In the rapidly evolving world of artificial intelligence, developers are increasingly adopting a ‘burn the boats’ mindset, embracing obsolescence and rapid iteration to stay ahead. This approach involves being willing to abandon existing work and switch to new technologies as they emerge, rather than becoming too attached to particular frameworks or methods.
Tuhin Srivastava, cofounder of AI inference platform Baseten, exemplifies this mindset. When Nvidia launched its new inference platform, Dynamo, Srivastava’s team was prepared to abandon their own platform and switch to Nvidia’s, demonstrating their willingness to adapt to the latest advancements.
The Challenges of AI Development
The story begins with DeepSeek’s AI model R1, which Baseten was working with earlier this year. The team faced significant challenges in scaling up inference, the computing process that generates AI outputs. Despite having access to Nvidia’s H200 chips, their inference platform was struggling with the demands of the advanced model.
Baseten’s Solution
To address this issue, Baseten built its own inference platform, as Nvidia’s Triton Inference Server was getting bogged down. However, when Nvidia launched Dynamo, an open-source software that helps Nvidia chips handle intensive inference for reasoning models at scale, Srivastava’s team was ready to switch.
“This is the thing about AI — you gotta burn the boats,” Srivastava told Business Insider. “When the juggernaut inevitably surpasses what we’ve built, we’ll abandon what we have and switch,” he said, referring to Nvidia’s Dynamo.
The ‘Burn the Boats’ Philosophy
This approach is not unique to Baseten. Many developers in the AI space are adopting a similar mindset, recognizing that machine learning is constantly evolving. Models become more complex, require more computing power, and then shrink again as engineers find new efficiencies.
“You cannot get married to a particular framework or way of doing things,” said Karl Mozurkewich, principal architect at cloud firm Valdi. Theo Browne, a YouTuber and developer, echoed this sentiment, noting that AI makes it possible to create things that were previously considered ‘super valuable and holy’ and then makes them ‘incredibly cheap and easy to throw away.’
Implications for Startups and Enterprises
This mindset often sets startups apart from larger enterprises, which can be slower to adapt. Quinn Slack, CEO of AI coding platform Sourcegraph, frequently advises Fortune 500 companies to be more agile in their AI development, telling them that “80% of them get there in an hour-long meeting.”
The Value of Pragmatism
Not everyone in the AI space is prioritizing the latest and greatest technology, however. Ben Miller, CEO of real estate investment platform Fundrise, is taking a more pragmatic approach, focusing on what works well enough for his customers rather than chasing the latest innovation.
“There’s no guarantee you’re going to grow your customer base or revenue just because you’re releasing the latest bleeding-edge feature,” Mozurkewich said, echoing Miller’s sentiment. For companies closer to the end-user, there are diminishing returns to moving fast and breaking things.
