• Pinterest's VP of product management said mixing open-source and closed-source AI models helped cut costs.
• The social platform's recent AI-enabled features combine OpenAI, Alibaba, and its own AI models.
• To support this approach, Pinterest invested in cloud infrastructure and an updated hiring strategy.

In its pursuit of creating AI-supported tools for its users and advertisers, Pinterest leaders said it is actually shrinking part of its AI budget.

As companies continue to spend on AI, they face pressure from investors to show returns on investment from this fast-evolving technology. One way to do that: Stretch investments by shrinking the budget needed for the systems that power AI features.

Pinterest, the visual-first social media platform where users can save images to curate their ideas, is taking what it calls a "model-agnostic" approach to generative AI, said Vicky Gkiza, the company's vice president of product management. The strategy started in 2023 and involves combining Pinterest's proprietary AI models, developed by the company's software engineers, its closed-source models from Anthropic and OpenAI, and open-source models from Alibaba, said Gkiza.

While closed-source AI models can quickly process large amounts of data, require little maintenance, and integrate instantly into a company's existing systems due to their pre-built nature, they're typically more expensive. Open-source models, meanwhile, are typically free to download, use publicly available data, and can be modified more deeply than closed-source offerings. However, they also require the expertise of software engineers who can build, maintain, and debug these highly customizable models.

Lan Guan, the chief AI and data officer at Accenture, said companies are increasingly seeing value in a multimodal AI approach that balances performance and the cost of tokens, or the units of text AI models process. "This token cost is going to slow you down if you don't start managing them proactively," Guan told Business Insider. "Open-source will be a really good option."

Gkiza walked Business Insider through how Pinterest bolstered its blended approach to generative AI through beta testing, an updated hiring strategy focused on software development expertise, and infrastructure investments.

The tech

Pinterest uses OpenAI's closed-source large language models to support some of its product features and relies on Anthropic's Claude, another closed-source AI, for internal use cases like coding, a company spokesperson told Business Insider. Alibaba's Qwen, an open-source LLM, is used for visual and content understanding, data labeling, and assistant tasks.

With this approach, the company rolled out several new AI features in 2025, each blending open-source and closed-source generative AI, said Gkiza.

Auto-collages, a feature where advertisers can convert their product catalogs into pins that populate on shopping feeds for categories like skincare, home decor, and fashion. Pinterest began testing auto-collages at the beginning of 2024, when software engineers fine-tuned a mix of internally developed, open-source, and third-party AI models. By June 2025, auto-collages was ready for a pilot, which included a small group of retailer-advertisers like Macy's.

Then, Pinterest's voice-enabled AI feature, which uses both open-source and third-party AI to generate responses to users' queries, underwent beta testing in October 2025. Early results showed that users tended to pose more shopping-specific questions when they could ask aloud rather than typing their searches, said a Pinterest spokesperson.

"Search has been evolving so fast. It was imperative for us to use AI to improve," Gkiza told Business Insider.

The talent

To advance its new AI-enabled features and execute its blended-model approach, Pinterest also hired employees with AI and machine learning expertise to steward the customization of its large language models, said Gkiza. Former Google engineer Matthias Zenger joined the company as its vice president of engineering in April 2025. Three months later, in August, Pinterest announced it had hired software engineer Mirjam Wattenhofer to focus on e-commerce and user experiences, and that it would open an Engineering Excellence Hub in Zurich.

Both Zenger and Wattenhofer work at the Zurich office, where a team focuses on improving user experiences with AI and machine-learning technologies. In February, Pinterest CEO Bill Ready said the company would hire additional research and development workers to support the company's AI efforts.

"We are investing more in hiring the right talent — evolving the team, whether it is engineering or product management — to be much more familiar with AI," Gkiza said.

The outcome

Gkiza said the company's blended approach to AI-driven experiences costs an estimated 90% less than when Pinterest relied solely on its proprietary models, a milestone the company touted during its February 2026 fourth-quarter earnings presentation.

