Glean, a company often described as the Google for enterprise, said it has reached $300 million in annual recurring revenue (ARR), a three-fold increase from the $100 million milestone it reached just 15 months ago.

While many AI startups are growing at a blistering pace, Glean’s progress is particularly remarkable. After years of essentially being the only player in the category, the seven-year-old startup is accelerating its growth as tech giants enter the enterprise AI search market with rival products.

“The first four or five years of our existence, we had no competition,” Glean CEO Arvind Jain told TechCrunch. “Given how important search is to make AI work in the enterprise, every single company in the world wants to be in this space.”

Tech heavyweights building Glean-like tools include Google, Microsoft, OpenAI, Anthropic, Salesforce, and Atlassian.

Jain maintains there’s value in being a first mover in the space, but that it’s also equally important to offer a better product.

What Glean does better than its competition, according to Jain, comes down to the deep understanding that its AI tools have of customers’ business needs. Glean’s AI achieves this knowledge — a concept captured by the new, popular term “context graph” — by connecting to and learning from enterprises’ internal software systems.

Jain claims that Glean’s context graph also helps enterprises cut AI computing costs.

“If you connect your AI to Glean, it gives you all the information that you need to do your work, and that results in AI consuming far fewer tokens compared to if you unleash AI onto your systems directly,” Jain said. That’s because with Glean, AI ends up performing fewer operations, he added.

At a time when many companies are blowing through their AI budgets, those token cost savings have become a major selling point for the company.

“One of the things you know our customers really like about Glean is the fact that we can reduce your AI bill significantly,” he said.

The company, which was last valued at $7.2 billion when it raised a $150 million Series F last June, offers various pricing structures to its customers, which include Databricks, Reddit, Pinterest, and Samsung.

According to Jain, Glean offers both a consumption-based model, where clients pay per use, and a hybrid model that combines a fixed monthly fee for active users with separate usage fees for model consumption.

Glean is definitely not the first company to do this, but it’s worth pointing out that the company’s $300 million milestone cannot be fully described as traditional ARR, because a consumption model by definition doesn’t have a strictly recurring component.

Pure consumption pricing models depend on fluctuating user activity rather than predictable subscription renewals, therefore a portion of Glean’s top line is more accurately described as an annualized revenue run rate.

Glean did not immediately respond to a request for comment; this post will be updated if the company replies.

TechCrunch Disrupt 2026 returns October 13–15 to Moscone West in San Francisco — and applications to speak are open for just a few more hours.

We’re inviting founders, investors, operators, and technology experts to apply for a chance to take the stage at one of the most influential tech events of the year.

More than 10,000 startup and VC leaders will gather at Disrupt 2026 to explore what’s next in AI, scaling, fintech, infrastructure, robotics, and the future of innovation.

Applications close tonight at 11:59 p.m. PT. Apply now to share your expertise and help shape the conversations defining the tech industry.

Pick your session format

We’re looking for high-impact speakers to lead one of two session types:

Breakout Sessions: A 30-minute talk (up to 4 speakers, including a moderator) with a 20-minute audience Q&A. Capacity: 100 attendees.

Roundtables: A 30-minute speaker-led group discussion, designed for up to 40 participants. No slides or AV — just insight and conversation.

How the application process works

Each application will be carefully reviewed by our editorial team. Finalists will be selected for the Audience Choice vote — where TechCrunch readers choose which sessions make it to the Disrupt Stage. Learn more about speaking on Disrupt’s Call for Content page.

Lead the conversation at Disrupt 2026

If you have actionable insights, real-world experience, and a desire to contribute meaningfully to the tech ecosystem, we want to hear from you. Submit your application before today’s deadline.

Cognition CEO Scott Wu made headlines again this week when his two-year-old AI coding agent startup raised $1 billion at a $26 billion valuation. Cognition is the maker of Devin, one of the first and, arguably, most successful AI coding agents. Devin, the CEO says, “naturally owns tasks end to end.”

In fact, in the blog post announcing that raise, Cognition laid out a vision where “we are shifting to a world of self-driving software development.”

So, could Devin replace, say, a mid-level L4 programmer? Yes, and no, Wu told TechCrunch. “We’ve never thought about it as replacing humans. I know it’s like a scenario, folks have said these things. It has never been our view.”

In this wild year of 2026 when every day another tech CEO announces layoffs in the name of supplanting workers with AI, Wu says he especially doesn’t want coders to lose their jobs. “We are all programmers ourselves,” he explained. “I started coding when I was nine.”

In fact, Wu has been called one of the most accomplished child competitive programmers of all time, according to a recent profile in Colossus. As a second-grader, Wu won a nationwide math competition for seventh-graders, which launched a childhood filled with math and programming tournaments. It also introduced him to other wunderkinds who went on to launch other AI tech startups, like Scale AI founder Alexandr Wang.

So, he tells TechCrunch, the idea was never to make human programmers obsolete.

“When we started building Devin, it’s kind of a funny thing,” he mused, “but we really just thought of it as: this is your buddy who helps you build more.” In fact, he showed off a little stuffed animal holding a computer, his own Devin teddy bear of sorts, that he keeps on his desk. He thinks of it as a physical symbol of the Devin AI coder “This is my buddy that helps you build more.”

Wu doesn’t want AI agents to take the joy of programming away from people.

“It’s not a secret, most software engineers love building software, right?” he said. “If you ask them why, what they’ll basically tell you is, ‘Well, it’s like I get to build things from nothing. I can make my whole idea that I have, and turn it into a product. I can turn it into an experience.’”

Just like visual development environments abstracted software creation away from machine instructions, he views agents as another layer of abstraction between envisioning a software product and producing it.

Yet, Cognition says that Devin’s role in its own company is to ship nearly all the software. The company says that 89% of code committed by its engineers was committed by Devin, and the rest by local agents in Windsurf, the AI coding competitor it acquired last year.

Wu explains that his agent’s role is largely to do the kinds of long-tail maintenance tasks that many programmers don’t like to do anyway: bringing old software up to date; moving applications off one platform and onto another. Agents will free programmers “from a lot of the toil, and so they can do much more of the creation side,” he promises.

So Wu bristles at the idea of Devin “replacing” human coders. While he says it can work independently, it works at “somewhere between a junior and a mid-level engineer” depending on the task at hand.

As for the concept of self-driving software, where the agent learns and improves itself so that one day it will work at higher levels (“recursive” is the latest buzzword in AI these days), Wu says. “I think we are in for a wild ride.”

He sees agents entering other fields where they will learn tasks, from customer service to medicine, but hopes the goal will be to augment human workers in those areas, too.

“Code and software has been the first to move, but we’ll see this happen in all these other industries,” he predicts. “One thing that’s been clear to us since the beginning is, it should always be up to the human what to do … you really see this in software engineering, but I think it’s true in all these other professions too.”