When a viral tweet two years ago declared “Airtable is dead,” CEO Howie Liu remembers being stunned, not by the claim itself, but by how far and fast it spread. “They literally had incorrect numbers by a strong multiple on what our revenue scale was,” Liu recalled in a recent interview with Lenny’s Podcast. “And yet this particular tweet went super viral.” For Liu, the moment crystallized something about how narratives, true or not, move faster than facts. It was a lesson in the power of speed, something he’s now trying to harness as he reorients Airtable into an AI-native company.
“Refounding” Airtable
Liu describes the AI era as so transformative that “every software product in my opinion has to be refounded.” For him, that meant stepping back into the weeds, even into the code, in what he and peers call the “IC-CEO” model: chief executives who act like individual contributors again. “AI is such a paradigm shift… with every new model release, it actually implies novel form factors and novel UX patterns to be invented,” Liu said. “To be continuously relevant, you have to be in the details.”
“I take pride in being the number one most expensive inference-cost user of Airtable AI.”
That return to details has reshaped Airtable’s product. The company has rolled out Omni, a conversational builder that lets users describe the app they want and watch as Airtable generates it. It has also launched AI Field Agents: agents that live inside customer apps to run tasks like research, analysis, or automation. And its new storage layer, HyperDB, supports up to 100 million records, making the platform viable for enterprise-scale deployments.
Liu reorganized Airtable’s engineering and product teams into what he calls “fast thinking” and “slow thinking” groups. The fast group, officially the AI Platform team, ships capabilities at what he hopes is a near-weekly cadence. The slow group focuses on deliberate, infrastructural work like HyperDB. “Fast execution creates the top of funnel excitement,” Liu said, “while slow thinking allows those seeds of adoption to sprout and grow into larger deployments.”
Playing With AI
If there’s one message Liu drills into his team, it’s to play. “I’ve even said look, if anyone wants to just literally block out a day or frankly even a week and cancel all your meetings to play around with every AI product you can find… go do it, period.” He models that behavior himself, sometimes racking up hundreds of dollars in inference costs while experimenting. “I take pride in being the number one most expensive inference-cost user of Airtable AI,” he laughed. “Hundreds of dollars spent on this exercise is trivial compared to the potential strategic value of better insights. You could pay a consulting firm millions to get that quality of work.”
This constant hands-on use, he argues, is the only way to truly understand what AI can do. “It’s like as a chef you just gained access to amazing new ingredients, but you have to actually get comfortable with them to put them into a new dish.”
AI Renaissance Men
“The ideal person may be specialized and deep in one dimension, but they’re well-rounded enough to be dangerous on the others.”
In Liu’s vision, product roles themselves are being rewritten by AI. “It really does become more about individual attitude,” he said. “There’s a strong advantage to any of those three roles, PM, engineering, design, who can cross over into the other two. As a PM you need to start looking more like a hybrid PM-prototyper who has some good design sensibilities.” He goes further: “I think you need to get decently good at all three. There’s just a minimum baseline.”
That ethos extends beyond engineering. In marketing, he argues, the traditional division of roles between copywriter, campaign manager, and creative should collapse. In sales, reps should be able to play a sales-engineering role. “The ideal person may be specialized and deep in one dimension, but they’re well-rounded enough to be dangerous on the others.”
Building for Speed
Liu measures success against the new generation of AI-native startups. “I basically want to always ask the question: how would an AI-native company execute? Are we executing as fast as them and taking advantage of all the new stuff as well as them?”
The reorg is designed to answer that. Fast-thinking pods prototype new AI experiences like code-generation extensions in Omni. “There are so many watermelons on the ground,” Liu said, invoking his favorite metaphor. “Just go out and pick the biggest ones.”
Yet speed is to be balanced with durability. For all the hype about AI tourists (users who try an AI product once and move on) Liu insists Airtable must build for sustained enterprise adoption. “The challenge for many AI-native companies I’ve seen is that they can have a very wide top of funnel, but how do you turn that into more durable growth? Our slow thinking is what lets those adoption seeds retain and expand over time.”
“AI is such a paradigm shift… with every new model release, it actually implies novel form factors and novel UX patterns to be invented.”
A Clean Slate
Airtable’s rivals aren’t standing still. Notion and Coda are embedding AI deeply into their document-first platforms. Monday.com has aggressively productized enterprise AI features and has already reported tangible business upside. Smartsheet, Asana, and Wrike are layering AI into project management. Liu knows Airtable’s differentiation: structured data and app-building at enterprise scale. will only matter if executed with speed. “You can’t just throw in some AI features and call it a day,” he warned. “You have to take a clean slate approach.”
Liu frames Airtable’s pivot as an eventuality. “If we started Airtable today, this is what we would be all in on,” he said. The company’s Lego-like building blocks, he argues, give it a unique advantage: reliable primitives that agents can assemble into robust business apps without coding from scratch. “If I didn’t fully and truly believe we have a better shot at doing it with our existing product, I wouldn’t be running this company in its form today.”
For Liu, the gamble is: Airtable must not only survive the AI transition, but prove it can lead. “AI is moving incredibly fast,” he said. “The only way to taste the soup is to be in the kitchen.”