With its growing use of open-source AI models, the company plans to invest more in cloud-computing infrastructure, like graphics processing units, which are needed to power the cost-saving technology, Gkiza said.

Pinterest said it will continue to experiment with various AI models, prioritizing its own models for personalization, open-source models for cost-effectiveness and multimodal machine learning, and closed-source models when they still offer the best performance.

• I asked ChatGPT to identify the unnamed male celebrity who allegedly tried to sext Lena Dunham in 2012.
• It told me it was Don Rickles, which I feel pretty certain is not correct.
• So what are we doing here, folks? Learning to use AI?

Did you hear about the time Don Rickles tried to chat up Lena Dunham in the middle of the night?

No? Let me explain. First, we need to talk about Reese Witherspoon.

See, I'm a simple woman. I have only two interests: tech news and celebrity gossip. So I was naturally intrigued by a recent online fuss over Reese Witherspoon's admonition for women to learn to use AI. It sparked so much backlash that she had to issue a follow-up explanation.

I've also been intrigued by Lena Dunham's new book. (They're related — sort of. Keep reading!)

I think Reese is generally right about AI — she's saying the same thing that every other business leader is saying. But her comments did make me think a little more about what "Learn to use AI" even means. Writing emails with ChatGPT? Understanding the technology behind different models? Vibe coding? What level of "using AI" is expected here to stave off falling behind in the workforce and life in general?

One area I've really leaned into is using ChatGPT as a sort of super Google — to find something I know is online but would take some effort to dig up with a normal search engine.

A recent example? It's related to — of course — celebrity gossip.

I was reading Dunham's new memoir, "Famesick," which is full of moderately juicy celebrity gossip about named people and also blind items — celebrity gossip that gives a few clues about the identity of the person without naming them, a fun little riddle for the readers to solve.

One blind item is about an unnamed male celebrity who — allegedly — sent Lena a flirty late-night text message after meeting her backstage while taping "The View" in 2012. I figured I could solve this blind item by finding out who the other guest was on the same episode — information that should be online somewhere, but would take me forever to find.

So I asked ChatGPT to identify the male guest on "The View" episode that Lena was also on that year. At first, ChatGPT told me that it was only the four female cast members from the show. When I asked again who the other male guest was, the suggestions were Chris Evans and Chris Hemsworth. (Not so. They appeared on a separate episode that same year, according to IMDb.)

That time Don Rickles chatted up Lena Dunham

When I said, "No, a comedian," as Dunham had described the man, ChatGPT confidently provided a new answer: It was legendary comedian Don Rickles who'd texted Dunham after the show.

I laughed out loud because of all the possibilities of who sent a late-night "u up?" text, I feel fairly certain it was not Don Rickles, who would've been 85 years old at the time.

Dunham's description of the man: "a bit of an American Hugh Grant, famous for that sort of chattery charm and his ability to woo his onscreen paramours with his fast-talking, hand-flapping anxiety. Ostensibly a comedian, he was there to promote his Gothic-tinted movie, where he had made a dramatic turn." Doesn't exactly sound like a Borscht Belt insult comic Don Rickles to me.

After spending way too much time searching the internet for answers on this — the old-fashioned way — I can make some guesses about how and why ChatGPT was so wrong here. IMDb's episode guide for episodes of "The View" from 2012 is spotty, with entries for some episodes missing information about guests, and no accessible video clips online. The only proof I found that Lena Dunham ever appeared on "The View" on April 20, 2012, was a Vulture blog post from that day, complete with an embedded YouTube clip that has been marked private.

Knowing this, I can start to see how AI got confused: When there's a lack of information, AI sometimes blurs together what it can find to try to spit out a plausible answer. Chris Evans and Chris Hemsworth appeared on the May 4, 2012, episode of "The View," and Dunham and Rickles appeared together on an episode in 2016.

ChatGPT doing this kind of thing — basically, taking a guess at what you might want to hear — could be useful if you're trying to write an email to a friend, maybe? It's not useful, obviously, if you're looking for a specific fact and it just plain makes something up.

