COO at @linear. previously building at @stripe, @NotionHQ & @firstround. angel investor to ~80 early-stage startups
San Francisco, CA
Joined March 2009
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Cristina Cordova retweeted
Issues created in @linear by people and via MCP are up 400% this year.
Another fast growing trend: more customers are building their own internal agents and using Linear as the shared layer for workflows, communication and context between people and agents.
As teams move faster, connecting goals, requests, reasoning and the work matters more, even if it sometimes happens after the fact in the review.
Here is one customer oriented example we can do in our Linear:
- Pick a top-10 customer. Ask the agent for a brief of their top requests and the reasoning we've captured
- Write it to a doc in Linear and decide what to build with some people
- Have the agent turn the decisions into projects and issues, carrying the customer requests and meeting notes with them
- Teams send their agents to work on them
- At the QBR, ask agent to generate a report and show the customer what has actually landed or them, how and why
Now multiple these kind of workflows 100 or 1000 times where someone is learning something worth fixing, or trying ideas and finding beta customers for it. Or just aligning across the team or cross function.
Not posting our revenue chart, but it looks a lot like this one
Imprint’s CTO @Lethain said almost no one thought moving to @linear was a good idea. He wanted agents to find tasks, pick them up, and do the work, so he pushed the decision through. Now his team is glad he did.
Part of being an exec is taking the right chances before there’s consensus.
As Linear’s COO, I’m also glad Will didn’t get fired. 😉
Cristina Cordova retweeted
Often simplicity just works.
Companies moving over and now creating their docs in @linear
We're building Linear to power how the world's best teams create software. From the beginning, Stephanie has understood that ambition, pushed us to think bigger, and done the work alongside us to get there. Excited to see her bring that same conviction to a new generation of founders.
I’m starting a new early-stage AI fund, doing what I love: partnering with founders from company formation on bold bets, long before consensus.
The fund’s LPs will include Sequoia, Jeff Dean, Sachin Katti, Philip Wong (my Stanford professor and Chief Scientist adviser to TSMC), and others whose work has shaped our industry and how I think about AI’s future.
I’ll remain a partner at Sequoia and keep serving on my boards on Sequoia’s behalf.
Sequoia has been my home for the past 11 years. I joined as the youngest investor the firm had ever hired. I grew up here. Through years of intense debate and shared work, I found lifelong mentors and friends who took me under their wing and taught me this craft. They taught me to aim high and take big swings. I’ll carry that into what I build: outsized ambition, relentless truth-seeking and curiosity, and a refusal to become complacent.
Working alongside founders has made me want to build something of my own: a firm shaped from day one around the convictions I’ve developed over the past decade.
Life has taught me not to take time for granted. This is how I want to spend mine.
Why now
We’re seeing a new way of building companies in today’s AI era. Research and products often advance together. A breakthrough can open a market or accelerate a business far faster than expected. Some companies require extraordinary capital and compute early on. Others reach meaningful scale with remarkably small teams. The rules for how big these businesses can get, and how fast, are being rewritten.
But early on, the technology is unproven, the resources required enormous, and the vision seemingly implausible.
This is what I love most: seeing the potential right from the beginning, and helping founders realize their full scale of ambition.
More than ever, it starts with an extreme willingness to believe early, with bold, independent conviction in a founder’s technical insight before any product or market validation. Then, it means helping founders take the biggest swings, giving the rare, long-term patience to see those bets through uncertainty, ambiguity, and turbulence, and serving as a level head when the stakes are highest.
I learned this kind of partnership at Sequoia. It’s the foundation of the firm I’m building.
Believing before consensus
My fascination with AI’s potential took root at Stanford in the early-to-mid 2010s, studying computer science and working in Andrew Ng’s lab. The friendships I formed connected me to a community whose people and ideas would help shape modern AI and build some of our generation’s defining companies. What stayed with me was the gap between what those people saw was possible and what the wider world could imagine.
I’m drawn to founders pursuing ambitions that sound impossible today.
I start with a simple question: “What if everything goes right?”
Then we work backward together to make it happen.
In 2023, Deepak and Abhinav set out to build a general-purpose robot brain at @SkildAI, before physical AI was a consensus bet. Their sim-to-real breakthroughs gave me conviction where earlier robotics approaches had fallen short. But the data flywheel required deployment at scale. We made commercialization as urgent as research and brought in strategic partners like NVIDIA and SoftBank to support the ambition. Three years in, Skild is advancing the frontier of physical AI with nine figures in annualized revenue.
In 2024, Ioannis and Misha founded @reflection_ai with an insight into scaling reinforcement learning. As that grew into the ambition to build a Western frontier lab for open models, the hard question was how a startup competes with labs spending tens of billions. An introduction to NVIDIA and many compute calls and recruiting events later, the team has built Beam, now one of the leading US open models.
In 2025, Anna and Azalia, the co-creators of AlphaChip, founded @RicursiveAI to design models and hardware together. From day one, we made early customers and ecosystem partners a priority. Today, they are showing order-of-magnitude improvements on real workloads, working with some of the industry’s most consequential players, and reaching a defining inflection point.
