to throw on top.

And just before I mixed everything together, I started cooking my pasta.

Per Garten’s recipe, you’re not actually supposed to fully cook the pasta. You just need to parboil the penne for four minutes in a pot of salted water. 

After I dumped my pound of pasta into the pot, I set a timer and went back to my bowl of cheese. 

As I mixed the cheesy sauce, I watched as it turned into a surprising shade of millennial pink.

Who knew Garten’s pasta would be so on-trend? The color was actually quite pretty, and not at all what I had expected. 

After draining my noodles, I put them back into the same pot and added my cheesy pink mixture.

Garten recommends dividing your pasta into “shallow ceramic gratin dishes,” but I realized this dish could easily turn into a one-pot recipe, and who doesn’t love dealing with fewer dishes?

So I tossed the penne with the mixture, ensuring all the noodles were submerged in the vibrant pink pool of cheese.  

And just before popping my pasta in the oven, I added some butter.

As much as I love Garten, I have to admit that I went against her recipe on this last step. The “Barefoot Contessa” star recommends using half a stick (four tablespoons) of unsalted butter to dot your penne pasta with, which, to be honest, sounded very overwhelming. 

My friend Molly, who is far more experienced in the kitchen than I am, confirmed that half a stick of butter would be too much — especially paired with all that cheese.

So, I decided to reduce the recipe to just one tablespoon, using a knife to shave off small knobs of butter that I sprinkled directly on top of the pot.

It took less than 20 minutes to bake the pasta.

Garten’s recipe recommends cooking the pasta until it’s “bubbly and brown” on top, which she estimates will take around 7 to 10 minutes.

As I waited for the pasta to cook, the delicious smell of cheese filled the kitchen completely. And, as the minutes ticked by, I could hear the penne start to bubble.

Of course, every oven is different. Overall, it took my pasta about 17 minutes to bake in total. I waited until I could see that the penne in the center of my pan was turning brown before I took it out, ensuring it had cooked through.

The pasta came out looking glorious.

The millennial pink turned into a beautiful, almost golden color, and there appeared to be an even crust on the top of the pasta. 

The chunks of mozzarella that had floated to the top made the dish look even more inviting.

And it tasted so good, we went back for seconds.

As much as I love very saucy pastas, I did wonder if five different cheeses — plus plenty of butter and cream — would be too much. I worried that the dish might taste more like cheese with a side of pasta, rather than the other way around, but my fears were unfounded.

Garten’s penne manages to be rich and soothing, without feeling too heavy on the stomach. 

“All that cheese,” my friend Molly happily exclaimed as she took her first few bites. “It tastes like a warm blanket.” 

Molly recommended sprinkling some red pepper flakes on top to cut the richness of the pasta, which turned out to be a great addition.

“But the cheese isn’t overwhelming,” added my friend Joe, who was also on taste-test duty. 

And personally, I loved the texture contrast between the crusty pieces and the gooey cheeses, which had sunk inside the penne and would burst with every bite.

Garten’s five-cheese penne is a must-have dish for the fall and winter seasons.

Garten’s five-cheese penne has the power of a warm blanket, roaring fireplace, and mug of hot cocoa — all wrapped up in one cheesy bowl. 

• Sidhant Bendre cofounded an AI company that initially operated with four to six people.
• The company prioritizes using AI to minimize head count and keep the company small.
• When hiring, he scrutinizes whether a person can leverage AI and go from specialist to generalist.

This as-told-to essay is based on a conversation with Sidhant Bendre, a 25-year-old cofounder of an AI-driven consumer software portfolio company based in New York. His company, Oleve, prioritizes using AI to stay lean while scaling with minimal staff and has also been recognized by OpenAI for processing an immense volume of text data through its models. His words have been edited for length and clarity.

I don’t know what it’s like to build a company without AI involved, and that impacts how my cofounders and I have always hired.

We started the first version of our company out of college in January 2023. The next year, we officially founded Oleve, an AI-driven consumer software portfolio across various app categories.

Right before then, there were only four of us, and we haven’t expanded much beyond that. We’ve been able to leverage AI tools, but staying tiny requires operating principles that actively resist the default path to add head count.

With AI, I can learn just enough operating knowledge about anything I need, which has allowed our small group to move faster. It’s also the reason we put extra scrutiny on hiring. Most companies reward people for becoming experts who are irreplaceable in their function. Tiny teams reward the opposite: people who master something fast enough to systematize it and move on.

We’ve only ever built with AI, so the ability to leverage it is necessary for a new hire

When we launched this company in college, we were already utilizing AI ourselves, so we had a clear understanding of its limits going into the business. As a result, we don’t have many issues with relying on it in our workflow.

If someone can’t leverage AI effectively, it could be a problem because we’ve built a lot of our systems around it. We have a template code base that we reuse for different products, and it’s built in a way that allows us to clone it for an individual product. We also use AI in our marketing, analytics, and hiring processes.

Hiring comes down to whether the job candidate is leveraging AI in the right way and with the right mindset about its limits.

My biggest piece of advice for people who want to join a tiny team

I tell people to learn to think operationally, not just in terms of execution. There are a few mistakes with leveraging AI that can immediately disqualify someone from a tiny team. One is treating it like a replacement.

Treating AI as a replacement for thinking rather than a tool for leverage is a big mistake. We want candidates to use AI, but we’ve seen take-home tasks where someone clearly just fed a prompt into ChatGPT and submitted whatever came back without critical thought.

On tiny teams, carelessness doesn’t just mean one bad deliverable — it means building bad systems that compound. There’s no middle management layer to catch sloppiness, and there’s no room for people who aren’t thinking about how their work affects what comes next.

AI can generate the first draft, but it can’t tell you if it’s the right draft. It can explain how code works, but it can’t tell you if it’s well-architected for your specific needs. It can create options, but it can’t evaluate which option actually solves your problem.

The right way to leverage AI is to use it to accelerate learning and execution so you can focus on higher-level thinking and decision-making.

We are recruiting with way more scrutiny on engineering, and we only hire specialists

Any decent engineer can now do a lot more than before with AI.

Results don’t necessarily mean skill anymore. We’ve had to create more involved engineering recruitment processes because we need to vet potential employees more closely. It’s a skill to use AI to fully drive results, but that can be temporary when issues arise with pushing out a complex product and someone lacks the deeper knowledge needed.

This is why I prefer hiring specialists and utilizing AI to turn them into generalists. If there’s a system for a product that we need help with, we identify the critical pieces of the product. Then, I hire someone who’s a really good specialist in that area, and we know we can train them to expand their work to other platforms and products with AI.

For example, I have an engineer who was purely a backend engineer, but is now working on a front-end project as well. Much of this is possible because he can leverage AI to learn on the fly, even though I hired him for this very specific skill set that was needed for a high-priority backend project.

There are new lean startup principles with tiny teams

I presented at an AI engineering conference earlier this year, where they launched a tiny teams track. My talk was based on what we’ve learned and developed as the new principles of lean startups using AI at Oleve.

Startups can begin building toward a world where people can command clusters of agents to perform tasks on their behalf. At the most basic level, everyone is now their own chief of staff.

Doing this is something that’s very achievable.

Do you work on a tiny team and want to share your story? Email this reporter at aapplegate@businessinsider.com.