Founder Story: May Habib of Writer

She arrived in Canada as a refugee at eight, edited the Harvard Crimson, and managed billions at a sovereign wealth fund before she ever wrote a line of code. Then she bet a struggling translation startup's entire future on transformers — twice — and built one of enterprise AI's most quietly formidable companies. This is how May Habib turned a near-death pivot into a $1.9 billion full-stack AI platform, and what her refusal to be a wrapper taught the industry.

Most founders can point to a single moment when their company was nearly over. For May Habib, the moment arrived in 2020, and it wore the face of success. Her startup, a translation-and-localization company called Qordoba, had just tripled its revenue. By every conventional metric it was working. And she decided to blow it up — to bet the whole company on a technology almost no one outside a few research labs had heard of. That bet became Writer, and it is now a full-stack enterprise AI platform valued at $1.9 billion.

A refugee's arithmetic

Habib's family fled rural Lebanon for Canada in the 1990s, when she was eight years old. That fact is not decoration; it shapes how she talks about risk to this day. When you have already survived the largest possible disruption to a life, the ordinary terrors of entrepreneurship — a failed round, a hard pivot, a competitor with more money — recalibrate. The downside of a startup is simply not the worst thing that can happen to you.

She channeled that steadiness into an improbable early résumé. Habib studied Economics and Near Eastern Languages and Civilizations at Harvard, where she served as Associate Managing Editor of The Harvard Crimson — an early sign of someone who took language and its precision seriously. Her most formative pre-founder role came in Abu Dhabi, where in 2009 she joined Mubadala, the UAE's sovereign wealth fund, as an M&A director helping assemble a technology portfolio worth billions. She learned how large enterprises actually make decisions — the procurement, the risk committees, the compliance gauntlet — long before she tried to sell to them.

Qordoba, and the pivot that made everything

In 2015, Habib co-founded Qordoba with Waseem AlShikh, a Syrian engineer who would become her long-term technical partner. Qordoba automated the localization of content across languages and regions. It was a real business with real customers, and by 2020 it was growing fast. It was also, Habib came to believe, aimed at the wrong future.

The transformer architecture — the breakthrough underneath modern large language models — had convinced her and AlShikh that generating and governing content itself was a far bigger opportunity than translating it. So in August 2020, they incorporated Writer, refocusing the company on a single mission: apply transformer technology to help enterprises produce consistent, on-brand content at scale. It was not a feature added to Qordoba. It was a new company built on the same team's conviction that a technological wave was about to break.

"The story of Writer is the story of the transformer. We started the company to build models, and with every big step-function change, we've either led it or been like four weeks behind."

That last line is the whole strategy in a sentence. Habib did not want to be a company that consumed models. She wanted to be a company that built them.

The unfashionable decision to build the models

In 2020 and 2021, the conventional wisdom for an application startup was clear: don't train your own models. Call an API, build a nice interface, focus on the workflow. Habib went the other way. Writer developed its own family of large language models — the Palmyra series, named after the ancient Syrian city, a nod to AlShikh's roots — and kept shipping new versions as the frontier moved.

The reasoning was rooted in that Mubadala-era understanding of the enterprise. Regulated buyers ask questions that a thin API wrapper cannot answer.

"How do we give a Goldman Sachs or a UnitedHealthcare information about our training data if we don't know what's in the training data?"

If you don't control the model, you can't answer for the model — and if you can't answer for the model, the largest customers in the world won't sign. Owning the full stack, from the LLM up through the guardrails, the graph-based retrieval, and the no-code tools, was not a vanity project. It was the price of admission to the accounts Writer wanted.

Selling to the enterprise, on the enterprise's terms

Writer's go-to-market reflected the same discipline. Rather than chase individual users, Habib went straight at the Fortune 500 — the Accentures, the Vanguards, the healthcare and financial giants — with a platform built around their non-negotiables: brand consistency, compliance, data control, and models trained on the customer's own material. The pitch was not "AI that writes." It was "AI you can actually deploy in a regulated company without your legal team stopping it."

Habib has been sharp about why so many rivals stumble here. In her telling, most teams approach generative AI the way they'd approach ordinary software, and it doesn't translate.

"The vast majority of teams that are trying to build generative AI applications are approaching it like they would traditional software development, and we think that's kind of like bringing a knife to a gunfight."

Generative AI, she argues, breaks the old mental model in a fundamental way — even the idea of a finished product. "Generative AI challenges the concept of done," she has said. "You need the ability to continuously be building and monitoring." A company that ships a static tool and walks away has misunderstood the medium.

The money follows the conviction

Investors, eventually, came to the same conclusion. Writer raised $5 million in seed funding in 2020, then a $100 million Series B in September 2023 led by ICONIQ Growth, with Insight Partners, WndrCo, Balderton Capital and others joining. The defining round came in November 2024: a $200 million Series C at a $1.9 billion valuation, co-led by Premji Invest, Radical Ventures, and ICONIQ Growth, bringing Writer's total raised to $326 million.

The investor list on that Series C tells its own story — Adobe Ventures, B Capital, Citi Ventures, IBM Ventures, Salesforce Ventures, and Workday Ventures, alongside Accenture, Balderton, Insight Partners, and Vanguard. When your cap table is populated by the strategic arms of the very enterprises you sell to, it is a strong signal that the full-stack bet landed. As the agentic wave arrived, Habib had a characteristically vivid read on why demand accelerated: "Agentic AI is like the straw that broke the enterprise's back when it comes to generative AI, and people are understanding they can't be doing all of this themselves."

Leading through permanent change

What stands out about Habib is not just the pivot but her comfort with never being finished pivoting. "We are in a constant state of re-establishing product-market fit as a generative AI company," she has said — a sentence most founders would be terrified to admit and she states as a plain operating condition. In a field where the ground shifts every few months, she treats instability not as a threat to be survived but as the environment to be mastered.

That posture traces straight back to the eight-year-old who left everything behind and rebuilt. Habib's whole career is an argument that adaptability, not certainty, is the founder's core asset. She built Writer for a world where the technology, the customers, and the definition of "done" are all in motion — and made that motion the company's advantage rather than its excuse.

Closing Thoughts

May Habib's story rearranges the usual founder mythology. She wasn't a teenage coder; she came to technology through economics, finance, and the machinery of how big institutions buy. She didn't chase the trend of the moment; she killed a growing business to get ahead of a wave she saw coming. And she refused the easy path of being a wrapper, choosing instead the harder, slower work of owning the full stack because that was what her customers truly needed.

The throughline is conviction under uncertainty — the willingness to make an irreversible bet before the outcome is obvious, and to keep re-betting as the world changes. "AGI doesn't mean God," she once put it. "It means super, super good." That is the sensibility of a builder, not a believer: pragmatic, precise, and unafraid to start over. For any founder staring down a pivot, that is the most useful thing she has to offer.

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