The ambition keeps growing as these companies scale.
@linear has always had a kind of magic to it. Now it’s the system a new generation of AI companies builds on, for teams and agents alike.
@tavus saw early that we’d one day talk to AI the way we talk to each other. Today, it’s building the human computing interface for a world of AI colleagues.
@Mach_Industries began as hydrogen experiments in an MIT dorm room. It has since become one of the most exciting next-generation defense companies.
Making the ambition possible
Being a first believer is only the beginning. Compute falls through. A deep-pocketed incumbent makes your mission its top priority. A breakthrough changes the opportunity and the capital required overnight.
These are stomach-churning moments, and early belief carries a responsibility to help make the bet work.
This is the partnership I love: turning the full ambition into concrete steps. Raising capital, securing compute and strategic partners, recruiting exceptional people, and winning the first customers together. Thinking several moves ahead while solving what’s in front of us. And as breakthroughs open new possibilities, helping founders dream even bigger.
Thank you
To the founders I’ve worked with: thank you for trusting me and Sequoia to be your first partner and first believer. It’s been the joy of a lifetime, and I can’t wait to keep building together.
Thank you to Alfred and Pat for your leadership of Sequoia and your support of my next chapter. To Roelof, for bringing me into Sequoia and believing in me from the beginning. Alfred and Roelof, you have been mentors in investing and in life. So much of what I know, and the investor I’ve become, comes from your guidance and generosity over the years. To Bill, for the close partnership and wealth of knowledge, always wrapped in humility. To Shaun, for showing me how to think deeply and imaginatively. To Michael Moritz, for inspiring 22-year-old me to dream big. To Doug, for teaching me to keep things simple. To Bogie and Jess, for bringing joy to the everyday and perspective on what matters. And to all my Sequoia teammates, for the friendship, camaraderie, and lessons I’ll carry with me.
To my family, especially my husband and my brother, who have each started companies of their own: thank you for giving me the courage to take this leap.
Let’s get to work!
Nothing makes you feel like a fintech veteran like remembering when you could put "banking" in the headline without a footnote explaining that, legally speaking, you’re absolutely not a bank.
My first startup internship was in Palo Alto around 2009. The financial crisis had just wiped out the jobs many of my classmates expected to have. Banking and consulting offers were being rescinded. Some of us found our way into startups because we needed a job -- any job. Others passed up Google because they wanted to work on something they believed should exist.
It would be easy to romanticize this. People wanted to make money then, too. But joining a startup wasn’t an especially reliable way to impress anyone. You usually had to explain what the company did, and sometimes why you'd joined it.
Someone asked me why I joined Stripe when it was small. You could already accept credit cards online. What was new or innovative about that? It was a reasonable question. The opportunity seemed obvious to the people working on it, but it wasn’t obvious to everyone else. That gap was part of the appeal. You could see something worth building before there was much social reward for seeing it.
In the early 2010s, teams like Pinterest and Stripe were still in Palo Alto. As Palantir took over more of downtown and space became harder to find, those teams chose to move to SF instead of further south to Mountain View or San Jose. We were in our early 20s. Of course we wanted to live in the city.
Over time, friends who'd gone into banking and consulting moved into tech too. Tech companies had become THE companies. SF became an industry town, and a career that once required some explanation became the obvious choice.
The odd thing about startups becoming prestigious is that they attract people who would never have joined one before they were prestigious. The ambition is still there, but more of it goes toward looking successful before you’ve made anything work.
You can see it in founders creating videos holding an influencer mic, or in a room where working at OpenAI is more interesting than starting something nobody has heard of. The famous company gives people a shortcut... they can be impressed without having to form an opinion of their own.
That’s what I miss. There was a time when joining a startup meant being willing to look unsuccessful for a while.
Cristina Cordova retweeted
Ticket requests for Orbit (by Linear) are now open.
Join us in San Francisco on Dec 9 for an exploration of the future of product development: If we can produce more software than ever, what does it take to make it good?
orbit.linear.app
One thing I learned at Stripe is that moving money is only part of the problem. Knowing where it came from, where it went, and why is just as important.
As agents start making financial decisions and moving money autonomously, that infrastructure becomes more critical.
Excited to see Fragment building the financial primitives for this next era of commerce. Congrats to @neckelthomas and the team on the $12M raise!
Fragment is automating commerce.
We think there are millions of businesses that haven't been invented yet. Not because folks lack imagination, but because it's too hard to build the financial systems that run them. Fragment removes that constraint.
Today, people run companies. With Fragment, they'll run on their own.
fragment.dev/v2
Cristina Cordova retweeted
Counter argument: Not only is taste subjective, it's a moving target. As soon as [tasteful thing] becomes easily replicable, it stops being tasteful.
Taste is a status game with a strong defensibility mechanism. That's why the term is so fuzzy and ill-defined. Vagueness is the whole point. It's meant to be hard to copy.
Cristina Cordova retweeted
Linear is becoming the place to drive more work forward in your orgs.