For the record: Neither Lena nor Don (who died in 2017) nor the National Comedy Center, which is the keeper of the Rickles archive, responded to my requests for comment.

Are we stuck in a pizza glue loop?

Look, I get it. It's not particularly exciting to point out that ChatGPT gets things wrong in the spring of 2026. We know this, or at least we all should know this. Still, I keep coming across so many obvious mistakes when asking AI for factual things. These are the glaring mistakes I catch when I know that what AI has generated is not the right answer.

But what about the mistakes that I don't catch — or don't even know to catch? Things that I blindly accept as fact? For work-related stuff, I'll always double-check, but in those cases, am I actually saving myself any time?

How soon will this improve? Will we be stuck in a pizza glue loop forever? Is this what's going to make a bunch of lawyers and tax CPAs lose their jobs? I mean, OK, sure.

Here's where Witherspoon's and other bosses' idea of "Learn to use AI!" feels frustrating. I feel fairly confident about using various AI tools and have a decent concept of how they work. I am a woman, and I have learned to use AI! And yet, here I am, still unsatisfied.

There's a gap between what Reese Witherspoon wants for me and what I want out of AI — and the wholesome image of comedy legend Don Rickles. For now, those things just aren't lining up right.

• A version of this story originally appeared in the BI Tech Memo newsletter.
• Sign up for the weekly BI Tech Memo newsletter here.

A few Fridays ago, I was feeling smug. I'd just sent another Tech Memo edition telling subscribers to stop worrying about AI eating tech jobs because Anthropic, the leading AI company pushing this narrative, is hiring so many engineers.

So clever! Until I got an email from a reader, Kiran Maya Sheikh. She has a computer science degree from the University of California, Irvine. It's a great school, and she graduated with an impressive GPA. And yet, she's struggling to land that all-important first full-time software engineering job.

"It's bad advice to 'not worry,'" she wrote. "AI is causing disruption in this job market. Employers are prioritizing hiring experienced workers, but not new graduates."

This week, I interviewed Kiran for Tech Memo. It was an eye-opening view into the realities of the new AI economy. Here are the highlights from our chat, edited for clarity and length.

Alistair: What did you think you were signing up for when you first chose computer science as a degree?

Kiran: After getting into UC Irvine in 2020, I took my first coding class and I really enjoyed it. The prospects at this time were that people were going into this major to get great jobs and it was very rewarding and I ended up liking the work.

What did you believe a career in computer science would give you financially, socially, and emotionally?

The dream at the time was definitely everyone was saying, "Let's go work for Google and the FAANG companies and get a six-figure salary." My motivation was just getting a stable job, getting enough money to take care of my family — what everyone wants. I expected that computer science would put me in a position to grow as a software engineer, first and foremost, and then maybe take me to more of the strategic side, the management side. The main thing that I did figure out was that I wanted financial stability and maybe financial independence as well.

Fast forward to late 2022, when ChatGPT launched. Did you see that as a tool at the time or a threat?

I was a hater at the beginning. Then, friends of mine started using ChatGPT and they're like, "Oh, you can just use it like Google. You can just text it and it'll give you the answer." And honestly, my first thought was like, "That's a bit lazy. You can get more learning out of doing the work yourself." But the more time went on, the more that people were using it, and they started using it for class. Suddenly, I was ahead in class. I was doing the assignments well and understanding more.

Was there a moment when you thought generative AI might reduce the need for junior engineers, or do you even believe that?

We all know the current job market. It's not too hot and a lot of companies are citing AI as part of the reason for layoffs — but maybe that they were going to cut those jobs anyway. At the time though, while I was in school and using ChatGPT, I honestly didn't think it would get this far. I expected AI would be integrated into software engineers' work and companies would start integrating it, but I didn't realize there would be potential for it to take over jobs that I was looking for.

