With Kite’s demise, can generative AI for code succeed?
Kite, a startup developing an AI-powered coding assistant, abruptly shut down last month. Despite securing tens of millions of dollars in VC backing, Kite struggled to pay the bills, founder Adam Smith revealed in a postmortem blog post, running into engineering headwinds that made finding a product-market fit essentially impossible.
“We failed to deliver our vision of AI-assisted programming because we were 10 years too early to market, i.e., the tech is not ready yet,” Smith said. “Our product did not monetize, and it took too long to figure that out.”
Kite’s loss doesn’t bode well to the many companies that are pursuing and trying to commercialize generative AI for coding. Copilot is perhaps the highest-profile example, a code-generating tool developed by GitHub and OpenAI priced at $10 per month. But Smith notes that while Copilot shows a lot of promise, it still has “a long way to go” — estimating that it could cost over $100 million to build a “production-quality” tool capable of synthesizing code reliably.
To get a sense of the challenges that lie ahead for players in the generative code space, TechCrunch spoke with startups developing AI systems for coding, including Tabnine and DeepCode, which Snyk acquired in 2020. Tabnine’s service predicts the next line of code and makes suggestions based on syntax and context. DeepCode uses AI to notify developers about bugs as they code.
Tabnine CEO Dror Weins was open about the obstacles he sees to code-synthesizing system’s mass adoption. These were the AI itself, user experience, and monetization.
I’m a journalist who specializes in investigative reporting and writing. I have written for the New York Times and other publications.