A customer shared this chart showing dramatically faster & automatic bug resolution after enabling Loops + @linear Cloud Coding Agent (claude/codex/open):
> Their 95th-percentile time from bug report or customer request to a fix in production dropped from 9 weeks to 3 days over three months.
Some use other use cases for Loops:
- cleaning up deprecated code
- investigating and fixing bugs
- routing customer requests to whoever is on call
- monitoring security vulnerabilities
- checking up on important projects or customer themes
We use Loops to automate recurring work across Linear, from triaging security vulnerabilities to cleaning up deprecated code.
Here are five things @twokeyboards, one of the engineers building Loops, has learned about delegating work to agents:
linear.app/now/five-principl…
🪄
Back in the old days, a request like this would have taken five stakeholder alignment calls, 10+ Jira tickets, and 3 months of wait time because the backlog is choked.
Kudos to @linear for building a product that borders on giving magical PM abilities.
Cristina Cordova retweeted
Linear CEO @karrisaarinen: "I took a break this summer from paying attention to AI. I thought that when I came back, I'd feel left behind. But when I came back, I realized that nothing has really changed.
There's new models, there's new techniques, there's new agents. But in the end, making great products, increasing revenue, and building the business—it's still hard.
It's clear the tools are getting better, you can do more, you can do it faster. But I think the more important question is: are we actually making better things with these tools? Are our teams getting better with these tools?
I don't think that answer is clearly yes.
There's a lot of emphasis now on toolmaking and using tools and building systems. But I think in the end, as product people, our job is to make something great."
Got this text from a friend this morning after their large public tech company rolled out Linear:
“Whereas I just used [legacy tool] when I had to, with Linear I actually… want to use it.”
Your context will always be wrong if people only use your system when they’re forced to.
That’s why we invest so much in making Linear great for the builders actually doing the work. The best system of record is one people want to keep up to date.
Ambitious startups should get to use the best tools from day one.
More free Linear for the companies of tomorrow thanks to our partnership with Claude!
The strongest brands are built through the product and the experience around it.
Excited to co-host this conversation with Warp and hear how leaders from Cash App, Coinbase, and Plaid think about making a brand feel inevitable.
Join us tomorrow in SF!
Some brands feel inevitable. Tomorrow I'm on a panel for SFTech Week with four people who have built that feeling at scale:
Cristina Cordova, COO at Linear
Hannah Hughes, CMO at Plaid
Ben Shen, Product Lead at Coinbase
Michael Duane, Product Lead at Cash App
We'll get into what an inevitable brand takes when your customers are both humans and agents, and how you keep the design simple while the technology underneath gets harder.
That's the bar I've set for Warp's brand. Analog precision meets velocity. Engineered for performance, designed with soul.
What I've learned so far is that inevitable brands are built on details nobody sees, and they get those details right every time, for years, until the result just looks obvious.
RSVP link in the comments
Peer hasn’t opened a Linear ticket by hand in three months. I believe him. Most of my own issue creation now happens through Slack and the Linear Agent.
So we’ve been watching a question closely -- as agents get access to Linear, do people stop using the app?
Over the past year, weekly MCP usage has grown roughly 20X from a much smaller base. The number of people using Linear’s app each week has grown significantly too.
Today, about 84% of weekly active users use the app, 48% use MCP, and 12% use an OAuth integration. Those groups overlap. People use different ways to work with Linear. Paid seat utilization is also higher than it was two years ago.
Creating an issue may move to an agent. But the team still needs a shared view of its work. Making it easier to get information into and out of Linear may make that shared view more valuable.
For SaaS companies, the question is broader than whether agents take clicks away from the app. Watch whether human engagement falls as agent activity rises, and whether the product becomes more central to the work. At Linear, app and MCP usage are both growing. We’ll keep watching to see how user behavior and our product evolves along side it.
i was skeptical about this until really good chat agents happened to come around
for the past 3 months i have not opened a @linear ticket by hand (pressing buttons no more)
mostly slack and in-app chat
Nothing says “modern enterprise technology” quite like someone trying to recall an email as though we’re operating a telegraph station in 1954.
Meanwhile, hitting recall doesn’t erase your screw-up. It just sends everyone a second email announcing, “Hey, remember that email you weren’t supposed to see? Yeah, that one.”
Cristina Cordova retweeted
why i think @linear 's agent session is the best collaboration surface for agentic work (even better than slack):
- every task is tracked as an issue in linear's beautiful ui
- your job to be done is already described clearly in the linear issue description, so you can give your agent more precise commands compared to in slack
- prompts for agent (agent session) is separated from discussion between people (comments), so you don't have to scroll down a full thread to find the next thing your teammate says after a long agent reply
- people can steer the agent's work, even if the work is running on someone else's computer (with the help of @usemerlin_ai)
- you can view the full agent tool call history, in comparison, in slack, you can only view the latest one
- linear doesn't charge anything for it. it only costs you the api fee, and you can even use your own subscription if you're using Merlin as the agent delegation