I don't think I was very attentive to the job market situation at the time, and I wasn't really thinking that far ahead. More of my worries at the time were just getting that first entry-level position. And I just thought it would be simple: I just get my degree and I would find a company that's hiring. Looking back, it was my mistake to not really research the current job market and maybe what some people were predicting about AI.

I didn't see it coming either. Few people did. Anyway, describe the moment when you realized the job market had changed?

I was already graduating, so this was after June 2025. I was getting into the reality of having to find my first job, and that's when I definitely started noticing something was wrong. A lot of my classmates, I haven't really heard of them getting any opportunities. Everyone's submitting so many resumes and there's a race to use AI to enhance resumes and send them out as fast as you can. And it seemed a lot more intense than I was prepared for.

A lot of my classmates and even students I know who are still in school are not even landing internships right now. It's not looking great. It's a very tough battle right now. So many people are quitting or getting fired or pivoting and there's new grads. Everyone is bracing, and it's a bloodbath right now.

Do you feel like you're competing against AI or laid-off senior engineers or both, or something else?

My fight is definitely with AI and all the competition with entry-level graduates — especially because AI is known to take over more junior roles. So it's important that we stay more relevant and offer something that AI can't. Scrolling through LinkedIn and on my job portals, I see more offers for mid-level positions, but I don't see as many for entry-level roles. So it's like I'm fighting AI and all these other graduates for roles that don't exist yet.

This job search so far, what has it done to your confidence?

I try to be optimistic. I am lucky to have a better situation than some other people do. I'm living at home with family, so I don't have to worry as much about expenses. Still, if I weren't doing anything about my situation, I would feel pretty bummed. I'd feel kind of trapped.

But I've been trying to work on building my network, finding people I know and learning from other people, just finding communities to be involved with. That's really helped my confidence because I find professionals that are trying to help — they are aware of the job market and they know how hard it is to get that first job. The one saving grace in this tough situation is definitely the community I've found and the people I know who are helping me through it.

Did you ever question your decision to study computer science?

Yes, I did question it. But I remember that I do like computer science and I did like what I learned. I really enjoyed my classes and programming. And instead of turning to a new discipline, I think I prefer to just specialize and find out new information and stay ahead of the news. And like I said, offer something that AI can't.

Do you feel like you were trained for a version of the tech industry that no longer exists?

I am a little salty, about this, if that's the right word. During my time at school, a lot of what the degree was about was learning the basics of software engineering. You learn programming languages and you learn how to set up your development and deployment. But right now there are so many more tools and I think that's the constant thing with the software engineering and the tech industry. There's always new technology and there's a lot of learning you have to keep up with.

But with AI in particular, I felt like I graduated a bit too early. Because now AI will probably be more integrated into learning. I had so many professors that were more welcoming towards AI. I remember a really cool professor who shared a website that would let you make your own LLM. And it's really useful stuff, but it wasn't part of the curriculum. It will be now, but I won't be there to see that change.

What I'm doing to help with that, and make the amends, is volunteering and doing more work on the side that involves newer technologies to just stay fresh and relevant and use all these new AI tools and see how I can leverage it.

If a high school senior asked you today whether they should major in computer science, what would you tell them?

It depends on what interests them about computer science. If it's absolutely something they're interested, they love learning about the technology and they want to code, I would still say go for it, but I would recommend how to position yourself for after college.

You need to start much earlier now, networking and knowing how to speak with people and how to apply, how to write a resume. And those all are also much more important now at the start of college, especially getting internships, if at all possible.

So, I would definitely recommend studying computer science, but being realistic about the opportunities available and keeping up with the news and the job market.

What would you say to potential employers out there?

The focus should still be in hiring entry-level talent if possible. I know it's tough with the current market and the economy and what's going on in the world right now. But entry-level talent is still important because you need to build this generation of professionals so that the future will have people to rely on. AI is still uncertain right now. People are still figuring out how it is impactful and it doesn't help to just force it upon your company.

Sign up for BI's Tech Memo newsletter here. Reach out to me via email at abarr@businessinsider.com.