In early 2023, Keith Peiris’s AI-powered presentation startup Tome was growing quickly. It had become the fastest productivity tool to reach 1 million users, Forbes reported at the time, a number that eventually climbed to 25 million. He raised $80 million from top Silicon Valley investors like Lightspeed Venture Partners, Coatue, Greylock and billionaire Reid Hoffman.
But by late 2024, Peiris realized he was building the wrong company.
It turned out that most people didn’t want to pay for its tools, which generated beautiful slides within minutes. Tome’s users, mainly students and small business owners, were largely on free plans or paying $10 monthly subscriptions—not nearly enough to sustain the business. And the startup couldn’t quite crack the market for professionals like marketers and salespeople because it wasn’t connected to their data and did not have the context needed to make good presentations. Users were still growing, but the company’s annual revenue plateaued at around just $3 million.
“Being frank about Tome, our technology thesis and our cultural thesis was very immature,” Peiris admits now.
With about half of Tome’s funding still in the bank and lots of GPU capacity on reserve, Peiris decided to pivot. “We were looking at this being like, ‘There’s no way that we’ve missed the boat in year two here. We’ve got a great team, a lot of capital. Why don’t we try again?’” he says.
So Peiris turned to billionaire Stewart Butterfield— who had twice turned his failed attempts at starting gaming companies into iconic businesses like Slack and Flickr— for “great sage advice” on pivoting. Butterfield told him to start fresh with a team small enough that it could be fed with two large pizzas. More importantly, Butterfield said, Peiris needed enough customer traction on a new product to keep investors and employees too busy to talk about the old days. In March 2025, Peiris shut down Tome and laid off most of his 70 employees, leaving a team of six.
Eight months later, he launched Lightfield, AI software that helps salespeople with busywork like summarizing calls, writing follow up emails and keeping track of client interactions.
His investors weren’t thrilled at first. A customer relationship management software was inherently harder to build and VCs questioned Peiris and his cofounder’s experience in this space. But it was a better business opportunity. “I think that there was animated discussion, but I think eventually everyone came around to it,” he says.”
Now the company’s revenue is growing 80% every month thanks to 1,000 paying customers including Substack, Goodfire and IntentHQ, Peiris says. So far, he’s built Lightfield entirely using funding raised for Tome, but he’s now in talks to raise more money. His previous backers are all participating.
Pivoting is a classic part of entrepreneurship. You try something, it doesn’t work as well as you thought, so you try something else. But that usually happens before a company gains substantial traction and raises a significant amount of money. Not so in the AI funding frenzy. Lightfield is part of the first wave of AI startups that raised a ton of capital, only to move away from what they initially built. While some have made hard pivots that entirely scrapped the original product or vision, others have expanded their focus to newer, more lucrative areas. The fast-paced nature of AI, has made it even more challenging for startups to remain defensible: Models improve so fast that the market is constantly shifting.
“As frontier models end up taking more and more oxygen in the room, I think what you’ll find is that a subset of these hot companies will either…do hard pivots or more likely they will find parts of infrastructure that they have built that they might want to spin out,” says Aditya Agarwal, a general partner at South Park Commons, a venture capital firm that works with tech founders.
Pika, for instance, raised $135 million to build an AI video generator but has evolved to building AI agents and avatars. Poolside raised $620 million to train AI coding models from scratch, but in late 2025 announced plans to construct a massive data center in West Texas called Project Horizon with CoreWeave — an effort that fell apart after Poolside wasn’t able to get chips online by CoreWeave’s deadline, the Financial Times reported. Poolside split itself into two companies, one focusing on infrastructure called PIC and another, to build models.
“I think it starts around a group of people that come together around a hypothesis that they may or may not reach,” says BCV partner Christina Melas-Kyriazi. “That plus capital has allowed these companies to take much more meandering paths than you would’ve otherwise seen in prior eras.”
Character AI, another early AI darling, has significantly transformed from the consumer chatbot app it first pitched to investors. Founded by Google Deepmind luminaries Noam Shazeer and Daniel De Freitas in 2021, the startup raised about $200 million from A-list backers like Andreessen Horowitz to generate AI characters inspired by real and fictional people that anyone could chat with, powered by its own large language models. The goal was to eventually “empower everyone with AGI,” Shazeer told Forbes in 2023. But in 2024, Google acqui-hired Shazeer and De Freitas and licensed Character’s technology for $2.7 billion. Then came a wave of lawsuits, which alleged that the company’s chatbots encouraged teens and minors to self harm, suicide and engage in sexually explicit conversations. In May 2025, board advisor and longtime Facebook executive Karandeep Anand took over as CEO.
That all seems to be distant history for the startup now. Character AI settled most of those lawsuits in January and banned under 18 users from chatting with characters on the app— a decision that cost it 4 million monthly active users. Instead of training models, it largely uses open source software. Instead of raising venture capital to release models or carry out research, the company is now fully bootstrapped and owned by its employees. Character AI has also been experimenting with new ways to monetize its products such as advertising and in-app purchases.
“A lot of the energy we’ve been focusing on is how do we not do the traditional ‘raise, raise, raise, raise money, grow, grow, grow.’ And we one day figure out whether this is a real business or not,’” Anand says. “Sustainable growth while also monetizing is very important to me.”
It’s now aggressively pushing into other non-text based forms of interactive entertainment, including releasing AI-generated audio stories, comics and microdramas, which are series of short video episodes produced with the help of AI. People can also chat with the characters featured in the stories. “Our goal has been on just expanding the ways people can experience this because not everyone is an avid typer,” Anand says.
But Anand says “pivot” is too strong of a word for the changes. “I would say this is more of an evolution,” he says.
That’s also how AI evaluation startup Patronus AI thinks of its recent change in strategy. The San Francisco-based startup got its start developing models to catch factual inaccuracies and flag responses that violated copyright, raising 20 million in funding from marquee backers like Lightspeed Venture Partners. Founded by Forbes 30 Under 30 alumni and ex-Meta AI researchers Anand Kannappan and Rebecca Qian, the San Francisco-based startup also built benchmarks to test how well AI models performed on financial, medical and legal tasks. But as the industry shifted towards AI agents, the startup began training so-called “digital world models” — replicas of internal systems and websites to test how well agents can complete tasks like ordering Doordash or booking a flight ticket. Patronus’s simulations help improve agents by rewarding accuracy and punishing errors.
It now calls itself a “frontier lab.” Today, these replicas account for 70% of its revenue, says CEO Kannappan, attracting top AI firms as customers. After releasing the new product, Patronus closed a $50 million funding round at a $400 million valuation. “I think it’s extremely important for us to continue to reinvent and rethink exactly what we do,” he says.
For others, pivoting was crucial for survival. Wispr AI cofounders and Stanford graduates Tanay Kothari and Sahaj Garg spent six months building a pair of headphones that converted a person’s neural signals and silent speech into text and voice. Three years and $14 million in funding later, the duo finally decided that it wouldn’t work. Plus they were scared off by major, embarrassing failures in consumer AI hardware, like Humane’s AI pin. In 2024, they decided to kill the hardware device, laid off most of their 40 employees and refocused on the AI-powered voice dictation software they had built for the headphones. “We had a 22,000 square foot office with five people in it,” CEO Kothari wrote in a blog post detailing the pivot.
Today their AI voice dictation app Wispr Flow has hundreds of thousands of daily active users and is growing 40% month over month. “We stopped chasing the sci-fi dream and started building what people truly needed,” the blog reads.
